LLM Comparison
GPT-5.6 Sol vs Jamba Large 1.7
Side-by-side specs, pricing & capabilities
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2/6 modelsSame tier:
| Organization | ||
| OpenTools Score | 85 7.0 | |
| Family | GPT-5.6 | Jamba |
| Status | Current | Current |
| Release Date | Jul 2026 | Aug 2025 |
| Context Window | 1.1M tokens | 256K tokens |
| Input Price | $4.00/M tokens | $2.00/M tokens |
| Output Price | $20.00/M tokens | $8.00/M tokens |
| Pricing Notes | OpenAI promotional standard short-context pricing is $4 input, $0.40 cached input, $5 cache writes, and $20 output per 1M tokens through at least November 21, 2026. Standard long-context pricing is $8 input, $0.80 cached input, $10 cache writes, and $30 output; Batch, Flex, and Fast mode use separate rates. | — |
| Capabilities | textvisionreasoningcodingtool-useweb-searchfile-searchcomputer-useagents | textcode |
| Training Cutoff | Feb 16, 2026 | — |
| Max Output | 128K tokens | 4K tokens |
| API Identifier | gpt-5.6-sol | ai21/jamba-large-1.7 |
| Benchmarks | ||
| Artificial Analysis Intelligence Index v4.3 | 47.1 indexartificial-analysis | — |
| Artificial Analysis Intelligence Index v4.3 | 47 indexhttps://artificialanalysis.ai/models/gpt-5-6-sol | — |
| GPQA Diamond | 94.1%artificial-analysis | — |
| SciCode | 57.1%artificial-analysis | — |
| Terminal-Bench 2.1 | 88%artificial-analysis | — |
| View GPT-5.6 Sol | View Jamba Large 1.7 | |
Cost Calculator
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| Model | Input | Output | Total / mo | vs Best |
|---|---|---|---|---|
| Jamba Large 1.7Cheapest | $2.00 | $4.00 | $6.00 | — |
| GPT-5.6 Sol | $4.00 | $10.00 | $14.00 | +133% |
OpenAI
GPT-5.6 Sol
GPT-5.6 Sol is OpenAI frontier GPT-5.6 model for complex professional work across coding, knowledge work, science, cybersecurity, and agentic workflows. OpenAI model docs list it as the GPT-5.6 alias target with function, web search, file search, and computer use tools, 1.05M context, and 128K max output.
AI21 Labs
Jamba Large 1.7
Jamba Large 1.7 is a large language model from AI21 Labs. Supports up to 256,000 token context window. Available from $2.00/M input tokens.
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