LLM Comparison
GPT-5.5 vs Mistral Small 4
Side-by-side specs, pricing & capabilities · Updated October 2026
Price vs Intelligence
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2/6 modelsSame tier:
| Organization | ||
| OpenTools Score | 85 4.9 | 17 44.3 |
| Family | GPT | Mistral |
| Status | Current | Current |
| Release Date | Apr 2026 | Mar 2026 |
| Context Window | 1.1M tokens | 262K tokens |
| Input Price | $5.00/M tokens | $0.15/M tokens |
| Output Price | $30.00/M tokens | $0.60/M tokens |
| Pricing Notes | Cached input: $0.50/M tokens. Long context (>272K tokens): 2x input, 1.5x output. Batch API: 50% discount. Priority: 2.5x standard. | Cache read: $0.0150/M tokens |
| Capabilities | textvisioncodetool-useextended-thinkingcomputer-useweb-search | textvisioncodetool-use |
| Training Cutoff | Dec 01, 2025 | — |
| Max Output | 128K tokens | — |
| API Identifier | openai/gpt-5.5 | mistralai/mistral-small-2603 |
| Benchmarks | ||
| MMLU | 92.4openai | — |
| GPQA Diamond | 93.6openai | 58.8mistral |
| ARC-AGI-2 | 85openai | — |
| Terminal-Bench 2.0 | 82.7openai | — |
| SWE-bench Pro | 58.6openai | — |
| OSWorld-Verified | 78.7openai | — |
| BrowseComp | 84.4openai | — |
| MMMU-Pro | 81.2openai | — |
| FrontierMath Tier 4 | 35.4openai | — |
| HLE (with tools) | 52.2openai | — |
| GDPval | 84.9openai | — |
| Toolathlon | 55.6openai | — |
| CyberGym | 81.8openai | — |
| MRCR v2 512K-1M | 74openai | — |
| Artificial Analysis Intelligence Index v4.3 | 38.6292artificial-analysis | 11.4511artificial-analysis |
| SciCode | 55.787artificial-analysis | 38.7731artificial-analysis |
| Terminal-Bench 2.1 | 84.2697artificial-analysis | 20.9738artificial-analysis |
| MMLU-Pro | — | 68.5mistral |
| HumanEval | — | 78.5mistral |
| MGSM | — | 72.3mistral |
| LiveCodeBench | — | 64mistral |
| View GPT-5.5 | View Mistral Small 4 | |
Cost Calculator
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| Model | Input | Output | Total / mo | vs Best |
|---|---|---|---|---|
| Mistral Small 4Cheapest | $0.15 | $0.30 | $0.45 | — |
| GPT-5.5 | $5.00 | $15.00 | $20.00 | +4344% |
OpenAI
GPT-5.5
GPT-5.5 is OpenAI's smartest and most intuitive model, built for agentic work like coding, research, and data analysis. It matches GPT-5.4 per-token latency while delivering higher intelligence with significantly fewer tokens. Supports a 1,050,000 token context window and five reasoning effort levels (none through xhigh).
Mistral AI
Mistral Small 4
Mistral Small 4 is Mistral's Apache-2.0 open-weight hybrid model for instruction following, reasoning, and coding. It has 119B total parameters, 6.5B active parameters, and a 256K-token context window.
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