DeepSeek V3.2 Speciale

Exact model and requirements

Artifact:

DeepSeek AI native checkpoint; reader-authored conversion, not a publisher GGUF / Full DeepSeek V3.2 Speciale reader-converted Q4_K_M · checkpoint deepseek-ai/DeepSeek-V3.2-Speciale

Publisher revision:

c562883eda916fd699a44bbf1f4987a53b96008b

Artifact digest:

Final reader-generated GGUF composition and SHA256 are unknown until that exact conversion; reader records and checks every output split before serving.

Download size:

Unknown

Memory requirement (unknown):

Unknown — Lazy conversion limits eager tensor loading but does not prove 512 GiB peak for conversion, quantization or serving. Routing/expert buffers, DSA/MLA cache, mapped inputs, scratch, OS and output state remain unknown.

System RAM / disk:

Unknown / Unknown

Placement:

single device. One CPU host. Actual reader-generated F16 and Q4_K_M disk split counts remain unknown until complete conversion; every numbered split is required. No device, tensor or pipeline sharding. All language layers, routed/shared experts and DSA/MLA computation on one CPU host; no GPU offload or selective expert subset.

KV cache:

F16 cache flags are explicit; native DSA maintains separate MLA and lightning-indexer state. Exact state layout and working-memory peak remain unmeasured.

Workload:

16,384 token context; Unknown; Unknown; concurrency 1; batch 1; cache unknown; repetitions Unknown.

Tokenizer:

Exact Speciale native tokenizer with authoritative native Python encoder; conversion-only BOS metadata adjustment is explicit · c562883eda916fd699a44bbf1f4987a53b96008b

Sampling / reasoning:

Native publisher recommends temperature 1.0 and top_p 0.95 for local deployment. Top_k 0, min_p 0 and repeat_penalty 1 are author choices. True native EOS is mandatory; length/word stop cannot substitute for complete reasoning and final text. Speciale is exclusively a deep-reasoning checkpoint and explicitly does not support tool calling. Both initial arithmetic and follow-up use native thinking mode with history and dropped past reasoning. Require actual EOS, nonempty closed thinking and nonempty final answer. No ordinary chat mode, tools, Jinja substitute or reasoning-disable switch is provided. 16,384 total / 8,192 output is an author short-fixture allocation, not a publisher full-reasoning recommendation.

Runtime prerequisites:

Ubuntu 24.04 x86_64; See prerequisites above.

Official artifact · License

Exact Speciale native card explicitly grants repository and model weights under MIT. Retain the copyright/permission notice in copies or substantial portions; the actual license disclaims warranties. Reader conversion is a modification with no publisher quantization-quality or byte-equivalence claim. No terms acceptance, commercial guarantee or legal clearance is performed for the reader.

• Native Speciale Python encoder/parser · 0 GiB · revision c562883eda916fd699a44bbf1f4987a53b96008b

• All 163 native safetensors inputs total 689,483,049,129 bytes. The native index metadata total_size is 1,370,793,842,752 bytes; it is not the serialized FP8 sum or a measured F16 GGUF size.
• A 4 TiB working filesystem and 512 GiB RAM are author allocations, not measured fit/minima. Native inputs, F16 intermediate and final quantized output coexist; scratch/loading/package/build space adds unknown demand. Stop if actual disk/RAM cannot accommodate the workflow.
• Full native 61 main layers, routed/shared experts and DSA lightning indexer remain. The converter preserves appended NextN by default; no --no-mtp, tensor removal, active-expert-only or no-light derivative is used. Speculative MTP execution remains outside this ordinary autoregressive reasoning guide.

Install the runtime

1. 1. Build pinned CPU tools and qualify the reader conversion environment

   Build exact native CPU tools and install the official CPU wheel into an isolated Python 3.12 venv. Its hash comes from the archived official wheel index, not a wheel downloaded by the author. Use exact checkout requirements; no custom conversion kernels or native architecture patch. Stop on any error and retain actual environment logs.

   CommandCopy command

   set -e
   sudo apt-get update
   sudo apt-get install -y build-essential cmake git curl ca-certificates openssl python3.12 python3.12-venv
   mkdir -p "$HOME/deepseek-speciale-hosting" 
   cd "$HOME/deepseek-speciale-hosting"
   python3.12 - <<'PYDISK'
   import shutil
   assert shutil.disk_usage('.').free >= 3*1024**4, 'Provide the planned 4 TiB filesystem with at least the author-selected 3 TiB free preflight floor; actual peak remains unknown'
   PYDISK
   git clone https://github.com/ggml-org/llama.cpp.git
   git -C llama.cpp checkout --detach 620d2225cc436ab0b001e3200e590e3b286ef9ab
   test "$(git -C llama.cpp rev-parse HEAD)" = 620d2225cc436ab0b001e3200e590e3b286ef9ab
   cmake -S llama.cpp -B llama.cpp/build -DCMAKE_BUILD_TYPE=Release -DGGML_NATIVE=ON -DGGML_METAL=OFF
   cmake --build llama.cpp/build --config Release -j 16
   python3.12 -m venv .venv
   curl --fail --location 'https://download-r2.pytorch.org/whl/cpu/torch-2.11.0%2Bcpu-cp312-cp312-manylinux_2_28_x86_64.whl' -o 'torch-2.11.0+cpu-cp312-cp312-manylinux_2_28_x86_64.whl'
   echo 'f82e2ae20c1545bb03997d1cc3143d94e14b800038669ee1aca45808a9acc338  torch-2.11.0+cpu-cp312-cp312-manylinux_2_28_x86_64.whl' | sha256sum --check
   .venv/bin/python -m pip install './torch-2.11.0+cpu-cp312-cp312-manylinux_2_28_x86_64.whl'
   .venv/bin/python -m pip install -r llama.cpp/requirements/requirements-convert_hf_to_gguf.txt
   .venv/bin/python -m pip check
   .venv/bin/python -m pip freeze > resolved-conversion-environment.txt
   .venv/bin/python - <<'PYCPU'
   import torch
   assert torch.__version__ == '2.11.0+cpu' and hasattr(torch,'float8_e8m0fnu')
   PYCPU
   ./llama.cpp/build/bin/llama-server --version

   Expected result: Exact source builds, wheel hash passes and CPU version / dependency checks pass, or setup stops. These are reader steps, not author execution results.

Download the model

1. 1. Write the fixed native artifact helper

   Save this exact reader-authored stdlib helper. It accepts safe fixed native filenames and constructs URLs only from the exact Speciale checkpoint pin. Downloads are streamed and capped; every source file must match its hash and size.

   CommandCopy command

   set -e
   cd "$HOME/deepseek-speciale-hosting"
   cat > reader-artifacts.py <<'PYARTIFACT'
   """Reader-authored bounded artifact preparation; no model/native imports."""
   import pathlib,hashlib,json,re,sys,urllib.request,os
   
   def digest(path):
    h=hashlib.sha256()
    with pathlib.Path(path).open('rb')as stream:
     for chunk in iter(lambda:stream.read(8*1024*1024),b''):h.update(chunk)
    return h.hexdigest()
   def validate_entry(e):
    if not isinstance(e,dict)or set(e)!={'name','bytes','sha256'}:raise ValueError('manifest_shape')
    if not isinstance(e['name'],str)or not re.fullmatch(r'[A-Za-z0-9_.-]+',e['name']):raise ValueError('unsafe_filename')
    if type(e['bytes'])is not int or e['bytes']<=0 or not isinstance(e['sha256'],str)or not re.fullmatch('[0-9a-f]{64}',e['sha256']):raise ValueError('invalid_identity')
    prefix='https://huggingface.co/deepseek-ai/DeepSeek-V3.2-Speciale/resolve/c562883eda916fd699a44bbf1f4987a53b96008b/'
    # URLs are constructed from the fixed native pin, never accepted from manifest input.
   def verify(path,e):
    validate_entry(e)
    if path.stat().st_size!=e['bytes']or digest(path)!=e['sha256']:raise ValueError('artifact_identity_mismatch')
   def download(root,manifest,opener=urllib.request.urlopen):
    root=pathlib.Path(root);root.mkdir(exist_ok=True)
    if len({e['name']for e in manifest})!=len(manifest):raise ValueError('duplicate_names')
    for e in manifest:
     validate_entry(e);path=root/e['name']
     if path.exists():verify(path,e);continue
     temp=path.with_name(path.name+'.partial')
     try:
      with opener('https://huggingface.co/deepseek-ai/DeepSeek-V3.2-Speciale/resolve/c562883eda916fd699a44bbf1f4987a53b96008b/'+e['name'],timeout=120)as response,temp.open('wb')as output:
       total=0
       while True:
        block=response.read(8*1024*1024)
        if not block:break
        total+=len(block)
        if total>e['bytes']:raise ValueError('oversized_download')
        output.write(block)
      verify(temp,e);temp.replace(path)
     except Exception:
      temp.unlink(missing_ok=True);raise
     print('Verified '+e['name'],flush=True)
   def prepare(native,dest,manifest):
    native=pathlib.Path(native).resolve();dest=pathlib.Path(dest)
    for e in manifest:verify(native/e['name'],e)
    if dest.exists():raise ValueError('conversion_input_must_be_new')
    index=json.loads((native/'model.safetensors.index.json').read_text())
    if set(index['weight_map'].values())!={e['name']for e in manifest if e['name'].endswith('.safetensors')}:raise ValueError('incomplete_index')
    dest.mkdir()
    for e in manifest:
     if e['name']!='tokenizer_config.json':(dest/e['name']).symlink_to(native/e['name'])
    original=json.loads((native/'tokenizer_config.json').read_text())
    if original.get('add_bos_token')is not False:raise ValueError('unexpected_original_bos_setting')
    changed=dict(original);changed['add_bos_token']=True
    (dest/'tokenizer_config.json').write_text(json.dumps(changed,indent=2)+'\n')
    if {k:v for k,v in changed.items()if k!='add_bos_token'}!={k:v for k,v in original.items()if k!='add_bos_token'}:raise ValueError('unexpected_config_change')
    print('Original native metadata preserved; only conversion-input add_bos_token changed to true.')
   def splits(root,prefix):
    root=pathlib.Path(root);files=sorted(root.glob(prefix+'-*-of-*.gguf'));rows=[];total=None
    for i,path in enumerate(files,1):
     match=re.fullmatch(re.escape(prefix)+r'-(\d{5})-of-(\d{5})\.gguf',path.name)
     if not match or int(match[1])!=i:raise ValueError('split_sequence')
     if total is None:total=int(match[2])
     if int(match[2])!=total or path.stat().st_size<=0:raise ValueError('split_shape')
     rows.append({'name':path.name,'bytes':path.stat().st_size,'sha256':digest(path)})
    if not rows or len(rows)!=total:raise ValueError('incomplete_splits')
    return rows
   if __name__=='__main__':
    action=sys.argv[1]
    if action in ('download','prepare'):
     manifest=json.loads(pathlib.Path('native-download-manifest.json').read_text())
     if action=='download':download('native',manifest)
     else:prepare('native','conversion-input',manifest)
    elif action=='manifest':
     rows=splits(sys.argv[2],sys.argv[3]);pathlib.Path(sys.argv[4]).write_text(json.dumps(rows,indent=2)+'\n');print(rows[0]['name'])
    elif action=='verify':
     root=pathlib.Path(sys.argv[2]);saved=json.loads(pathlib.Path(sys.argv[4]).read_text());actual=splits(root,sys.argv[3])
     if actual!=saved:raise ValueError('reader_output_changed')
     print(str(root/actual[0]['name']))
    else:raise ValueError('unknown_action')
   PYARTIFACT
   echo 'dfbc7919b95b002a2f3a676f22537d864a689a9f9d4042e37d77bcf779f35879  reader-artifacts.py' | sha256sum --check

   Expected result: Exact helper is saved; no model download or execution occurs until the later reader download step.

2. 2. Write exact native manifest part 1

   Save this exact source metadata chunk. All chunks are combined and checked before download; no listed shard is optional.

   CommandCopy command

   set -e
   cd "$HOME/deepseek-speciale-hosting"
   cat > native-manifest-part-1.json <<'MANIFEST'
   [
     {
       "name": "model-00001-of-000163.safetensors",
       "bytes": 5233198531,
       "sha256": "3b45dd46fd8270cce028029c0ba90d22d7cc61a75fae1b62c2c66e154e5c2a92"
     },
     {
       "name": "model-00002-of-000163.safetensors",
       "bytes": 4302383956,
       "sha256": "aba186c3680e6e6fef536be1853c5b6b7687db84af7e331dbbfbe5825b562f57"
     },
     {
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       "bytes": 4302384377,
       "sha256": "0564184ab71017a4cf573ef548b2adc323424e6ae8f7c1f0699c3bf701b8abce"
     },
     {
       "name": "model-00004-of-000163.safetensors",
       "bytes": 4302121967,
       "sha256": "a54bfa7943348cae8a82b307a336375d0753c59de90c58f2acdcaa4e5951727d"
     },
     {
       "name": "model-00005-of-000163.safetensors",
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     },
     {
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     },
     {
       "name": "model-00008-of-000163.safetensors",
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     },
     {
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     },
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     },
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     },
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     },
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       "sha256": "8c22f8339cb47d10d4ea28e25e9d685d7a5d830f3d1fa97982884353a7f7d109"
     },
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       "sha256": "dd8a7cbdf6a3a99205951f0862e379caf80ffa71c912a7efd7fbd23f04009880"
     }
   ]
   MANIFEST
   echo '4261b547757ca9389b190aabed2f40d4ac7c883e7c59a62c691afd3deedeb263  native-manifest-part-1.json' | sha256sum --check

   Expected result: This exact manifest chunk passes its SHA check.

3. 3. Write exact native manifest part 2

   Save this exact source metadata chunk. All chunks are combined and checked before download; no listed shard is optional.

   CommandCopy command

   set -e
   cd "$HOME/deepseek-speciale-hosting"
   cat > native-manifest-part-2.json <<'MANIFEST'
   [
     {
       "name": "model-00031-of-000163.safetensors",
       "bytes": 4302122808,
       "sha256": "dcf4d7f3678b9b8cc1395dd34a9a4e3af182ec00713cb850ea6a180258e7ac01"
     },
     {
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       "sha256": "66afeba2a55df6736b7990054498e28a0adb9f3ca14a3fb6241a5a40844e9a25"
     },
     {
       "name": "model-00050-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "a97f1ff372698faa88c2717265e97e404d51ba5599b74163df6fee19d2b5e186"
     },
     {
       "name": "model-00051-of-000163.safetensors",
       "bytes": 4302122420,
       "sha256": "634e40ba294b1ff0e13c1ad1e3818fa2140c74138779b258d1c19ff17a0e8dde"
     },
     {
       "name": "model-00052-of-000163.safetensors",
       "bytes": 4302384870,
       "sha256": "b4594c999e5bc3c40843282d8e34aac6e4976d36077ffad7037a18ab08e507bd"
     },
     {
       "name": "model-00053-of-000163.safetensors",
       "bytes": 4302122808,
       "sha256": "bcf16d4eba83ff6647f3c301eacdee1587bd1fe4f768c4354e00baa5b4da6dad"
     },
     {
       "name": "model-00054-of-000163.safetensors",
       "bytes": 4302384470,
       "sha256": "04db2549b0761d90eeacccc985b2e057c8fd9b193a43c477ba9944fd10eb8af7"
     },
     {
       "name": "model-00055-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "863441a303a9f06bd67acee1caa22849fdd4acf0a9523a74fb7f4cc2d9864e87"
     },
     {
       "name": "model-00056-of-000163.safetensors",
       "bytes": 1864917414,
       "sha256": "c993b3fb3fde9ac95329b261f1c6391b519c236b162abb3280e2151c7b344531"
     },
     {
       "name": "model-00057-of-000163.safetensors",
       "bytes": 4302061105,
       "sha256": "f18cd8b7b63d1351acfbd3cc07ada6fd85b0fa990c407c6940478a3531c8903a"
     },
     {
       "name": "model-00058-of-000163.safetensors",
       "bytes": 4302384914,
       "sha256": "b5a2cfce49cbe06b43e590f9d4564b133224d22ac6ac10db5e50f7089bd45c67"
     },
     {
       "name": "model-00059-of-000163.safetensors",
       "bytes": 4302122764,
       "sha256": "2feb7533949df0fb668c18df5146e242e5dd3c6939e99a9062f768bef1dfe157"
     },
     {
       "name": "model-00060-of-000163.safetensors",
       "bytes": 4302384516,
       "sha256": "ddf2505aa4f8bbc0215bcafcc68c9cc8040d7a28e571ebe4f5801b2fdbbfbbf0"
     }
   ]
   MANIFEST
   echo '425ae45a19742bf01fc33ae0bb2ce94eff52d7cdd6d5eef7d9c24c0e472174e1  native-manifest-part-2.json' | sha256sum --check

   Expected result: This exact manifest chunk passes its SHA check.

4. 4. Write exact native manifest part 3

   Save this exact source metadata chunk. All chunks are combined and checked before download; no listed shard is optional.

   CommandCopy command

   set -e
   cd "$HOME/deepseek-speciale-hosting"
   cat > native-manifest-part-3.json <<'MANIFEST'
   [
     {
       "name": "model-00061-of-000163.safetensors",
       "bytes": 4302384961,
       "sha256": "45a2f2e4c0655992d052573f48b8355518291e840663fce85965e52bf2ae2623"
     },
     {
       "name": "model-00062-of-000163.safetensors",
       "bytes": 4302122576,
       "sha256": "dced6863869f2182a16eb384dfb1aabb979e63eb485f5f73291d0bd249437495"
     },
     {
       "name": "model-00063-of-000163.safetensors",
       "bytes": 4302384704,
       "sha256": "525bc417483c458f404947ba584019f18ccf235243e9df75f2dd81a178193af8"
     },
     {
       "name": "model-00064-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "d0bee64de778717221d961419b2b042f1eb6bc38e58cee585774dfafb8db87e7"
     },
     {
       "name": "model-00065-of-000163.safetensors",
       "bytes": 4302122398,
       "sha256": "4589fa62e0cf08216d2b9f7cb4649a7bc3c4912df7b8de19787515d36ee8adab"
     },
     {
       "name": "model-00066-of-000163.safetensors",
       "bytes": 4302384890,
       "sha256": "0a74c81756d57de4c083674f49c5276d2c5edf11b9a7dbc87be31023c131ebc9"
     },
     {
       "name": "model-00067-of-000163.safetensors",
       "bytes": 4302122786,
       "sha256": "bfcd9034dedc9f3c009cc4b544ab8e129efc9359622cec9db69f8c3d53473324"
     },
     {
       "name": "model-00068-of-000163.safetensors",
       "bytes": 4302384494,
       "sha256": "5d381484b92ad457ccfda696c6a570e05631ec6a1a5dcee18ea1c64899b8164b"
     },
     {
       "name": "model-00069-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "58434bc6afe5c05d19f01295525a6a0a355a838e72d48de3048423f7af15626e"
     },
     {
       "name": "model-00070-of-000163.safetensors",
       "bytes": 4302122598,
       "sha256": "4f4fc1d62e0f4367326d8a5edd8de3470cec82f3f04974f5e54f8e7ce98450a8"
     },
     {
       "name": "model-00071-of-000163.safetensors",
       "bytes": 4302384680,
       "sha256": "ab19d958c521718a6d35232dd0d4dcc996d6105de6237c7bbeee0268a2a9bd41"
     },
     {
       "name": "model-00072-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "bd3c245cfab46212e2a2c6c1e9c33fd2a3ae4b8cc876ed0f400e16ea65b2de30"
     },
     {
       "name": "model-00073-of-000163.safetensors",
       "bytes": 4302122420,
       "sha256": "9e53968bfcab515a5b93a89d4afa635e85150a7f5ccaa87faa05183e9540fc07"
     },
     {
       "name": "model-00074-of-000163.safetensors",
       "bytes": 4302384870,
       "sha256": "0c9d63b66cb21e72d732c81ff36e8583bb0943468ba38735012f356ee4525df5"
     },
     {
       "name": "model-00075-of-000163.safetensors",
       "bytes": 4302122808,
       "sha256": "79e1c07ef8d2d1861fe9fde95751b53b9c81eda6a76d13948dfb8520f225d0c8"
     },
     {
       "name": "model-00076-of-000163.safetensors",
       "bytes": 4302384470,
       "sha256": "8de0b608082953689c130df6494c6180b676dcb7f7e64119c91ce9cfd47d5edf"
     },
     {
       "name": "model-00077-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "ce8e4069167d26c2c809ee6a5613f3e9be50982704455bde04273ba87bdd0390"
     },
     {
       "name": "model-00078-of-000163.safetensors",
       "bytes": 1864917414,
       "sha256": "3ac5a8a9404fe6f6a829fdf49087be25571090f7afc0d3ad142562497af4a9e0"
     },
     {
       "name": "model-00079-of-000163.safetensors",
       "bytes": 4302061105,
       "sha256": "7bd35ade9310684161536787e07474dd676b340986787f22708512a4a17828b1"
     },
     {
       "name": "model-00080-of-000163.safetensors",
       "bytes": 4302384914,
       "sha256": "4d00329410e711200d04d1cc3fed93e5ca9f5159598a29f8bfdd06cda01320ff"
     },
     {
       "name": "model-00081-of-000163.safetensors",
       "bytes": 4302122764,
       "sha256": "c7d1a0207848e81ea4465fe11f07621929305f2cb35a8d75ffb560beab8dd242"
     },
     {
       "name": "model-00082-of-000163.safetensors",
       "bytes": 4302384516,
       "sha256": "dc219cc84fb914ae12617fbc0f9b032ffefb5f76314e0e116637acc6fa9b9a95"
     },
     {
       "name": "model-00083-of-000163.safetensors",
       "bytes": 4302384961,
       "sha256": "4c0bb64431002edf1937c85dbddf579848e75c161791888db4daed10f5af4035"
     },
     {
       "name": "model-00084-of-000163.safetensors",
       "bytes": 4302122576,
       "sha256": "90183af42f0b025543c48d97608d03d8da16a5050b0097499c46fb2c356b1feb"
     },
     {
       "name": "model-00085-of-000163.safetensors",
       "bytes": 4302384704,
       "sha256": "aae4b6e751c2ed573cb2299f39ffe433618955039d0b52246fec7c0ecf3fa7d5"
     },
     {
       "name": "model-00086-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "56507428ba95e2e65aa2d92a02c4346e410b7d3d5079a634e9b6fcad808416f0"
     },
     {
       "name": "model-00087-of-000163.safetensors",
       "bytes": 4302122398,
       "sha256": "03abbca18e83996ba89b9cb64e28e745a54a8d3d4657d4dece995e46081fc353"
     },
     {
       "name": "model-00088-of-000163.safetensors",
       "bytes": 4302384890,
       "sha256": "beafd017117dfc722603a3de2fc4eb3fe38c97564ac505eac7fe146e16888d1c"
     },
     {
       "name": "model-00089-of-000163.safetensors",
       "bytes": 4302122786,
       "sha256": "8ae385ce053c9dedb5bcb164d80c2b6db93bfa91a268865d4c1b0d569a3c9467"
     },
     {
       "name": "model-00090-of-000163.safetensors",
       "bytes": 4302384494,
       "sha256": "37e67cd92190f4357879a3803c9e67502cd68904626a520221eb26e3ddaee4dd"
     }
   ]
   MANIFEST
   echo 'cb904b287e9f63eb68cb0d860a93756877f6bde2f1f0b10fb4bb641b892036c1  native-manifest-part-3.json' | sha256sum --check

   Expected result: This exact manifest chunk passes its SHA check.

5. 5. Write exact native manifest part 4

   Save this exact source metadata chunk. All chunks are combined and checked before download; no listed shard is optional.

   CommandCopy command

   set -e
   cd "$HOME/deepseek-speciale-hosting"
   cat > native-manifest-part-4.json <<'MANIFEST'
   [
     {
       "name": "model-00091-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "f01ce1c13a22636f48a4ac34f6ada537651572aa3e03be6a9a31fdca80a691f1"
     },
     {
       "name": "model-00092-of-000163.safetensors",
       "bytes": 4302122598,
       "sha256": "64d70b2f7643ee6d39c308d658d2a70c78af88ee83ae9f5ffe920da06384925f"
     },
     {
       "name": "model-00093-of-000163.safetensors",
       "bytes": 4302384680,
       "sha256": "bee293eb77e9261a07a1bec0563128b66fc615cce22804a79139bd4668da6c86"
     },
     {
       "name": "model-00094-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "17469ee58950c4b2dfffcccd1c17729969adcf3c1c1f1f43dd5e3b87541d6b64"
     },
     {
       "name": "model-00095-of-000163.safetensors",
       "bytes": 4302122420,
       "sha256": "d539783d8e5278cb57611edd108a3bfba426e360053b881170ae065b4822a990"
     },
     {
       "name": "model-00096-of-000163.safetensors",
       "bytes": 4302384870,
       "sha256": "596ef0684ba973813479949c39419b7214a07ff91787fa4f14b311c5fa5ebe1b"
     },
     {
       "name": "model-00097-of-000163.safetensors",
       "bytes": 4302122808,
       "sha256": "18b6fd1c57697dbf01e1c57adb0f80a0eb5838733600a10cc7f2b359bb5d7cb3"
     },
     {
       "name": "model-00098-of-000163.safetensors",
       "bytes": 4302384470,
       "sha256": "232bb1be729623b1a9d411e0dbd2899ddeddc6a361f54a0018b29eddb1a5383d"
     },
     {
       "name": "model-00099-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "29e9ec2944e09bc653e0a02cf2272f4a78c8c5355afb8315fc7773c3a8383d6e"
     },
     {
       "name": "model-00100-of-000163.safetensors",
       "bytes": 1864917414,
       "sha256": "51786f6acee394c24bc5851258887b51d26dfd628c9e2c888cd79f1be08d5f76"
     },
     {
       "name": "model-00101-of-000163.safetensors",
       "bytes": 4302061105,
       "sha256": "654b15641395876e4797f6f7587ccd815617dccd6a5612712a6aed2881aea4bc"
     },
     {
       "name": "model-00102-of-000163.safetensors",
       "bytes": 4302384914,
       "sha256": "91a03a21acc0326ff3f7719b799f2f7244a45fa08f74eafec0eddaa487d1378e"
     },
     {
       "name": "model-00103-of-000163.safetensors",
       "bytes": 4302122764,
       "sha256": "aaef65b416a8d96e6094b285739aa7675e6bbf9f8c6930f4232a00ba1bb030ae"
     },
     {
       "name": "model-00104-of-000163.safetensors",
       "bytes": 4302384516,
       "sha256": "e5d2f240b68fb46ab8ae29a9a95831a00c529bc8f51b8e20829b5700319c1ee5"
     },
     {
       "name": "model-00105-of-000163.safetensors",
       "bytes": 4302384961,
       "sha256": "da2ef8d5f33aaa517a89d6f908eed4a0722c8e836d221b72bf120da2a8f7bd1b"
     },
     {
       "name": "model-00106-of-000163.safetensors",
       "bytes": 4302122576,
       "sha256": "03621b54b89ede8ff214f5f14f5711f6168ab5f6f58681ee478fd71f30cb01d0"
     },
     {
       "name": "model-00107-of-000163.safetensors",
       "bytes": 4302384704,
       "sha256": "a3c9c62afd4e1609738856a3a68161067db218d3ff297033bf26d71218a8e54c"
     },
     {
       "name": "model-00108-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "eecb5e8394ad76b9f2aae5f4a5b0e30f20a92105e61c056cc8f98cc99fee1a92"
     },
     {
       "name": "model-00109-of-000163.safetensors",
       "bytes": 4302122398,
       "sha256": "096c4aeff0c34a1d600d1be5ee19171663a80a4dd7b690307c52776551bd1297"
     },
     {
       "name": "model-00110-of-000163.safetensors",
       "bytes": 4302384890,
       "sha256": "8182c7059f15f92407caa60cfd9c478cbd37ff49c097efaa28ecb86606e6dfdc"
     },
     {
       "name": "model-00111-of-000163.safetensors",
       "bytes": 4302122786,
       "sha256": "89b431c62abccaf8fc22437ef0fbd6f71cfb1a4b3fb01855a780cdf67c986ec9"
     },
     {
       "name": "model-00112-of-000163.safetensors",
       "bytes": 4302384494,
       "sha256": "d385889177b8c5d4d46cf02c0c57a10258d7b52369d207f87c72c7527a149e1f"
     },
     {
       "name": "model-00113-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "3dc999e44b63fe1c2c636ee217f2d83ad20a66aa8d3030ddbcfb9b4c157e9576"
     },
     {
       "name": "model-00114-of-000163.safetensors",
       "bytes": 4302122598,
       "sha256": "19495eea649f4eaf67de619224ccd5ef729983c68b0e8db6b60124933d5ce9eb"
     },
     {
       "name": "model-00115-of-000163.safetensors",
       "bytes": 4302384680,
       "sha256": "873bb28d7073048868a50a4587c506b4b75e07c93b43280ecb49038a070f8876"
     },
     {
       "name": "model-00116-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "ebb5b18a3d2c10f6733f90f02150d555d28e4126d9a9812fd2bd46c9b3220fd6"
     },
     {
       "name": "model-00117-of-000163.safetensors",
       "bytes": 4302122420,
       "sha256": "966fe1a15883edc44d4aeccf88eff5dd588aca792a401b5a6205707ab898a1a4"
     },
     {
       "name": "model-00118-of-000163.safetensors",
       "bytes": 4302384870,
       "sha256": "c8ef897e1dec39e212662d306a96dc5fa6f89b647c4b5cf289296618c74f2be7"
     },
     {
       "name": "model-00119-of-000163.safetensors",
       "bytes": 4302122808,
       "sha256": "e9431a5ba2dc20e7ff6a3d5c48e010dccb376d303c9a499b40f586e20812c395"
     },
     {
       "name": "model-00120-of-000163.safetensors",
       "bytes": 4302384470,
       "sha256": "6c72caab19c214eda985680d9ae62acac2922753f95a3e5440bc94ef56425b62"
     }
   ]
   MANIFEST
   echo 'a2c0741cdfc74188ea15a5d60b6012f259cda565ba72b7501d84947e4c53ecf5  native-manifest-part-4.json' | sha256sum --check

   Expected result: This exact manifest chunk passes its SHA check.

6. 6. Write exact native manifest part 5

   Save this exact source metadata chunk. All chunks are combined and checked before download; no listed shard is optional.

   CommandCopy command

   set -e
   cd "$HOME/deepseek-speciale-hosting"
   cat > native-manifest-part-5.json <<'MANIFEST'
   [
     {
       "name": "model-00121-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "caccd7c38c7595f75625e504f122156205609d5def97c5836e13608ba6e33862"
     },
     {
       "name": "model-00122-of-000163.safetensors",
       "bytes": 1864917414,
       "sha256": "321bbcbef0c710d66836681108269c49945665c78c744d9a15d9052add146ab3"
     },
     {
       "name": "model-00123-of-000163.safetensors",
       "bytes": 4302061105,
       "sha256": "9e0976ae801be4f6af51614b44e49f278c89ba724e46b90ad40ea023e82b854e"
     },
     {
       "name": "model-00124-of-000163.safetensors",
       "bytes": 4302384914,
       "sha256": "8c47c2d1309b68c57acbd6b3d2f12a6bde930f55de5f93b92122b391b0330b8d"
     },
     {
       "name": "model-00125-of-000163.safetensors",
       "bytes": 4302122764,
       "sha256": "50a7faeb6ce937184f318af85a3dc7aee61b5d39b93373ee16370cdd019254b4"
     },
     {
       "name": "model-00126-of-000163.safetensors",
       "bytes": 4302384516,
       "sha256": "584383202cec81c52c9e9454491d08f7ae0215bb5cf0d38fbe6585c5656d5253"
     },
     {
       "name": "model-00127-of-000163.safetensors",
       "bytes": 4302384961,
       "sha256": "efdb6f8ba904e252bdf8112439612059ca90cbebd4e6f4e35d32f00025f74048"
     },
     {
       "name": "model-00128-of-000163.safetensors",
       "bytes": 4302122576,
       "sha256": "ad872a598894e0706ae5749bb5545c00e9c03864c877ac7685edbb5f351886ba"
     },
     {
       "name": "model-00129-of-000163.safetensors",
       "bytes": 4302384704,
       "sha256": "febe4ee4154afd505a170367d152d4375df4482e8d632785ce5059656b2e4b43"
     },
     {
       "name": "model-00130-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "438ca4d1e799e1d61281a3c10dab0fb0682b2797f609e1ef543552e2da9e5f87"
     },
     {
       "name": "model-00131-of-000163.safetensors",
       "bytes": 4302122398,
       "sha256": "976877bcef9a45f6874cfce0e5106523bb2cd21fbe2b61e5fbf1d64619c73f3c"
     },
     {
       "name": "model-00132-of-000163.safetensors",
       "bytes": 4302384890,
       "sha256": "6913d5c42023d3cf26e0cee83836eabd604b8185b1815f9ceff87935ca09a78f"
     },
     {
       "name": "model-00133-of-000163.safetensors",
       "bytes": 4302122786,
       "sha256": "0b2f6f918109f4b1ce89c784d71410ba527fa529fc82b38fe66c1823d12ad815"
     },
     {
       "name": "model-00134-of-000163.safetensors",
       "bytes": 4302384494,
       "sha256": "b89357ea72f4d19d7fdb0bb571d4f9fae9145e3aaaed984a8f9f91a25c828ca0"
     },
     {
       "name": "model-00135-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "e06ab711e960be0a6018b1bfd4dbf5da883f57f2932f47b07a07a5fc6564f80c"
     },
     {
       "name": "model-00136-of-000163.safetensors",
       "bytes": 4302122598,
       "sha256": "f844c3004bb622600c8e4d7778c3112c17409163f2be19f64e9389459030df27"
     },
     {
       "name": "model-00137-of-000163.safetensors",
       "bytes": 4302384680,
       "sha256": "9f24493f3d67e3715bb401a66454846debdbd1f4615c247e384af9d4170219bc"
     },
     {
       "name": "model-00138-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "6c4293949318bea4aea34e77d4b8f5c24c81e4c8846dda6387299e032242b017"
     },
     {
       "name": "model-00139-of-000163.safetensors",
       "bytes": 4302122420,
       "sha256": "18ce46aa84a4993744c7a78024f3fe3074dce564ed516702adf898a144e3bf4b"
     },
     {
       "name": "model-00140-of-000163.safetensors",
       "bytes": 4302384870,
       "sha256": "adc2970ddae9b725901595eaae34fab6dcb94203fa3b8323e22b03dd14c7f6b7"
     },
     {
       "name": "model-00141-of-000163.safetensors",
       "bytes": 3245204828,
       "sha256": "36ffb84d6fa304372583182cec1fef00294daa5ce087ebf0ad22ded25a19e687"
     },
     {
       "name": "model-00142-of-000163.safetensors",
       "bytes": 4302061105,
       "sha256": "8a564710c22c6ce19b835e0632337369f9e9be4ed33c7c30a4d7ca45e7859616"
     },
     {
       "name": "model-00143-of-000163.safetensors",
       "bytes": 4302384914,
       "sha256": "84ce3f89ecb97c1d7ea227752c56c25c085bdc843c53f250d651833370455944"
     },
     {
       "name": "model-00144-of-000163.safetensors",
       "bytes": 4302122764,
       "sha256": "e4889ff54ac74758f6cdb95ef9c1798d10f2fd3b06e89f9d14b7e86f6ed8efdd"
     },
     {
       "name": "model-00145-of-000163.safetensors",
       "bytes": 4302384516,
       "sha256": "cd7ce1397dfd7a10085003b50f0ebbb541c9009832eb0498834b703875f68b7c"
     },
     {
       "name": "model-00146-of-000163.safetensors",
       "bytes": 4302384961,
       "sha256": "eb8473c1361858cc88689bbfde0d80e87dd4884786a712adc778886cb435d682"
     },
     {
       "name": "model-00147-of-000163.safetensors",
       "bytes": 4302122576,
       "sha256": "5710defd19fd0123913f4c0f3d10195538442b21ea5c228e44160a5073265d37"
     },
     {
       "name": "model-00148-of-000163.safetensors",
       "bytes": 4302384704,
       "sha256": "aa72c2da95c14896d8d11bdf22cdb469e85070e9be631de62aba2baa1d4c0c13"
     },
     {
       "name": "model-00149-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "c5acbb3c161819aab88f67aaf166638519590dc2f87f469d19ce6f98bbf8a0b8"
     },
     {
       "name": "model-00150-of-000163.safetensors",
       "bytes": 4302122398,
       "sha256": "cc53b2c7aee78c9735fb2ddca616c4ff7519ca358d1acfca4a4e90cfab3554de"
     }
   ]
   MANIFEST
   echo 'e4a30c312451f069575e68e7061541cd5d3497d700647c2892804c7ac7f3291f  native-manifest-part-5.json' | sha256sum --check

   Expected result: This exact manifest chunk passes its SHA check.

7. 7. Write exact native manifest part 6

   Save this exact source metadata chunk. All chunks are combined and checked before download; no listed shard is optional.

   CommandCopy command

   set -e
   cd "$HOME/deepseek-speciale-hosting"
   cat > native-manifest-part-6.json <<'MANIFEST'
   [
     {
       "name": "model-00151-of-000163.safetensors",
       "bytes": 4302384890,
       "sha256": "1def32f991993ffa0f80782d69d237bb9e69a1a82575e56f34f732101cea1301"
     },
     {
       "name": "model-00152-of-000163.safetensors",
       "bytes": 4302122786,
       "sha256": "b6630cad76fa28a9fb8e8aebd296cdbf4164096867177539bf28e6486a1d21f1"
     },
     {
       "name": "model-00153-of-000163.safetensors",
       "bytes": 4302384494,
       "sha256": "6326a6fc6bdaba357c2316e7b9ed65ab4538f1b010492b11b67cf05f720f4014"
     },
     {
       "name": "model-00154-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "171e7f22d6416a2231604a1ad8dfa00bd76d3308b530327b75e962169e0d6ff5"
     },
     {
       "name": "model-00155-of-000163.safetensors",
       "bytes": 4302122598,
       "sha256": "e938795a24925cf367c8f08b083f73744ba714ef0f2424b000a59b528128e1e6"
     },
     {
       "name": "model-00156-of-000163.safetensors",
       "bytes": 4302384680,
       "sha256": "567ddad661d9ecaf04f5dc6a0943a801d87f8a78da2ad93120e9cdfab38c8aba"
     },
     {
       "name": "model-00157-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "bcebfeeb9244c117932ff424810ae745d5c68b70afffb6947007369c9c349a9f"
     },
     {
       "name": "model-00158-of-000163.safetensors",
       "bytes": 4302122420,
       "sha256": "9315ac9c3150edb096436190df544c98581238be04e207ebceea2c47dcad0403"
     },
     {
       "name": "model-00159-of-000163.safetensors",
       "bytes": 4302384870,
       "sha256": "a8c137bef6e4141ef3d51273173f25f700a33836ea253b5adb4112003142f4e8"
     },
     {
       "name": "model-00160-of-000163.safetensors",
       "bytes": 5285723731,
       "sha256": "6af9415a2e19b971073a8741170d104159d493f37fa52f9758254c82bebc391d"
     },
     {
       "name": "model-00161-of-000163.safetensors",
       "bytes": 4305819875,
       "sha256": "4c3a9de3f0f2919f71de2b84155812f1770ac5156e79656da22f7e0016c41e2e"
     },
     {
       "name": "model-00162-of-000163.safetensors",
       "bytes": 4302384938,
       "sha256": "c02a368f4188f3ec43484c98cbf29f5d99b42be4f45b3b6bcbdda56e8bc187b1"
     },
     {
       "name": "model-00163-of-000163.safetensors",
       "bytes": 6643591758,
       "sha256": "b8f64009d3dc3aa35c6d891a27232e45dd6cee755d22cf8a13ff9c8dc6591251"
     },
     {
       "name": "config.json",
       "bytes": 1552,
       "sha256": "c7fa8b191e9936d8e6a57d864baab82b792fae16a116416cdd3a75ba76bc5af1"
     },
     {
       "name": "tokenizer_config.json",
       "bytes": 795,
       "sha256": "b5de6cc1c6758d02c0d3cec0efa062f1161654475458003f6f293f6ef28acdaa"
     },
     {
       "name": "tokenizer.json",
       "bytes": 7847502,
       "sha256": "cd050be35cae877f8f0aa847f45aa87e23835a56ca32b29b28545597852784e5"
     },
     {
       "name": "model.safetensors.index.json",
       "bytes": 8938926,
       "sha256": "2a150b2af4aba7b037edc9fdba70f3b41abf758ee926279e7701d954298f9884"
     },
     {
       "name": "generation_config.json",
       "bytes": 171,
       "sha256": "c9ce7f8d4a66c6cedd053650db3596328f241f00a7e49e67b89e5c9e336e7205"
     },
     {
       "name": "LICENSE",
       "bytes": 1084,
       "sha256": "f2c6c602815669d292889e5be8c802f2ed950653b77999b1584e8e6aed25d040"
     }
   ]
   MANIFEST
   echo 'd27ad12ddd7d6b663ef0407fc81d8c6766bfa9aea30d08b4731aa87903887f17  native-manifest-part-6.json' | sha256sum --check

   Expected result: This exact manifest chunk passes its SHA check.

8. 8. Assemble and verify the full native checkpoint

   Combine all six metadata chunks, verify the exact 169-entry manifest and download all 163 native weights plus six metadata/license files. Preserve every original file. The native Python encoder is separately fetched and checked.

   CommandCopy command

   set -e
   cd "$HOME/deepseek-speciale-hosting"
   python3.12 - <<'PYMANIFEST'
   import pathlib,json,hashlib
   rows=[]
   for i in range(1,7):rows+=json.loads(pathlib.Path('native-manifest-part-'+str(i)+'.json').read_text())
   b=(json.dumps(rows,indent=2)+'\n').encode()
   assert len(rows)==169 and hashlib.sha256(b).hexdigest()=='f5614b81179c4d80badd132c3d22e2b9a4acbc68ccd86f180d3b4c13abbdd0ff'
   pathlib.Path('native-download-manifest.json').write_bytes(b)
   PYMANIFEST
   python3.12 reader-artifacts.py download
   curl --fail --location 'https://huggingface.co/deepseek-ai/DeepSeek-V3.2-Speciale/resolve/c562883eda916fd699a44bbf1f4987a53b96008b/encoding/encoding_dsv32.py' -o encoding_dsv32.py
   echo '5e068c2ba2a6e5ebe37a49bb005650c507e7935d77a32f3f7c11ee071498b370  encoding_dsv32.py' | sha256sum --check

   Expected result: All native inputs and encoder verify; any size/hash/access/missing-part failure stops.

Configure

1. 1. Convert complete native FP8 inputs and quantize all output splits

   Prepare a separate conversion-only metadata copy; source weights/config/tokenizer remain unchanged. Default lazy conversion dequantizes FP8 block scales and writes full F16 splits; no eager/no-mtp/pruning flag is used. Quantize with native keep-split support and record actual generated SHA/bytes for both sets. Unknown split counts and final bytes are discovered, never fabricated. Do not delete F16/native inputs to hide a failed or partial conversion.

   CommandCopy command

   set -e
   cd "$HOME/deepseek-speciale-hosting"
   python3.12 reader-artifacts.py prepare
   mkdir -p models/f16 models/q4
   .venv/bin/python llama.cpp/convert_hf_to_gguf.py conversion-input --outfile models/f16/Speciale-F16.gguf --outtype f16 --split-max-size 40G
   python3.12 reader-artifacts.py manifest models/f16 Speciale-F16 f16-output-manifest.json
   FIRST_F16="$(python3.12 reader-artifacts.py verify models/f16 Speciale-F16 f16-output-manifest.json)"
   ./llama.cpp/build/bin/llama-quantize --keep-split "$FIRST_F16" models/q4/Speciale-Q4_K_M Q4_K_M 16
   python3.12 reader-artifacts.py manifest models/q4 Speciale-Q4_K_M q4-output-manifest.json
   python3.12 reader-artifacts.py verify models/q4 Speciale-Q4_K_M q4-output-manifest.json
   umask 077
   if [ ! -e .api-key ]; then openssl rand -hex 32 > .api-key; fi
   test -s .api-key
   chmod 600 .api-key

   Expected result: Complete lazy conversion and quantization finish; all F16/Q4 splits form exact complete numbered sets and generated hashes/sizes are recorded. Existing service key is preserved. No successful conversion/fit is preclaimed.

2. 2. Write the thinking-only native diagnostic

   Save the exact original bounded stdlib client. The reader later loads the verified native encoder, uses thinking mode for both turns, rejects malformed/unfinished responses, and requires true EOS before official parsing. No ordinary chat, tools or external actions are substituted.

   CommandCopy command

   set -e
   cd "$HOME/deepseek-speciale-hosting"
   cat > reasoning-client.py <<'PYCLIENT'
   """Private native DeepSeek V3.2 Speciale thinking-only diagnostic; stdlib only."""
   import hashlib, importlib.util, json, pathlib, urllib.request, urllib.error
   BASE='http://127.0.0.1:8080'
   CONTEXT, OUTPUT = 16384, 8192
   ENCODER_SHA='5e068c2ba2a6e5ebe37a49bb005650c507e7935d77a32f3f7c11ee071498b370'
   BOS='<｜begin▁of▁sentence｜>'
   EOS='<｜end▁of▁sentence｜>'
   
   def positive(v): return type(v) is int and v>0
   
   def checked_messages(messages):
       if not isinstance(messages,list) or not 1<=len(messages)<=12: raise ValueError('Bounded conversation required')
       for i,m in enumerate(messages):
           if not isinstance(m,dict) or set(m)-{'role','content'}: raise ValueError('Only ordinary text conversation is accepted by this diagnostic')
           role,text=m.get('role'),m.get('content')
           if role not in ('system','user','assistant') or (role=='system' and i!=0): raise ValueError('Invalid role order')
           if not isinstance(text,str) or not text.strip() or len(text.encode())>12000: raise ValueError('Invalid text')
           if any(t in text for t in (BOS,EOS,'<｜User｜>','<｜Assistant｜>','<think>','</think>','｜DSML｜')): raise ValueError('Reserved native control marker in user content')
       roles=[m['role'] for m in messages if m['role']!='system']
       if not roles or roles!=['user' if i%2==0 else 'assistant' for i in range(len(roles))] or roles[-1]!='user': raise ValueError('Alternating user/assistant history ending in user required')
       return messages
   
   def complete(call,encode,parse,messages,mode):
       if mode != 'thinking': raise ValueError('Invalid native mode')
       checked_messages(messages)
       prompt=encode(messages,thinking_mode=mode,drop_thinking=True,add_default_bos_token=True)
       if not isinstance(prompt,str) or not prompt.startswith(BOS) or prompt.count(BOS)!=1: raise ValueError('Exactly one native BOS required')
       expected='<think>' if mode=='thinking' else '</think>'
       if not prompt.endswith(expected): raise ValueError('Native mode prefix mismatch')
       ids=call('/tokenize',{'content':prompt,'add_special':False,'parse_special':True}).get('tokens')
       if not isinstance(ids,list) or not ids or any(type(x)is not int or x<0 for x in ids) or ids[0]!=0 or ids.count(0)!=1: raise ValueError('Invalid token IDs or duplicate BOS')
       if len(ids)+OUTPUT>CONTEXT: raise ValueError('Input plus complete reasoning/output reserve exceeds context')
       body={'prompt':ids,'n_predict':OUTPUT,'temperature':1.0,'top_p':0.95,'top_k':0,'min_p':0,'repeat_penalty':1,'stream':False,'cache_prompt':False,'return_tokens':True,'stop':[]}
       result=call('/completion',body)
       if result.get('stop_type')!='eos' or result.get('truncated') is not False: raise ValueError('Require actual native EOS without truncation; limit/word stop does not prove completion')
       n=result.get('tokens_predicted')
       if not positive(n) or n>OUTPUT or result.get('tokens_evaluated')!=len(ids): raise ValueError('Usage mismatch')
       text=result.get('content')
       if not isinstance(text,str) or not text.strip(): raise ValueError('Empty completion')
       # Native server normally omits the EOS text. Reconstitute it only after actual EOS proof.
       if EOS in text and not text.endswith(EOS): raise ValueError('Unexpected internal EOS')
       serialized=text if text.endswith(EOS) else text+EOS
       parsed=parse(serialized,thinking_mode=mode)
       if not isinstance(parsed,dict) or parsed.get('tool_calls') or not isinstance(parsed.get('content'),str) or not parsed['content'].strip(): raise ValueError('Nonempty final text with no tools required')
       if mode=='thinking' and (not isinstance(parsed.get('reasoning_content'),str) or not parsed['reasoning_content'].strip() or '</think>' not in text): raise ValueError('Unclosed or empty native reasoning')
       return {'mode':mode,'inputTokens':len(ids),'outputCap':OUTPUT,'parsed':parsed,'nativeResponse':result}
   
   def http_call(key):
       def call(path,body=None):
           data=None if body is None else json.dumps(body).encode()
           req=urllib.request.Request(BASE+path,data=data,headers={'Authorization':'Bearer '+key,'Content-Type':'application/json'})
           with urllib.request.urlopen(req,timeout=7200) as r:
               if r.status!=200: raise ValueError('HTTP failure')
               raw=r.read(2000001)
           if len(raw)>2000000: raise ValueError('Response limit')
           obj=json.loads(raw)
           if not isinstance(obj,dict): raise ValueError('JSON object required')
           return obj
       return call
   
   def main():
       key=pathlib.Path('.api-key').read_text().strip()
       if len(key)!=64 or any(c not in '0123456789abcdef' for c in key): raise ValueError('Restore private service key')
       path=pathlib.Path('encoding_dsv32.py')
       if hashlib.sha256(path.read_bytes()).hexdigest()!=ENCODER_SHA: raise ValueError('Native encoder checksum mismatch')
       spec=importlib.util.spec_from_file_location('pinned_native_encoding',path)
       native=importlib.util.module_from_spec(spec);spec.loader.exec_module(native)
       call=http_call(key);call('/health')
       req=urllib.request.Request(BASE+'/completion',data=b'{}',headers={'Content-Type':'application/json'})
       try:
           with urllib.request.urlopen(req,timeout=30): raise ValueError('Unauthorized completion accepted')
       except urllib.error.HTTPError as e:
           if e.code!=401: raise
       history=[{'role':'user','content':'The community library is open weekdays 9am to 6pm, Saturday 10am to 4pm and closed Sunday. Using only this schedule, calculate total opening hours in a normal Monday-through-Sunday week. Explain your arithmetic briefly.'}]
       first=complete(call,native.encode_messages,native.parse_message_from_completion_text,history,'thinking')
       pathlib.Path('first-thinking-response.json').write_text(json.dumps(first,indent=2)+'\n')
       history += [{'role':'assistant','content':first['parsed']['content']},{'role':'user','content':'Using the same supplied schedule, how many hours is the library open on Saturday, and is it open on Sunday? Explain briefly.'}]
       second=complete(call,native.encode_messages,native.parse_message_from_completion_text,history,'thinking')
       pathlib.Path('followup-thinking-response.json').write_text(json.dumps(second,indent=2)+'\n')
       print(json.dumps({'firstThinking':first,'followupThinking':second},ensure_ascii=False))
       print('Manually require 5 times 9 plus 6 equals 51 weekly hours, Saturday six hours and Sunday closed; inspect the reasoning against the supplied schedule. Native EOS/closed thinking proves completion shape, not answer quality or speed.')
   if __name__=='__main__': main()
   PYCLIENT
   echo 'd52fafa538936b01ac9f96ff1c8c11e443861e1c82e14b8292f46264d5f6001d  reasoning-client.py' | sha256sum --check

   Expected result: The hash-verified client is saved without generation.

Start the model

1. 1. Start the complete reader-converted Speciale CPU model

   Reverify the complete reader-output manifest on every start. The first split loads the full set; native DSA and all experts remain. NextN weights remain in the complete artifact but no speculative draft is configured. F16 cache flags and disabled flash-attention fusion do not disable DSA. One 16,384-position sequence reserves up to 8,192 generated reasoning/final tokens.

   CommandCopy command

   set -e
   cd "$HOME/deepseek-speciale-hosting"
   FIRST_Q4="$(python3.12 reader-artifacts.py verify models/q4 Speciale-Q4_K_M q4-output-manifest.json)"
   ./llama.cpp/build/bin/llama-server -m "$FIRST_Q4" --alias deepseek-v32-speciale --host 127.0.0.1 --port 8080 --api-key-file .api-key --device none -ngl 0 -t 16 -c 16384 -np 1 -n 8192 --no-context-shift --flash-attn off --cache-type-k f16 --cache-type-v f16 -b 256 -ub 256 --special --temp 1.0 --top-p 0.95 --top-k 0 --min-p 0 --repeat-penalty 1

   Expected result: The complete reader-generated DEEPSEEK32 model initializes or a clear tensor/split/cache/allocation error stops setup. Actual startup, memory fit and speed are unknown.

Verify the setup

1. 1. Check authentication, reasoning, history, budget and native EOS

   Run in a second terminal inside this host. Count the complete native thinking prompt before generation and reserve all 8,192 output tokens. Both turns must reach true EOS without truncation, close nonempty native reasoning and provide a nonempty final answer. Manually inspect five weekdays times nine hours plus Saturday six equals 51 weekly hours, Saturday six and Sunday closed. Correct protocol shape is not reasoning quality.

   CommandCopy command

   set -e
   cd "$HOME/deepseek-speciale-hosting"
   python3.12 reasoning-client.py

   Expected result: Private protected route rejects unauthenticated access; both thinking responses complete with consistent positive usage and native parser acceptance. Incorrect arithmetic/facts, missing closure, length/word stop or malformed output fails.

Performance evidence

No compatible measurement available. Documented support and estimated memory do not establish response speed.

Limits and troubleshooting

• Complete source-qualified reader conversion only; no author weights/model imports/native encoder execution, dependency install/build/conversion/inference/fit/speed/quality result.
• Exact native Speciale is exclusively a deep-reasoning checkpoint and explicitly lacks tool calling. Both initial and follow-up requests use native thinking mode; no ordinary V3.2 chat, Exp, distillation, tools or no-light architecture is substituted.
• All 163 source files and exact metadata are required. Native serialized bytes total 689,483,049,129; index metadata total_size 1,370,793,842,752 is distinct. Final F16/Q4 GGUF bytes, hashes and split counts are reader-generated unknowns until actual conversion.
• Native converter default preserves full main DSA and appended NextN tensors. No --no-mtp, tensor removal, prune or alternate DeepseekV3 architecture is passed. Speculative MTP serving is not configured.
• The converter explicitly requires add_bos_token true. Only a separate conversion-input tokenizer metadata copy changes that key; originals remain hash-verified. Native Python encoding supplies one BOS and raw tokenizer add_special false at serving. No Jinja substitute is installed.
• 4 TiB working disk covers planning space for native inputs, F16 intermediate, unknown Q4 final and environment/build/scratch. 512 GiB RAM, lazy materialization and bounded token batches do not establish actual conversion or serving fit. Do not reclaim required inputs mid-failure to force a partial model.
• Native config has 163,840 positions and tokenizer declares 131,072. This guide deliberately uses 16,384 combined positions with 8,192 for reasoning and final text on a short arithmetic fixture. It is not a full-depth reasoning recommendation or long-context claim; truncation fails.
• Official CPU Torch wheel, exact runtime requirements and source are pinned; some transitive Python/system packages resolve during reader setup. Record actual versions/logs and stop on pip check, float8/conversion/runtime errors rather than claiming executed compatibility.
• MIT covers the exact native model and repository. Retain required notices in copies/substantial portions; conversion is a reader modification with no publisher accuracy certification.
• Full native GPU/distributed precision, tool-free longer reasoning tasks, other quantizations and speculative MTP remain open scopes. Required total guide jobs remains null; unknown memory, latency and task cost are not replaced by active-parameter math.

Conversion, unknown tensor, FP8 scale or resource failure

Stop and retain complete logs. Verify exact source/runtime/CPU wheel, all source hashes and derived tokenizer metadata. Do not remove DSA/NextN, change architecture, substitute an old derivative or bypass failed checks. Requalify a changed allocation/runtime separately.

Split sequence or generated-output hash mismatch

Do not serve. Preserve native/F16/output evidence and inspect failed conversion. Every generated split must exist under its actual numbered name and pass the reader manifest. A successful hash only proves those output bytes remain unchanged, not conversion correctness or model quality.

Length stop, malformed thinking, wrong arithmetic or empty final answer

Treat the diagnostic as failed. Require true EOS, strict native parse and closed reasoning with useful final text. Do not repair malformed reasoning or substitute chat mode; a larger budget needs separate context/resource review.

HTTP 401 or connection refused

Check the foreground initialization logs, exact workstation loopback and matching private key.

Stop the model

1. 1. Stop the foreground service

   Press Ctrl+C in the foreground terminal. Use the same trusted workstation to verify the listener is gone.

   CommandCopy command

   if curl --silent --max-time 3 http://127.0.0.1:8080/health >/dev/null; then echo "Still serving: stop the intended process"; exit 1; fi

   Expected result: The intended loopback service no longer responds.

Uninstall

1. 1. Remove the dedicated source/conversion/service files

   After stopping, back up desired logs/manifests/results and confirm the exact dedicated directory. This removes native inputs, symlinks, all intermediate/final splits, venv/build and key; shared system packages remain.

   CommandCopy command

   rm -r -- "$HOME/deepseek-speciale-hosting"

   Expected result: Dedicated files removed; shared system packages remain.

Exact model and requirements

Artifact:

DeepSeek AI native checkpoint; reader-authored conversion, not a publisher GGUF / Full DeepSeek V3.2 Speciale reader-converted Q4_K_M · checkpoint deepseek-ai/DeepSeek-V3.2-Speciale

Publisher revision:

c562883eda916fd699a44bbf1f4987a53b96008b

Artifact digest:

Final reader-generated GGUF composition and SHA256 are unknown until that exact conversion; reader records and checks every output split before serving.

Download size:

Unknown

Memory requirement (unknown):

Unknown — Lazy conversion limits eager tensor loading but does not prove 512 GiB peak for conversion, quantization or serving. Routing/expert buffers, DSA/MLA cache, mapped inputs, scratch, OS and output state remain unknown.

System RAM / disk:

Unknown / Unknown

Placement:

single device. One CPU host. Actual reader-generated F16 and Q4_K_M disk split counts remain unknown until complete conversion; every numbered split is required. No device, tensor or pipeline sharding. All language layers, routed/shared experts and DSA/MLA computation on one CPU host; no GPU offload or selective expert subset.

KV cache:

F16 cache flags are explicit; native DSA maintains separate MLA and lightning-indexer state. Exact state layout and working-memory peak remain unmeasured.

Workload:

16,384 token context; Unknown; Unknown; concurrency 1; batch 1; cache unknown; repetitions Unknown.

Tokenizer:

Exact Speciale native tokenizer with authoritative native Python encoder; conversion-only BOS metadata adjustment is explicit · c562883eda916fd699a44bbf1f4987a53b96008b

Sampling / reasoning:

Native publisher recommends temperature 1.0 and top_p 0.95 for local deployment. Top_k 0, min_p 0 and repeat_penalty 1 are author choices. True native EOS is mandatory; length/word stop cannot substitute for complete reasoning and final text. Speciale is exclusively a deep-reasoning checkpoint and explicitly does not support tool calling. Both initial arithmetic and follow-up use native thinking mode with history and dropped past reasoning. Require actual EOS, nonempty closed thinking and nonempty final answer. No ordinary chat mode, tools, Jinja substitute or reasoning-disable switch is provided. 16,384 total / 8,192 output is an author short-fixture allocation, not a publisher full-reasoning recommendation.

Runtime prerequisites:

Ubuntu 24.04 x86_64; See prerequisites above.

Official artifact · License

Exact Speciale native card explicitly grants repository and model weights under MIT. Retain the copyright/permission notice in copies or substantial portions; the actual license disclaims warranties. Reader conversion is a modification with no publisher quantization-quality or byte-equivalence claim. No terms acceptance, commercial guarantee or legal clearance is performed for the reader.

• Native Speciale Python encoder/parser · 0 GiB · revision c562883eda916fd699a44bbf1f4987a53b96008b

• All 163 native safetensors inputs total 689,483,049,129 bytes. The native index metadata total_size is 1,370,793,842,752 bytes; it is not the serialized FP8 sum or a measured F16 GGUF size.
• A 4 TiB working filesystem and 512 GiB RAM are author allocations, not measured fit/minima. Native inputs, F16 intermediate and final quantized output coexist; scratch/loading/package/build space adds unknown demand. Stop if actual disk/RAM cannot accommodate the workflow.
• Full native 61 main layers, routed/shared experts and DSA lightning indexer remain. The converter preserves appended NextN by default; no --no-mtp, tensor removal, active-expert-only or no-light derivative is used. Speculative MTP execution remains outside this ordinary autoregressive reasoning guide.

Install the runtime

1. 1. Build pinned CPU tools and qualify the reader conversion environment

   Build exact native CPU tools and install the official CPU wheel into an isolated Python 3.12 venv. Its hash comes from the archived official wheel index, not a wheel downloaded by the author. Use exact checkout requirements; no custom conversion kernels or native architecture patch. Stop on any error and retain actual environment logs.

   CommandCopy command

   set -e
   sudo apt-get update
   sudo apt-get install -y build-essential cmake git curl ca-certificates openssl python3.12 python3.12-venv
   mkdir -p "$HOME/deepseek-speciale-hosting" 
   cd "$HOME/deepseek-speciale-hosting"
   python3.12 - <<'PYDISK'
   import shutil
   assert shutil.disk_usage('.').free >= 3*1024**4, 'Provide the planned 4 TiB filesystem with at least the author-selected 3 TiB free preflight floor; actual peak remains unknown'
   PYDISK
   git clone https://github.com/ggml-org/llama.cpp.git
   git -C llama.cpp checkout --detach 620d2225cc436ab0b001e3200e590e3b286ef9ab
   test "$(git -C llama.cpp rev-parse HEAD)" = 620d2225cc436ab0b001e3200e590e3b286ef9ab
   cmake -S llama.cpp -B llama.cpp/build -DCMAKE_BUILD_TYPE=Release -DGGML_NATIVE=ON -DGGML_METAL=OFF
   cmake --build llama.cpp/build --config Release -j 64
   python3.12 -m venv .venv
   curl --fail --location 'https://download-r2.pytorch.org/whl/cpu/torch-2.11.0%2Bcpu-cp312-cp312-manylinux_2_28_x86_64.whl' -o 'torch-2.11.0+cpu-cp312-cp312-manylinux_2_28_x86_64.whl'
   echo 'f82e2ae20c1545bb03997d1cc3143d94e14b800038669ee1aca45808a9acc338  torch-2.11.0+cpu-cp312-cp312-manylinux_2_28_x86_64.whl' | sha256sum --check
   .venv/bin/python -m pip install './torch-2.11.0+cpu-cp312-cp312-manylinux_2_28_x86_64.whl'
   .venv/bin/python -m pip install -r llama.cpp/requirements/requirements-convert_hf_to_gguf.txt
   .venv/bin/python -m pip check
   .venv/bin/python -m pip freeze > resolved-conversion-environment.txt
   .venv/bin/python - <<'PYCPU'
   import torch
   assert torch.__version__ == '2.11.0+cpu' and hasattr(torch,'float8_e8m0fnu')
   PYCPU
   ./llama.cpp/build/bin/llama-server --version

   Expected result: Exact source builds, wheel hash passes and CPU version / dependency checks pass, or setup stops. These are reader steps, not author execution results.

Download the model

1. 1. Write the fixed native artifact helper

   Save this exact reader-authored stdlib helper. It accepts safe fixed native filenames and constructs URLs only from the exact Speciale checkpoint pin. Downloads are streamed and capped; every source file must match its hash and size.

   CommandCopy command

   set -e
   cd "$HOME/deepseek-speciale-hosting"
   cat > reader-artifacts.py <<'PYARTIFACT'
   """Reader-authored bounded artifact preparation; no model/native imports."""
   import pathlib,hashlib,json,re,sys,urllib.request,os
   
   def digest(path):
    h=hashlib.sha256()
    with pathlib.Path(path).open('rb')as stream:
     for chunk in iter(lambda:stream.read(8*1024*1024),b''):h.update(chunk)
    return h.hexdigest()
   def validate_entry(e):
    if not isinstance(e,dict)or set(e)!={'name','bytes','sha256'}:raise ValueError('manifest_shape')
    if not isinstance(e['name'],str)or not re.fullmatch(r'[A-Za-z0-9_.-]+',e['name']):raise ValueError('unsafe_filename')
    if type(e['bytes'])is not int or e['bytes']<=0 or not isinstance(e['sha256'],str)or not re.fullmatch('[0-9a-f]{64}',e['sha256']):raise ValueError('invalid_identity')
    prefix='https://huggingface.co/deepseek-ai/DeepSeek-V3.2-Speciale/resolve/c562883eda916fd699a44bbf1f4987a53b96008b/'
    # URLs are constructed from the fixed native pin, never accepted from manifest input.
   def verify(path,e):
    validate_entry(e)
    if path.stat().st_size!=e['bytes']or digest(path)!=e['sha256']:raise ValueError('artifact_identity_mismatch')
   def download(root,manifest,opener=urllib.request.urlopen):
    root=pathlib.Path(root);root.mkdir(exist_ok=True)
    if len({e['name']for e in manifest})!=len(manifest):raise ValueError('duplicate_names')
    for e in manifest:
     validate_entry(e);path=root/e['name']
     if path.exists():verify(path,e);continue
     temp=path.with_name(path.name+'.partial')
     try:
      with opener('https://huggingface.co/deepseek-ai/DeepSeek-V3.2-Speciale/resolve/c562883eda916fd699a44bbf1f4987a53b96008b/'+e['name'],timeout=120)as response,temp.open('wb')as output:
       total=0
       while True:
        block=response.read(8*1024*1024)
        if not block:break
        total+=len(block)
        if total>e['bytes']:raise ValueError('oversized_download')
        output.write(block)
      verify(temp,e);temp.replace(path)
     except Exception:
      temp.unlink(missing_ok=True);raise
     print('Verified '+e['name'],flush=True)
   def prepare(native,dest,manifest):
    native=pathlib.Path(native).resolve();dest=pathlib.Path(dest)
    for e in manifest:verify(native/e['name'],e)
    if dest.exists():raise ValueError('conversion_input_must_be_new')
    index=json.loads((native/'model.safetensors.index.json').read_text())
    if set(index['weight_map'].values())!={e['name']for e in manifest if e['name'].endswith('.safetensors')}:raise ValueError('incomplete_index')
    dest.mkdir()
    for e in manifest:
     if e['name']!='tokenizer_config.json':(dest/e['name']).symlink_to(native/e['name'])
    original=json.loads((native/'tokenizer_config.json').read_text())
    if original.get('add_bos_token')is not False:raise ValueError('unexpected_original_bos_setting')
    changed=dict(original);changed['add_bos_token']=True
    (dest/'tokenizer_config.json').write_text(json.dumps(changed,indent=2)+'\n')
    if {k:v for k,v in changed.items()if k!='add_bos_token'}!={k:v for k,v in original.items()if k!='add_bos_token'}:raise ValueError('unexpected_config_change')
    print('Original native metadata preserved; only conversion-input add_bos_token changed to true.')
   def splits(root,prefix):
    root=pathlib.Path(root);files=sorted(root.glob(prefix+'-*-of-*.gguf'));rows=[];total=None
    for i,path in enumerate(files,1):
     match=re.fullmatch(re.escape(prefix)+r'-(\d{5})-of-(\d{5})\.gguf',path.name)
     if not match or int(match[1])!=i:raise ValueError('split_sequence')
     if total is None:total=int(match[2])
     if int(match[2])!=total or path.stat().st_size<=0:raise ValueError('split_shape')
     rows.append({'name':path.name,'bytes':path.stat().st_size,'sha256':digest(path)})
    if not rows or len(rows)!=total:raise ValueError('incomplete_splits')
    return rows
   if __name__=='__main__':
    action=sys.argv[1]
    if action in ('download','prepare'):
     manifest=json.loads(pathlib.Path('native-download-manifest.json').read_text())
     if action=='download':download('native',manifest)
     else:prepare('native','conversion-input',manifest)
    elif action=='manifest':
     rows=splits(sys.argv[2],sys.argv[3]);pathlib.Path(sys.argv[4]).write_text(json.dumps(rows,indent=2)+'\n');print(rows[0]['name'])
    elif action=='verify':
     root=pathlib.Path(sys.argv[2]);saved=json.loads(pathlib.Path(sys.argv[4]).read_text());actual=splits(root,sys.argv[3])
     if actual!=saved:raise ValueError('reader_output_changed')
     print(str(root/actual[0]['name']))
    else:raise ValueError('unknown_action')
   PYARTIFACT
   echo 'dfbc7919b95b002a2f3a676f22537d864a689a9f9d4042e37d77bcf779f35879  reader-artifacts.py' | sha256sum --check

   Expected result: Exact helper is saved; no model download or execution occurs until the later reader download step.

2. 2. Write exact native manifest part 1

   Save this exact source metadata chunk. All chunks are combined and checked before download; no listed shard is optional.

   CommandCopy command

   set -e
   cd "$HOME/deepseek-speciale-hosting"
   cat > native-manifest-part-1.json <<'MANIFEST'
   [
     {
       "name": "model-00001-of-000163.safetensors",
       "bytes": 5233198531,
       "sha256": "3b45dd46fd8270cce028029c0ba90d22d7cc61a75fae1b62c2c66e154e5c2a92"
     },
     {
       "name": "model-00002-of-000163.safetensors",
       "bytes": 4302383956,
       "sha256": "aba186c3680e6e6fef536be1853c5b6b7687db84af7e331dbbfbe5825b562f57"
     },
     {
       "name": "model-00003-of-000163.safetensors",
       "bytes": 4302384377,
       "sha256": "0564184ab71017a4cf573ef548b2adc323424e6ae8f7c1f0699c3bf701b8abce"
     },
     {
       "name": "model-00004-of-000163.safetensors",
       "bytes": 4302121967,
       "sha256": "a54bfa7943348cae8a82b307a336375d0753c59de90c58f2acdcaa4e5951727d"
     },
     {
       "name": "model-00005-of-000163.safetensors",
       "bytes": 4302384146,
       "sha256": "815bb2496eef215f8641f502ef256bab4d46cda759e49aa422708a6d48888b39"
     },
     {
       "name": "model-00006-of-000163.safetensors",
       "bytes": 4307162046,
       "sha256": "95db1f510732e501771a63dae3d9b02e43ca6b70f3361c56ff76bc2ab829a6f0"
     },
     {
       "name": "model-00007-of-000163.safetensors",
       "bytes": 4312028034,
       "sha256": "9cfb3d2bd41518b0556600484206af3e1c7118295ef5b5406206b918ba4eefe4"
     },
     {
       "name": "model-00008-of-000163.safetensors",
       "bytes": 4302384334,
       "sha256": "3eace1dabe821b780a8092ad52f792a259ab00050b34259dc99ba934d69d5931"
     },
     {
       "name": "model-00009-of-000163.safetensors",
       "bytes": 4302122175,
       "sha256": "1ceebf763225f8e6614eaefa072f8dce347ab1c2f869f21770b5463ecd610cbd"
     },
     {
       "name": "model-00010-of-000163.safetensors",
       "bytes": 4302383938,
       "sha256": "e9b2d1dc294cc8707d7c42eb8e752d744b7d5d2fa2b6493045e72c483a560f63"
     },
     {
       "name": "model-00011-of-000163.safetensors",
       "bytes": 4302384377,
       "sha256": "1057b94c230c51d6dca7c5821fe6229158ad580983246990f8b465b658b3e482"
     },
     {
       "name": "model-00012-of-000163.safetensors",
       "bytes": 1483135583,
       "sha256": "7b864bb3fc1f2ccbcee329da2b38dae6a4cb79da1cb772a41ac0084addad0ce8"
     },
     {
       "name": "model-00013-of-000163.safetensors",
       "bytes": 4302060527,
       "sha256": "c139a90e4d23c60a3d228eb6716620de3cd03866819497664dc132fb258ce89f"
     },
     {
       "name": "model-00014-of-000163.safetensors",
       "bytes": 4302384328,
       "sha256": "9df81f55f08aafe169fcf3b6f5ec763577ab6af13a50ce204af32234887b7ce4"
     },
     {
       "name": "model-00015-of-000163.safetensors",
       "bytes": 4302122183,
       "sha256": "9220da217fc17dafe1a8ca8279202fa82a9b7e1dbfa31331296c26075db530f1"
     },
     {
       "name": "model-00016-of-000163.safetensors",
       "bytes": 4302383930,
       "sha256": "7fe739f6b49e44ad52c395484ca9b24099c2cad99a39c661e85cdff9f927777d"
     },
     {
       "name": "model-00017-of-000163.safetensors",
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     },
     {
       "name": "model-00018-of-000163.safetensors",
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     },
     {
       "name": "model-00019-of-000163.safetensors",
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     },
     {
       "name": "model-00020-of-000163.safetensors",
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     },
     {
       "name": "model-00021-of-000163.safetensors",
       "bytes": 4302122373,
       "sha256": "012b83599e1ad690eed57f7622f9654b74a2c63fdde8c665435c15d7aa15c24a"
     },
     {
       "name": "model-00022-of-000163.safetensors",
       "bytes": 4302384890,
       "sha256": "ee45b243151874fb2a9c0177d50e982699f85afe5b5791faa517fef8abfe4012"
     },
     {
       "name": "model-00023-of-000163.safetensors",
       "bytes": 4302122786,
       "sha256": "30aec317197328b3a32338211b5b76e68d7647689c79ab1fd9bf8e22acc975aa"
     },
     {
       "name": "model-00024-of-000163.safetensors",
       "bytes": 4302384494,
       "sha256": "be65b867b92a4faf3341e76d3f03e714a5992c36b904ad0c6e23792d7ef4f518"
     },
     {
       "name": "model-00025-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "36ba6cb562bf8565edfdd7bedce9d1faad8cab4ee636f7d98012f5003c7d2916"
     },
     {
       "name": "model-00026-of-000163.safetensors",
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       "sha256": "5d5b6f48af4db515acd26f18f202c864c0ba10d730f95c887bae72657b0f58c2"
     },
     {
       "name": "model-00027-of-000163.safetensors",
       "bytes": 4302384680,
       "sha256": "c2fbcc2560daf3e79851f520c95ea982b4d3b5d29efe882305e831ba98346d9a"
     },
     {
       "name": "model-00028-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "41aa902c6a3646bab8af4c9de2fdd004b09357bf1565145b8a89265fd2ee3dc5"
     },
     {
       "name": "model-00029-of-000163.safetensors",
       "bytes": 4302122420,
       "sha256": "8c22f8339cb47d10d4ea28e25e9d685d7a5d830f3d1fa97982884353a7f7d109"
     },
     {
       "name": "model-00030-of-000163.safetensors",
       "bytes": 4302384870,
       "sha256": "dd8a7cbdf6a3a99205951f0862e379caf80ffa71c912a7efd7fbd23f04009880"
     }
   ]
   MANIFEST
   echo '4261b547757ca9389b190aabed2f40d4ac7c883e7c59a62c691afd3deedeb263  native-manifest-part-1.json' | sha256sum --check

   Expected result: This exact manifest chunk passes its SHA check.

3. 3. Write exact native manifest part 2

   Save this exact source metadata chunk. All chunks are combined and checked before download; no listed shard is optional.

   CommandCopy command

   set -e
   cd "$HOME/deepseek-speciale-hosting"
   cat > native-manifest-part-2.json <<'MANIFEST'
   [
     {
       "name": "model-00031-of-000163.safetensors",
       "bytes": 4302122808,
       "sha256": "dcf4d7f3678b9b8cc1395dd34a9a4e3af182ec00713cb850ea6a180258e7ac01"
     },
     {
       "name": "model-00032-of-000163.safetensors",
       "bytes": 4302384470,
       "sha256": "d033c84f69152620b4403f3789e72a4f52cff54447de741eacea4ec8e2b4bc07"
     },
     {
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       "bytes": 4302384963,
       "sha256": "8dd3a4b54a9ee4bdce1ab4343511a19a00a098ff86dd59124a49649970683982"
     },
     {
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       "bytes": 1864917414,
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     },
     {
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       "bytes": 4302061105,
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     },
     {
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       "bytes": 4302384914,
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     },
     {
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       "sha256": "2460764a988c1209dee1f1d12b2154ea8d2adca9e1467db50afccee28f130507"
     },
     {
       "name": "model-00038-of-000163.safetensors",
       "bytes": 4302384516,
       "sha256": "142080cd861b80cec8993968c202a0bd6b18c635807fb44c1aae675456f2d268"
     },
     {
       "name": "model-00039-of-000163.safetensors",
       "bytes": 4302384961,
       "sha256": "4ed51d60523069d85737435578bc5635799a02b96fa7d26de5633deae3b15eb5"
     },
     {
       "name": "model-00040-of-000163.safetensors",
       "bytes": 4302122576,
       "sha256": "aaba9853f30a66594b00a9f3752e8d43259590f5c6d8923fcb271ab897effec1"
     },
     {
       "name": "model-00041-of-000163.safetensors",
       "bytes": 4302384704,
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     },
     {
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       "bytes": 4302384963,
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     },
     {
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     },
     {
       "name": "model-00044-of-000163.safetensors",
       "bytes": 4302384890,
       "sha256": "4ca9f3a70b16c67cfd97c3421f3d0d18bd36441a7be730c5283eeb89f917039f"
     },
     {
       "name": "model-00045-of-000163.safetensors",
       "bytes": 4302122786,
       "sha256": "931d74cc078fc529b52c254fb1a9e77f9f9a5da0f78c558b803c9fd99a2c3722"
     },
     {
       "name": "model-00046-of-000163.safetensors",
       "bytes": 4302384494,
       "sha256": "a7e443c1f167987939b2d2b68407a6b3721a46138854865c94d009a755624929"
     },
     {
       "name": "model-00047-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "a97023b471232e730265c091bd93267a0a58b02e0c78164aa7b22fefdbea158a"
     },
     {
       "name": "model-00048-of-000163.safetensors",
       "bytes": 4302122598,
       "sha256": "5f1e2d547dbef9507f0f9278360b6eadbbe579df4f1559cfa9460117c4fa0dba"
     },
     {
       "name": "model-00049-of-000163.safetensors",
       "bytes": 4302384680,
       "sha256": "66afeba2a55df6736b7990054498e28a0adb9f3ca14a3fb6241a5a40844e9a25"
     },
     {
       "name": "model-00050-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "a97f1ff372698faa88c2717265e97e404d51ba5599b74163df6fee19d2b5e186"
     },
     {
       "name": "model-00051-of-000163.safetensors",
       "bytes": 4302122420,
       "sha256": "634e40ba294b1ff0e13c1ad1e3818fa2140c74138779b258d1c19ff17a0e8dde"
     },
     {
       "name": "model-00052-of-000163.safetensors",
       "bytes": 4302384870,
       "sha256": "b4594c999e5bc3c40843282d8e34aac6e4976d36077ffad7037a18ab08e507bd"
     },
     {
       "name": "model-00053-of-000163.safetensors",
       "bytes": 4302122808,
       "sha256": "bcf16d4eba83ff6647f3c301eacdee1587bd1fe4f768c4354e00baa5b4da6dad"
     },
     {
       "name": "model-00054-of-000163.safetensors",
       "bytes": 4302384470,
       "sha256": "04db2549b0761d90eeacccc985b2e057c8fd9b193a43c477ba9944fd10eb8af7"
     },
     {
       "name": "model-00055-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "863441a303a9f06bd67acee1caa22849fdd4acf0a9523a74fb7f4cc2d9864e87"
     },
     {
       "name": "model-00056-of-000163.safetensors",
       "bytes": 1864917414,
       "sha256": "c993b3fb3fde9ac95329b261f1c6391b519c236b162abb3280e2151c7b344531"
     },
     {
       "name": "model-00057-of-000163.safetensors",
       "bytes": 4302061105,
       "sha256": "f18cd8b7b63d1351acfbd3cc07ada6fd85b0fa990c407c6940478a3531c8903a"
     },
     {
       "name": "model-00058-of-000163.safetensors",
       "bytes": 4302384914,
       "sha256": "b5a2cfce49cbe06b43e590f9d4564b133224d22ac6ac10db5e50f7089bd45c67"
     },
     {
       "name": "model-00059-of-000163.safetensors",
       "bytes": 4302122764,
       "sha256": "2feb7533949df0fb668c18df5146e242e5dd3c6939e99a9062f768bef1dfe157"
     },
     {
       "name": "model-00060-of-000163.safetensors",
       "bytes": 4302384516,
       "sha256": "ddf2505aa4f8bbc0215bcafcc68c9cc8040d7a28e571ebe4f5801b2fdbbfbbf0"
     }
   ]
   MANIFEST
   echo '425ae45a19742bf01fc33ae0bb2ce94eff52d7cdd6d5eef7d9c24c0e472174e1  native-manifest-part-2.json' | sha256sum --check

   Expected result: This exact manifest chunk passes its SHA check.

4. 4. Write exact native manifest part 3

   Save this exact source metadata chunk. All chunks are combined and checked before download; no listed shard is optional.

   CommandCopy command

   set -e
   cd "$HOME/deepseek-speciale-hosting"
   cat > native-manifest-part-3.json <<'MANIFEST'
   [
     {
       "name": "model-00061-of-000163.safetensors",
       "bytes": 4302384961,
       "sha256": "45a2f2e4c0655992d052573f48b8355518291e840663fce85965e52bf2ae2623"
     },
     {
       "name": "model-00062-of-000163.safetensors",
       "bytes": 4302122576,
       "sha256": "dced6863869f2182a16eb384dfb1aabb979e63eb485f5f73291d0bd249437495"
     },
     {
       "name": "model-00063-of-000163.safetensors",
       "bytes": 4302384704,
       "sha256": "525bc417483c458f404947ba584019f18ccf235243e9df75f2dd81a178193af8"
     },
     {
       "name": "model-00064-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "d0bee64de778717221d961419b2b042f1eb6bc38e58cee585774dfafb8db87e7"
     },
     {
       "name": "model-00065-of-000163.safetensors",
       "bytes": 4302122398,
       "sha256": "4589fa62e0cf08216d2b9f7cb4649a7bc3c4912df7b8de19787515d36ee8adab"
     },
     {
       "name": "model-00066-of-000163.safetensors",
       "bytes": 4302384890,
       "sha256": "0a74c81756d57de4c083674f49c5276d2c5edf11b9a7dbc87be31023c131ebc9"
     },
     {
       "name": "model-00067-of-000163.safetensors",
       "bytes": 4302122786,
       "sha256": "bfcd9034dedc9f3c009cc4b544ab8e129efc9359622cec9db69f8c3d53473324"
     },
     {
       "name": "model-00068-of-000163.safetensors",
       "bytes": 4302384494,
       "sha256": "5d381484b92ad457ccfda696c6a570e05631ec6a1a5dcee18ea1c64899b8164b"
     },
     {
       "name": "model-00069-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "58434bc6afe5c05d19f01295525a6a0a355a838e72d48de3048423f7af15626e"
     },
     {
       "name": "model-00070-of-000163.safetensors",
       "bytes": 4302122598,
       "sha256": "4f4fc1d62e0f4367326d8a5edd8de3470cec82f3f04974f5e54f8e7ce98450a8"
     },
     {
       "name": "model-00071-of-000163.safetensors",
       "bytes": 4302384680,
       "sha256": "ab19d958c521718a6d35232dd0d4dcc996d6105de6237c7bbeee0268a2a9bd41"
     },
     {
       "name": "model-00072-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "bd3c245cfab46212e2a2c6c1e9c33fd2a3ae4b8cc876ed0f400e16ea65b2de30"
     },
     {
       "name": "model-00073-of-000163.safetensors",
       "bytes": 4302122420,
       "sha256": "9e53968bfcab515a5b93a89d4afa635e85150a7f5ccaa87faa05183e9540fc07"
     },
     {
       "name": "model-00074-of-000163.safetensors",
       "bytes": 4302384870,
       "sha256": "0c9d63b66cb21e72d732c81ff36e8583bb0943468ba38735012f356ee4525df5"
     },
     {
       "name": "model-00075-of-000163.safetensors",
       "bytes": 4302122808,
       "sha256": "79e1c07ef8d2d1861fe9fde95751b53b9c81eda6a76d13948dfb8520f225d0c8"
     },
     {
       "name": "model-00076-of-000163.safetensors",
       "bytes": 4302384470,
       "sha256": "8de0b608082953689c130df6494c6180b676dcb7f7e64119c91ce9cfd47d5edf"
     },
     {
       "name": "model-00077-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "ce8e4069167d26c2c809ee6a5613f3e9be50982704455bde04273ba87bdd0390"
     },
     {
       "name": "model-00078-of-000163.safetensors",
       "bytes": 1864917414,
       "sha256": "3ac5a8a9404fe6f6a829fdf49087be25571090f7afc0d3ad142562497af4a9e0"
     },
     {
       "name": "model-00079-of-000163.safetensors",
       "bytes": 4302061105,
       "sha256": "7bd35ade9310684161536787e07474dd676b340986787f22708512a4a17828b1"
     },
     {
       "name": "model-00080-of-000163.safetensors",
       "bytes": 4302384914,
       "sha256": "4d00329410e711200d04d1cc3fed93e5ca9f5159598a29f8bfdd06cda01320ff"
     },
     {
       "name": "model-00081-of-000163.safetensors",
       "bytes": 4302122764,
       "sha256": "c7d1a0207848e81ea4465fe11f07621929305f2cb35a8d75ffb560beab8dd242"
     },
     {
       "name": "model-00082-of-000163.safetensors",
       "bytes": 4302384516,
       "sha256": "dc219cc84fb914ae12617fbc0f9b032ffefb5f76314e0e116637acc6fa9b9a95"
     },
     {
       "name": "model-00083-of-000163.safetensors",
       "bytes": 4302384961,
       "sha256": "4c0bb64431002edf1937c85dbddf579848e75c161791888db4daed10f5af4035"
     },
     {
       "name": "model-00084-of-000163.safetensors",
       "bytes": 4302122576,
       "sha256": "90183af42f0b025543c48d97608d03d8da16a5050b0097499c46fb2c356b1feb"
     },
     {
       "name": "model-00085-of-000163.safetensors",
       "bytes": 4302384704,
       "sha256": "aae4b6e751c2ed573cb2299f39ffe433618955039d0b52246fec7c0ecf3fa7d5"
     },
     {
       "name": "model-00086-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "56507428ba95e2e65aa2d92a02c4346e410b7d3d5079a634e9b6fcad808416f0"
     },
     {
       "name": "model-00087-of-000163.safetensors",
       "bytes": 4302122398,
       "sha256": "03abbca18e83996ba89b9cb64e28e745a54a8d3d4657d4dece995e46081fc353"
     },
     {
       "name": "model-00088-of-000163.safetensors",
       "bytes": 4302384890,
       "sha256": "beafd017117dfc722603a3de2fc4eb3fe38c97564ac505eac7fe146e16888d1c"
     },
     {
       "name": "model-00089-of-000163.safetensors",
       "bytes": 4302122786,
       "sha256": "8ae385ce053c9dedb5bcb164d80c2b6db93bfa91a268865d4c1b0d569a3c9467"
     },
     {
       "name": "model-00090-of-000163.safetensors",
       "bytes": 4302384494,
       "sha256": "37e67cd92190f4357879a3803c9e67502cd68904626a520221eb26e3ddaee4dd"
     }
   ]
   MANIFEST
   echo 'cb904b287e9f63eb68cb0d860a93756877f6bde2f1f0b10fb4bb641b892036c1  native-manifest-part-3.json' | sha256sum --check

   Expected result: This exact manifest chunk passes its SHA check.

5. 5. Write exact native manifest part 4

   Save this exact source metadata chunk. All chunks are combined and checked before download; no listed shard is optional.

   CommandCopy command

   set -e
   cd "$HOME/deepseek-speciale-hosting"
   cat > native-manifest-part-4.json <<'MANIFEST'
   [
     {
       "name": "model-00091-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "f01ce1c13a22636f48a4ac34f6ada537651572aa3e03be6a9a31fdca80a691f1"
     },
     {
       "name": "model-00092-of-000163.safetensors",
       "bytes": 4302122598,
       "sha256": "64d70b2f7643ee6d39c308d658d2a70c78af88ee83ae9f5ffe920da06384925f"
     },
     {
       "name": "model-00093-of-000163.safetensors",
       "bytes": 4302384680,
       "sha256": "bee293eb77e9261a07a1bec0563128b66fc615cce22804a79139bd4668da6c86"
     },
     {
       "name": "model-00094-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "17469ee58950c4b2dfffcccd1c17729969adcf3c1c1f1f43dd5e3b87541d6b64"
     },
     {
       "name": "model-00095-of-000163.safetensors",
       "bytes": 4302122420,
       "sha256": "d539783d8e5278cb57611edd108a3bfba426e360053b881170ae065b4822a990"
     },
     {
       "name": "model-00096-of-000163.safetensors",
       "bytes": 4302384870,
       "sha256": "596ef0684ba973813479949c39419b7214a07ff91787fa4f14b311c5fa5ebe1b"
     },
     {
       "name": "model-00097-of-000163.safetensors",
       "bytes": 4302122808,
       "sha256": "18b6fd1c57697dbf01e1c57adb0f80a0eb5838733600a10cc7f2b359bb5d7cb3"
     },
     {
       "name": "model-00098-of-000163.safetensors",
       "bytes": 4302384470,
       "sha256": "232bb1be729623b1a9d411e0dbd2899ddeddc6a361f54a0018b29eddb1a5383d"
     },
     {
       "name": "model-00099-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "29e9ec2944e09bc653e0a02cf2272f4a78c8c5355afb8315fc7773c3a8383d6e"
     },
     {
       "name": "model-00100-of-000163.safetensors",
       "bytes": 1864917414,
       "sha256": "51786f6acee394c24bc5851258887b51d26dfd628c9e2c888cd79f1be08d5f76"
     },
     {
       "name": "model-00101-of-000163.safetensors",
       "bytes": 4302061105,
       "sha256": "654b15641395876e4797f6f7587ccd815617dccd6a5612712a6aed2881aea4bc"
     },
     {
       "name": "model-00102-of-000163.safetensors",
       "bytes": 4302384914,
       "sha256": "91a03a21acc0326ff3f7719b799f2f7244a45fa08f74eafec0eddaa487d1378e"
     },
     {
       "name": "model-00103-of-000163.safetensors",
       "bytes": 4302122764,
       "sha256": "aaef65b416a8d96e6094b285739aa7675e6bbf9f8c6930f4232a00ba1bb030ae"
     },
     {
       "name": "model-00104-of-000163.safetensors",
       "bytes": 4302384516,
       "sha256": "e5d2f240b68fb46ab8ae29a9a95831a00c529bc8f51b8e20829b5700319c1ee5"
     },
     {
       "name": "model-00105-of-000163.safetensors",
       "bytes": 4302384961,
       "sha256": "da2ef8d5f33aaa517a89d6f908eed4a0722c8e836d221b72bf120da2a8f7bd1b"
     },
     {
       "name": "model-00106-of-000163.safetensors",
       "bytes": 4302122576,
       "sha256": "03621b54b89ede8ff214f5f14f5711f6168ab5f6f58681ee478fd71f30cb01d0"
     },
     {
       "name": "model-00107-of-000163.safetensors",
       "bytes": 4302384704,
       "sha256": "a3c9c62afd4e1609738856a3a68161067db218d3ff297033bf26d71218a8e54c"
     },
     {
       "name": "model-00108-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "eecb5e8394ad76b9f2aae5f4a5b0e30f20a92105e61c056cc8f98cc99fee1a92"
     },
     {
       "name": "model-00109-of-000163.safetensors",
       "bytes": 4302122398,
       "sha256": "096c4aeff0c34a1d600d1be5ee19171663a80a4dd7b690307c52776551bd1297"
     },
     {
       "name": "model-00110-of-000163.safetensors",
       "bytes": 4302384890,
       "sha256": "8182c7059f15f92407caa60cfd9c478cbd37ff49c097efaa28ecb86606e6dfdc"
     },
     {
       "name": "model-00111-of-000163.safetensors",
       "bytes": 4302122786,
       "sha256": "89b431c62abccaf8fc22437ef0fbd6f71cfb1a4b3fb01855a780cdf67c986ec9"
     },
     {
       "name": "model-00112-of-000163.safetensors",
       "bytes": 4302384494,
       "sha256": "d385889177b8c5d4d46cf02c0c57a10258d7b52369d207f87c72c7527a149e1f"
     },
     {
       "name": "model-00113-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "3dc999e44b63fe1c2c636ee217f2d83ad20a66aa8d3030ddbcfb9b4c157e9576"
     },
     {
       "name": "model-00114-of-000163.safetensors",
       "bytes": 4302122598,
       "sha256": "19495eea649f4eaf67de619224ccd5ef729983c68b0e8db6b60124933d5ce9eb"
     },
     {
       "name": "model-00115-of-000163.safetensors",
       "bytes": 4302384680,
       "sha256": "873bb28d7073048868a50a4587c506b4b75e07c93b43280ecb49038a070f8876"
     },
     {
       "name": "model-00116-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "ebb5b18a3d2c10f6733f90f02150d555d28e4126d9a9812fd2bd46c9b3220fd6"
     },
     {
       "name": "model-00117-of-000163.safetensors",
       "bytes": 4302122420,
       "sha256": "966fe1a15883edc44d4aeccf88eff5dd588aca792a401b5a6205707ab898a1a4"
     },
     {
       "name": "model-00118-of-000163.safetensors",
       "bytes": 4302384870,
       "sha256": "c8ef897e1dec39e212662d306a96dc5fa6f89b647c4b5cf289296618c74f2be7"
     },
     {
       "name": "model-00119-of-000163.safetensors",
       "bytes": 4302122808,
       "sha256": "e9431a5ba2dc20e7ff6a3d5c48e010dccb376d303c9a499b40f586e20812c395"
     },
     {
       "name": "model-00120-of-000163.safetensors",
       "bytes": 4302384470,
       "sha256": "6c72caab19c214eda985680d9ae62acac2922753f95a3e5440bc94ef56425b62"
     }
   ]
   MANIFEST
   echo 'a2c0741cdfc74188ea15a5d60b6012f259cda565ba72b7501d84947e4c53ecf5  native-manifest-part-4.json' | sha256sum --check

   Expected result: This exact manifest chunk passes its SHA check.

6. 6. Write exact native manifest part 5

   Save this exact source metadata chunk. All chunks are combined and checked before download; no listed shard is optional.

   CommandCopy command

   set -e
   cd "$HOME/deepseek-speciale-hosting"
   cat > native-manifest-part-5.json <<'MANIFEST'
   [
     {
       "name": "model-00121-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "caccd7c38c7595f75625e504f122156205609d5def97c5836e13608ba6e33862"
     },
     {
       "name": "model-00122-of-000163.safetensors",
       "bytes": 1864917414,
       "sha256": "321bbcbef0c710d66836681108269c49945665c78c744d9a15d9052add146ab3"
     },
     {
       "name": "model-00123-of-000163.safetensors",
       "bytes": 4302061105,
       "sha256": "9e0976ae801be4f6af51614b44e49f278c89ba724e46b90ad40ea023e82b854e"
     },
     {
       "name": "model-00124-of-000163.safetensors",
       "bytes": 4302384914,
       "sha256": "8c47c2d1309b68c57acbd6b3d2f12a6bde930f55de5f93b92122b391b0330b8d"
     },
     {
       "name": "model-00125-of-000163.safetensors",
       "bytes": 4302122764,
       "sha256": "50a7faeb6ce937184f318af85a3dc7aee61b5d39b93373ee16370cdd019254b4"
     },
     {
       "name": "model-00126-of-000163.safetensors",
       "bytes": 4302384516,
       "sha256": "584383202cec81c52c9e9454491d08f7ae0215bb5cf0d38fbe6585c5656d5253"
     },
     {
       "name": "model-00127-of-000163.safetensors",
       "bytes": 4302384961,
       "sha256": "efdb6f8ba904e252bdf8112439612059ca90cbebd4e6f4e35d32f00025f74048"
     },
     {
       "name": "model-00128-of-000163.safetensors",
       "bytes": 4302122576,
       "sha256": "ad872a598894e0706ae5749bb5545c00e9c03864c877ac7685edbb5f351886ba"
     },
     {
       "name": "model-00129-of-000163.safetensors",
       "bytes": 4302384704,
       "sha256": "febe4ee4154afd505a170367d152d4375df4482e8d632785ce5059656b2e4b43"
     },
     {
       "name": "model-00130-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "438ca4d1e799e1d61281a3c10dab0fb0682b2797f609e1ef543552e2da9e5f87"
     },
     {
       "name": "model-00131-of-000163.safetensors",
       "bytes": 4302122398,
       "sha256": "976877bcef9a45f6874cfce0e5106523bb2cd21fbe2b61e5fbf1d64619c73f3c"
     },
     {
       "name": "model-00132-of-000163.safetensors",
       "bytes": 4302384890,
       "sha256": "6913d5c42023d3cf26e0cee83836eabd604b8185b1815f9ceff87935ca09a78f"
     },
     {
       "name": "model-00133-of-000163.safetensors",
       "bytes": 4302122786,
       "sha256": "0b2f6f918109f4b1ce89c784d71410ba527fa529fc82b38fe66c1823d12ad815"
     },
     {
       "name": "model-00134-of-000163.safetensors",
       "bytes": 4302384494,
       "sha256": "b89357ea72f4d19d7fdb0bb571d4f9fae9145e3aaaed984a8f9f91a25c828ca0"
     },
     {
       "name": "model-00135-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "e06ab711e960be0a6018b1bfd4dbf5da883f57f2932f47b07a07a5fc6564f80c"
     },
     {
       "name": "model-00136-of-000163.safetensors",
       "bytes": 4302122598,
       "sha256": "f844c3004bb622600c8e4d7778c3112c17409163f2be19f64e9389459030df27"
     },
     {
       "name": "model-00137-of-000163.safetensors",
       "bytes": 4302384680,
       "sha256": "9f24493f3d67e3715bb401a66454846debdbd1f4615c247e384af9d4170219bc"
     },
     {
       "name": "model-00138-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "6c4293949318bea4aea34e77d4b8f5c24c81e4c8846dda6387299e032242b017"
     },
     {
       "name": "model-00139-of-000163.safetensors",
       "bytes": 4302122420,
       "sha256": "18ce46aa84a4993744c7a78024f3fe3074dce564ed516702adf898a144e3bf4b"
     },
     {
       "name": "model-00140-of-000163.safetensors",
       "bytes": 4302384870,
       "sha256": "adc2970ddae9b725901595eaae34fab6dcb94203fa3b8323e22b03dd14c7f6b7"
     },
     {
       "name": "model-00141-of-000163.safetensors",
       "bytes": 3245204828,
       "sha256": "36ffb84d6fa304372583182cec1fef00294daa5ce087ebf0ad22ded25a19e687"
     },
     {
       "name": "model-00142-of-000163.safetensors",
       "bytes": 4302061105,
       "sha256": "8a564710c22c6ce19b835e0632337369f9e9be4ed33c7c30a4d7ca45e7859616"
     },
     {
       "name": "model-00143-of-000163.safetensors",
       "bytes": 4302384914,
       "sha256": "84ce3f89ecb97c1d7ea227752c56c25c085bdc843c53f250d651833370455944"
     },
     {
       "name": "model-00144-of-000163.safetensors",
       "bytes": 4302122764,
       "sha256": "e4889ff54ac74758f6cdb95ef9c1798d10f2fd3b06e89f9d14b7e86f6ed8efdd"
     },
     {
       "name": "model-00145-of-000163.safetensors",
       "bytes": 4302384516,
       "sha256": "cd7ce1397dfd7a10085003b50f0ebbb541c9009832eb0498834b703875f68b7c"
     },
     {
       "name": "model-00146-of-000163.safetensors",
       "bytes": 4302384961,
       "sha256": "eb8473c1361858cc88689bbfde0d80e87dd4884786a712adc778886cb435d682"
     },
     {
       "name": "model-00147-of-000163.safetensors",
       "bytes": 4302122576,
       "sha256": "5710defd19fd0123913f4c0f3d10195538442b21ea5c228e44160a5073265d37"
     },
     {
       "name": "model-00148-of-000163.safetensors",
       "bytes": 4302384704,
       "sha256": "aa72c2da95c14896d8d11bdf22cdb469e85070e9be631de62aba2baa1d4c0c13"
     },
     {
       "name": "model-00149-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "c5acbb3c161819aab88f67aaf166638519590dc2f87f469d19ce6f98bbf8a0b8"
     },
     {
       "name": "model-00150-of-000163.safetensors",
       "bytes": 4302122398,
       "sha256": "cc53b2c7aee78c9735fb2ddca616c4ff7519ca358d1acfca4a4e90cfab3554de"
     }
   ]
   MANIFEST
   echo 'e4a30c312451f069575e68e7061541cd5d3497d700647c2892804c7ac7f3291f  native-manifest-part-5.json' | sha256sum --check

   Expected result: This exact manifest chunk passes its SHA check.

7. 7. Write exact native manifest part 6

   Save this exact source metadata chunk. All chunks are combined and checked before download; no listed shard is optional.

   CommandCopy command

   set -e
   cd "$HOME/deepseek-speciale-hosting"
   cat > native-manifest-part-6.json <<'MANIFEST'
   [
     {
       "name": "model-00151-of-000163.safetensors",
       "bytes": 4302384890,
       "sha256": "1def32f991993ffa0f80782d69d237bb9e69a1a82575e56f34f732101cea1301"
     },
     {
       "name": "model-00152-of-000163.safetensors",
       "bytes": 4302122786,
       "sha256": "b6630cad76fa28a9fb8e8aebd296cdbf4164096867177539bf28e6486a1d21f1"
     },
     {
       "name": "model-00153-of-000163.safetensors",
       "bytes": 4302384494,
       "sha256": "6326a6fc6bdaba357c2316e7b9ed65ab4538f1b010492b11b67cf05f720f4014"
     },
     {
       "name": "model-00154-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "171e7f22d6416a2231604a1ad8dfa00bd76d3308b530327b75e962169e0d6ff5"
     },
     {
       "name": "model-00155-of-000163.safetensors",
       "bytes": 4302122598,
       "sha256": "e938795a24925cf367c8f08b083f73744ba714ef0f2424b000a59b528128e1e6"
     },
     {
       "name": "model-00156-of-000163.safetensors",
       "bytes": 4302384680,
       "sha256": "567ddad661d9ecaf04f5dc6a0943a801d87f8a78da2ad93120e9cdfab38c8aba"
     },
     {
       "name": "model-00157-of-000163.safetensors",
       "bytes": 4302384963,
       "sha256": "bcebfeeb9244c117932ff424810ae745d5c68b70afffb6947007369c9c349a9f"
     },
     {
       "name": "model-00158-of-000163.safetensors",
       "bytes": 4302122420,
       "sha256": "9315ac9c3150edb096436190df544c98581238be04e207ebceea2c47dcad0403"
     },
     {
       "name": "model-00159-of-000163.safetensors",
       "bytes": 4302384870,
       "sha256": "a8c137bef6e4141ef3d51273173f25f700a33836ea253b5adb4112003142f4e8"
     },
     {
       "name": "model-00160-of-000163.safetensors",
       "bytes": 5285723731,
       "sha256": "6af9415a2e19b971073a8741170d104159d493f37fa52f9758254c82bebc391d"
     },
     {
       "name": "model-00161-of-000163.safetensors",
       "bytes": 4305819875,
       "sha256": "4c3a9de3f0f2919f71de2b84155812f1770ac5156e79656da22f7e0016c41e2e"
     },
     {
       "name": "model-00162-of-000163.safetensors",
       "bytes": 4302384938,
       "sha256": "c02a368f4188f3ec43484c98cbf29f5d99b42be4f45b3b6bcbdda56e8bc187b1"
     },
     {
       "name": "model-00163-of-000163.safetensors",
       "bytes": 6643591758,
       "sha256": "b8f64009d3dc3aa35c6d891a27232e45dd6cee755d22cf8a13ff9c8dc6591251"
     },
     {
       "name": "config.json",
       "bytes": 1552,
       "sha256": "c7fa8b191e9936d8e6a57d864baab82b792fae16a116416cdd3a75ba76bc5af1"
     },
     {
       "name": "tokenizer_config.json",
       "bytes": 795,
       "sha256": "b5de6cc1c6758d02c0d3cec0efa062f1161654475458003f6f293f6ef28acdaa"
     },
     {
       "name": "tokenizer.json",
       "bytes": 7847502,
       "sha256": "cd050be35cae877f8f0aa847f45aa87e23835a56ca32b29b28545597852784e5"
     },
     {
       "name": "model.safetensors.index.json",
       "bytes": 8938926,
       "sha256": "2a150b2af4aba7b037edc9fdba70f3b41abf758ee926279e7701d954298f9884"
     },
     {
       "name": "generation_config.json",
       "bytes": 171,
       "sha256": "c9ce7f8d4a66c6cedd053650db3596328f241f00a7e49e67b89e5c9e336e7205"
     },
     {
       "name": "LICENSE",
       "bytes": 1084,
       "sha256": "f2c6c602815669d292889e5be8c802f2ed950653b77999b1584e8e6aed25d040"
     }
   ]
   MANIFEST
   echo 'd27ad12ddd7d6b663ef0407fc81d8c6766bfa9aea30d08b4731aa87903887f17  native-manifest-part-6.json' | sha256sum --check

   Expected result: This exact manifest chunk passes its SHA check.

8. 8. Assemble and verify the full native checkpoint

   Combine all six metadata chunks, verify the exact 169-entry manifest and download all 163 native weights plus six metadata/license files. Preserve every original file. The native Python encoder is separately fetched and checked.

   CommandCopy command

   set -e
   cd "$HOME/deepseek-speciale-hosting"
   python3.12 - <<'PYMANIFEST'
   import pathlib,json,hashlib
   rows=[]
   for i in range(1,7):rows+=json.loads(pathlib.Path('native-manifest-part-'+str(i)+'.json').read_text())
   b=(json.dumps(rows,indent=2)+'\n').encode()
   assert len(rows)==169 and hashlib.sha256(b).hexdigest()=='f5614b81179c4d80badd132c3d22e2b9a4acbc68ccd86f180d3b4c13abbdd0ff'
   pathlib.Path('native-download-manifest.json').write_bytes(b)
   PYMANIFEST
   python3.12 reader-artifacts.py download
   curl --fail --location 'https://huggingface.co/deepseek-ai/DeepSeek-V3.2-Speciale/resolve/c562883eda916fd699a44bbf1f4987a53b96008b/encoding/encoding_dsv32.py' -o encoding_dsv32.py
   echo '5e068c2ba2a6e5ebe37a49bb005650c507e7935d77a32f3f7c11ee071498b370  encoding_dsv32.py' | sha256sum --check

   Expected result: All native inputs and encoder verify; any size/hash/access/missing-part failure stops.

Configure

1. 1. Convert complete native FP8 inputs and quantize all output splits

   Prepare a separate conversion-only metadata copy; source weights/config/tokenizer remain unchanged. Default lazy conversion dequantizes FP8 block scales and writes full F16 splits; no eager/no-mtp/pruning flag is used. Quantize with native keep-split support and record actual generated SHA/bytes for both sets. Unknown split counts and final bytes are discovered, never fabricated. Do not delete F16/native inputs to hide a failed or partial conversion.

   CommandCopy command

   set -e
   cd "$HOME/deepseek-speciale-hosting"
   python3.12 reader-artifacts.py prepare
   mkdir -p models/f16 models/q4
   .venv/bin/python llama.cpp/convert_hf_to_gguf.py conversion-input --outfile models/f16/Speciale-F16.gguf --outtype f16 --split-max-size 40G
   python3.12 reader-artifacts.py manifest models/f16 Speciale-F16 f16-output-manifest.json
   FIRST_F16="$(python3.12 reader-artifacts.py verify models/f16 Speciale-F16 f16-output-manifest.json)"
   ./llama.cpp/build/bin/llama-quantize --keep-split "$FIRST_F16" models/q4/Speciale-Q4_K_M Q4_K_M 64
   python3.12 reader-artifacts.py manifest models/q4 Speciale-Q4_K_M q4-output-manifest.json
   python3.12 reader-artifacts.py verify models/q4 Speciale-Q4_K_M q4-output-manifest.json
   umask 077
   if [ ! -e .api-key ]; then openssl rand -hex 32 > .api-key; fi
   test -s .api-key
   chmod 600 .api-key

   Expected result: Complete lazy conversion and quantization finish; all F16/Q4 splits form exact complete numbered sets and generated hashes/sizes are recorded. Existing service key is preserved. No successful conversion/fit is preclaimed.

2. 2. Write the thinking-only native diagnostic

   Save the exact original bounded stdlib client. The reader later loads the verified native encoder, uses thinking mode for both turns, rejects malformed/unfinished responses, and requires true EOS before official parsing. No ordinary chat, tools or external actions are substituted.

   CommandCopy command

   set -e
   cd "$HOME/deepseek-speciale-hosting"
   cat > reasoning-client.py <<'PYCLIENT'
   """Private native DeepSeek V3.2 Speciale thinking-only diagnostic; stdlib only."""
   import hashlib, importlib.util, json, pathlib, urllib.request, urllib.error
   BASE='http://127.0.0.1:8080'
   CONTEXT, OUTPUT = 16384, 8192
   ENCODER_SHA='5e068c2ba2a6e5ebe37a49bb005650c507e7935d77a32f3f7c11ee071498b370'
   BOS='<｜begin▁of▁sentence｜>'
   EOS='<｜end▁of▁sentence｜>'
   
   def positive(v): return type(v) is int and v>0
   
   def checked_messages(messages):
       if not isinstance(messages,list) or not 1<=len(messages)<=12: raise ValueError('Bounded conversation required')
       for i,m in enumerate(messages):
           if not isinstance(m,dict) or set(m)-{'role','content'}: raise ValueError('Only ordinary text conversation is accepted by this diagnostic')
           role,text=m.get('role'),m.get('content')
           if role not in ('system','user','assistant') or (role=='system' and i!=0): raise ValueError('Invalid role order')
           if not isinstance(text,str) or not text.strip() or len(text.encode())>12000: raise ValueError('Invalid text')
           if any(t in text for t in (BOS,EOS,'<｜User｜>','<｜Assistant｜>','<think>','</think>','｜DSML｜')): raise ValueError('Reserved native control marker in user content')
       roles=[m['role'] for m in messages if m['role']!='system']
       if not roles or roles!=['user' if i%2==0 else 'assistant' for i in range(len(roles))] or roles[-1]!='user': raise ValueError('Alternating user/assistant history ending in user required')
       return messages
   
   def complete(call,encode,parse,messages,mode):
       if mode != 'thinking': raise ValueError('Invalid native mode')
       checked_messages(messages)
       prompt=encode(messages,thinking_mode=mode,drop_thinking=True,add_default_bos_token=True)
       if not isinstance(prompt,str) or not prompt.startswith(BOS) or prompt.count(BOS)!=1: raise ValueError('Exactly one native BOS required')
       expected='<think>' if mode=='thinking' else '</think>'
       if not prompt.endswith(expected): raise ValueError('Native mode prefix mismatch')
       ids=call('/tokenize',{'content':prompt,'add_special':False,'parse_special':True}).get('tokens')
       if not isinstance(ids,list) or not ids or any(type(x)is not int or x<0 for x in ids) or ids[0]!=0 or ids.count(0)!=1: raise ValueError('Invalid token IDs or duplicate BOS')
       if len(ids)+OUTPUT>CONTEXT: raise ValueError('Input plus complete reasoning/output reserve exceeds context')
       body={'prompt':ids,'n_predict':OUTPUT,'temperature':1.0,'top_p':0.95,'top_k':0,'min_p':0,'repeat_penalty':1,'stream':False,'cache_prompt':False,'return_tokens':True,'stop':[]}
       result=call('/completion',body)
       if result.get('stop_type')!='eos' or result.get('truncated') is not False: raise ValueError('Require actual native EOS without truncation; limit/word stop does not prove completion')
       n=result.get('tokens_predicted')
       if not positive(n) or n>OUTPUT or result.get('tokens_evaluated')!=len(ids): raise ValueError('Usage mismatch')
       text=result.get('content')
       if not isinstance(text,str) or not text.strip(): raise ValueError('Empty completion')
       # Native server normally omits the EOS text. Reconstitute it only after actual EOS proof.
       if EOS in text and not text.endswith(EOS): raise ValueError('Unexpected internal EOS')
       serialized=text if text.endswith(EOS) else text+EOS
       parsed=parse(serialized,thinking_mode=mode)
       if not isinstance(parsed,dict) or parsed.get('tool_calls') or not isinstance(parsed.get('content'),str) or not parsed['content'].strip(): raise ValueError('Nonempty final text with no tools required')
       if mode=='thinking' and (not isinstance(parsed.get('reasoning_content'),str) or not parsed['reasoning_content'].strip() or '</think>' not in text): raise ValueError('Unclosed or empty native reasoning')
       return {'mode':mode,'inputTokens':len(ids),'outputCap':OUTPUT,'parsed':parsed,'nativeResponse':result}
   
   def http_call(key):
       def call(path,body=None):
           data=None if body is None else json.dumps(body).encode()
           req=urllib.request.Request(BASE+path,data=data,headers={'Authorization':'Bearer '+key,'Content-Type':'application/json'})
           with urllib.request.urlopen(req,timeout=7200) as r:
               if r.status!=200: raise ValueError('HTTP failure')
               raw=r.read(2000001)
           if len(raw)>2000000: raise ValueError('Response limit')
           obj=json.loads(raw)
           if not isinstance(obj,dict): raise ValueError('JSON object required')
           return obj
       return call
   
   def main():
       key=pathlib.Path('.api-key').read_text().strip()
       if len(key)!=64 or any(c not in '0123456789abcdef' for c in key): raise ValueError('Restore private service key')
       path=pathlib.Path('encoding_dsv32.py')
       if hashlib.sha256(path.read_bytes()).hexdigest()!=ENCODER_SHA: raise ValueError('Native encoder checksum mismatch')
       spec=importlib.util.spec_from_file_location('pinned_native_encoding',path)
       native=importlib.util.module_from_spec(spec);spec.loader.exec_module(native)
       call=http_call(key);call('/health')
       req=urllib.request.Request(BASE+'/completion',data=b'{}',headers={'Content-Type':'application/json'})
       try:
           with urllib.request.urlopen(req,timeout=30): raise ValueError('Unauthorized completion accepted')
       except urllib.error.HTTPError as e:
           if e.code!=401: raise
       history=[{'role':'user','content':'The community library is open weekdays 9am to 6pm, Saturday 10am to 4pm and closed Sunday. Using only this schedule, calculate total opening hours in a normal Monday-through-Sunday week. Explain your arithmetic briefly.'}]
       first=complete(call,native.encode_messages,native.parse_message_from_completion_text,history,'thinking')
       pathlib.Path('first-thinking-response.json').write_text(json.dumps(first,indent=2)+'\n')
       history += [{'role':'assistant','content':first['parsed']['content']},{'role':'user','content':'Using the same supplied schedule, how many hours is the library open on Saturday, and is it open on Sunday? Explain briefly.'}]
       second=complete(call,native.encode_messages,native.parse_message_from_completion_text,history,'thinking')
       pathlib.Path('followup-thinking-response.json').write_text(json.dumps(second,indent=2)+'\n')
       print(json.dumps({'firstThinking':first,'followupThinking':second},ensure_ascii=False))
       print('Manually require 5 times 9 plus 6 equals 51 weekly hours, Saturday six hours and Sunday closed; inspect the reasoning against the supplied schedule. Native EOS/closed thinking proves completion shape, not answer quality or speed.')
   if __name__=='__main__': main()
   PYCLIENT
   echo 'd52fafa538936b01ac9f96ff1c8c11e443861e1c82e14b8292f46264d5f6001d  reasoning-client.py' | sha256sum --check

   Expected result: The hash-verified client is saved without generation.

Start the model

1. 1. Start the complete reader-converted Speciale CPU model

   Reverify the complete reader-output manifest on every start. The first split loads the full set; native DSA and all experts remain. NextN weights remain in the complete artifact but no speculative draft is configured. F16 cache flags and disabled flash-attention fusion do not disable DSA. One 16,384-position sequence reserves up to 8,192 generated reasoning/final tokens.

   CommandCopy command

   set -e
   cd "$HOME/deepseek-speciale-hosting"
   FIRST_Q4="$(python3.12 reader-artifacts.py verify models/q4 Speciale-Q4_K_M q4-output-manifest.json)"
   ./llama.cpp/build/bin/llama-server -m "$FIRST_Q4" --alias deepseek-v32-speciale --host 127.0.0.1 --port 8080 --api-key-file .api-key --device none -ngl 0 -t 64 -c 16384 -np 1 -n 8192 --no-context-shift --flash-attn off --cache-type-k f16 --cache-type-v f16 -b 256 -ub 256 --special --temp 1.0 --top-p 0.95 --top-k 0 --min-p 0 --repeat-penalty 1

   Expected result: The complete reader-generated DEEPSEEK32 model initializes or a clear tensor/split/cache/allocation error stops setup. Actual startup, memory fit and speed are unknown.

Verify the setup

1. 1. Check authentication, reasoning, history, budget and native EOS

   Run in a second terminal inside this host. Count the complete native thinking prompt before generation and reserve all 8,192 output tokens. Both turns must reach true EOS without truncation, close nonempty native reasoning and provide a nonempty final answer. Manually inspect five weekdays times nine hours plus Saturday six equals 51 weekly hours, Saturday six and Sunday closed. Correct protocol shape is not reasoning quality.

   CommandCopy command

   set -e
   cd "$HOME/deepseek-speciale-hosting"
   python3.12 reasoning-client.py

   Expected result: Private protected route rejects unauthenticated access; both thinking responses complete with consistent positive usage and native parser acceptance. Incorrect arithmetic/facts, missing closure, length/word stop or malformed output fails.

Performance evidence

No compatible measurement available. Documented support and estimated memory do not establish response speed.

Limits and troubleshooting

• Complete source-qualified reader conversion only; no author weights/model imports/native encoder execution, dependency install/build/conversion/inference/fit/speed/quality result.
• Exact native Speciale is exclusively a deep-reasoning checkpoint and explicitly lacks tool calling. Both initial and follow-up requests use native thinking mode; no ordinary V3.2 chat, Exp, distillation, tools or no-light architecture is substituted.
• All 163 source files and exact metadata are required. Native serialized bytes total 689,483,049,129; index metadata total_size 1,370,793,842,752 is distinct. Final F16/Q4 GGUF bytes, hashes and split counts are reader-generated unknowns until actual conversion.
• Native converter default preserves full main DSA and appended NextN tensors. No --no-mtp, tensor removal, prune or alternate DeepseekV3 architecture is passed. Speculative MTP serving is not configured.
• The converter explicitly requires add_bos_token true. Only a separate conversion-input tokenizer metadata copy changes that key; originals remain hash-verified. Native Python encoding supplies one BOS and raw tokenizer add_special false at serving. No Jinja substitute is installed.
• 4 TiB working disk covers planning space for native inputs, F16 intermediate, unknown Q4 final and environment/build/scratch. 512 GiB RAM, lazy materialization and bounded token batches do not establish actual conversion or serving fit. Do not reclaim required inputs mid-failure to force a partial model.
• Native config has 163,840 positions and tokenizer declares 131,072. This guide deliberately uses 16,384 combined positions with 8,192 for reasoning and final text on a short arithmetic fixture. It is not a full-depth reasoning recommendation or long-context claim; truncation fails.
• Official CPU Torch wheel, exact runtime requirements and source are pinned; some transitive Python/system packages resolve during reader setup. Record actual versions/logs and stop on pip check, float8/conversion/runtime errors rather than claiming executed compatibility.
• MIT covers the exact native model and repository. Retain required notices in copies/substantial portions; conversion is a reader modification with no publisher accuracy certification.
• Full native GPU/distributed precision, tool-free longer reasoning tasks, other quantizations and speculative MTP remain open scopes. Required total guide jobs remains null; unknown memory, latency and task cost are not replaced by active-parameter math.

Conversion, unknown tensor, FP8 scale or resource failure

Stop and retain complete logs. Verify exact source/runtime/CPU wheel, all source hashes and derived tokenizer metadata. Do not remove DSA/NextN, change architecture, substitute an old derivative or bypass failed checks. Requalify a changed allocation/runtime separately.

Split sequence or generated-output hash mismatch

Do not serve. Preserve native/F16/output evidence and inspect failed conversion. Every generated split must exist under its actual numbered name and pass the reader manifest. A successful hash only proves those output bytes remain unchanged, not conversion correctness or model quality.

Length stop, malformed thinking, wrong arithmetic or empty final answer

Treat the diagnostic as failed. Require true EOS, strict native parse and closed reasoning with useful final text. Do not repair malformed reasoning or substitute chat mode; a larger budget needs separate context/resource review.

HTTP 401 or connection refused

Check the foreground initialization logs, exact VM loopback and matching key; keep public ingress closed and use only the documented existing SSH host.

Stop the model

1. 1. Stop the foreground service

   Press Ctrl+C in the foreground terminal. Close any SSH tunnel; stopping this process does not end EC2 or storage billing.

   CommandCopy command

   if curl --silent --max-time 3 http://127.0.0.1:8080/health >/dev/null; then echo "Still serving: stop the intended process"; exit 1; fi

   Expected result: The intended loopback service no longer responds.

Uninstall

1. 1. Remove the dedicated source/conversion/service files

   After stopping, back up desired logs/manifests/results and confirm the exact dedicated directory. This removes native inputs, symlinks, all intermediate/final splits, venv/build and key; shared system packages remain.

   CommandCopy command

   rm -r -- "$HOME/deepseek-speciale-hosting"

   Expected result: Dedicated files removed. Cloud retained resources require the separate billing lifecycle step.

Shut down cloud resources

1. 1. End cloud resource billing

   In EC2 us-east-1 stop this exact VM for later reuse or terminate it. Review root-volume Delete on termination and remove unwanted detached volumes, snapshots and reserved/Elastic/public IP resources. Stopped-instance storage and retained resources may still bill. Check Bills/Cost Explorer for final usage.

   Expected result: The exact instance is stopped or terminated as intended, and unwanted retained billed resources are removed. Stopping the native service alone does not end compute billing.