LLM Comparison
Nemotron 3 Nano 30B A3B vs Trinity Mini
Side-by-side specs, pricing & capabilities
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2/6 models| Organization | ||
| OpenTools Score | ||
| Family | Nemotron | Trinity |
| Status | Current | Current |
| Release Date | Dec 2025 | Dec 2025 |
| Context Window | 262K tokens | 131K tokens |
| Input Price | $0.05/M tokens | $0.04/M tokens |
| Output Price | $0.20/M tokens | $0.15/M tokens |
| Capabilities | textcode | textcode |
| Max Output | — | 131K tokens |
| API Identifier | nvidia/nemotron-3-nano-30b-a3b | arcee-ai/trinity-mini |
| View Nemotron 3 Nano 30B A3B | View Trinity Mini |
Cost Calculator
Enter your expected monthly token usage to compare costs.
| Model | Input | Output | Total / mo | vs Best |
|---|---|---|---|---|
| Trinity MiniCheapest | $0.05 | $0.08 | $0.12 | — |
| Nemotron 3 Nano 30B A3B | $0.05 | $0.10 | $0.15 | +25% |
Compare hosting configurations
Compare two exact setups, including different configurations of the same model. Hardware fit, measured speed and costs are separate decisions.
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Use hours for the same scenario period. Cloud billing includes idle time; active hours alone do not set the bill. Local electricity uses whole-system attributable power, powered hours and your tariff. Missing inputs remain unknown.
Measured speed needs the same pinned workload protocol, tokenizer, context, batching and cache state.
| Configuration | Run Nemotron 3 Nano on a 64 GiB Intel desktop | Run Trinity Mini on a 64 GiB Intel desktop |
|---|---|---|
| Model | Nemotron 3 Nano 30B A3B | Trinity Mini |
| Hardware | Intel Core i5-12400 desktop, 8 inference threads, 64 GiB RAM | Intel Core i5-12400 desktop, 8 inference threads, 64 GiB RAM |
| Runtime | llama.cpp v0.7.0 (620d2225cc436ab0b001e3200e590e3b286ef9ab) · CPU | llama.cpp v0.7.0 (620d2225cc436ab0b001e3200e590e3b286ef9ab) · CPU |
| Artifact | Nemotron-3-Nano-30B-A3B Q4_K_M · GGUF Q4_K_M mixed quantization · Q4_K_M mixed quantization by Unsloth | Trinity Mini Q4_K_M, publisher GGUF · GGUF Q4_K_M mixed quantization · Q4_K_M GGUF quantization published by Arcee AI |
| Context / concurrency | 4,096 tokens / 1 | 8,192 tokens / 1 |
| Required memory | Unknown (unknown) | Unknown (unknown) |
| Evidence | Documented setup | Documented setup |
| Hardware fit | Hardware fit unknown No exact peak for Nemotron hybrid MoE/Mamba Q4_K_M configuration. Enter available memory per device or unified memory pool. Host RAM: 64 GiB is chosen host capacity, not a measured minimum. Free disk space: 80 GiB is an author free/root disk allocation, not measured disk minimum. | Hardware fit unknown No full-process memory peak is measured for this exact Trinity Mini Q4_K_M and CPU context configuration. Enter available memory per device or unified memory pool. Host RAM: 64 GiB is chosen host capacity, not a measured minimum. Free disk space: 80 GiB is an author free/root disk allocation, not measured disk minimum. |
| One-time cost | Unknown hardware: Existing desktop purchase price and incremental hardware cost depend on the reader; unknown. setup: Initial provisioning/build time and labor cost are unknown. | Unknown hardware: Existing desktop purchase price and incremental hardware cost depend on the reader; unknown. setup: Initial provisioning/build time and labor cost are unknown. |
| Recurring scenario cost | Unknown electricity: Actual wall power, electricity rate and powered hours are unknown; no TDP-to-wall-power conversion. storage: Incremental cost of local disk capacity is unknown. The 80 GiB free-disk walkthrough allocation is an author choice, not a measured requirement. egress: Data transfer price, allowances and traffic volume are unknown. administration: Maintenance labor rate and hours are unknown. One-time setup and recurring costs are separate. Unknown components are not treated as free. No monthly token output is inferred from peak throughput. | Unknown electricity: Actual wall power, electricity rate and powered hours are unknown; no TDP-to-wall-power conversion. storage: Incremental cost of local disk capacity is unknown. The 80 GiB free-disk walkthrough allocation is an author choice, not a measured requirement. egress: Data transfer price, allowances and traffic volume are unknown. administration: Maintenance labor rate and hours are unknown. One-time setup and recurring costs are separate. Unknown components are not treated as free. No monthly token output is inferred from peak throughput. |
| Published measurements (unranked) | No compatible measurement available | No compatible measurement available |
Different currencies and incomplete costs are not ranked. Model quality benchmarks remain on the model pages; they do not establish quality or speed for every deployment.
NVIDIA
Nemotron 3 Nano 30B A3B
Nemotron 3 Nano 30B A3B is a large language model from NVIDIA. Supports up to 262,144 token context window. Available from $0.05/M input tokens.
Arcee AI
Trinity Mini
Trinity Mini is a large language model from Arcee AI. Supports up to 131,072 token context window. Available from $0.04/M input tokens.
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