GPT-5.5 vs Mistral Large
Pricing, benchmarks, and use case comparison
Quick take
- •GPT-5.5 is meaningfully stronger at long context (93 vs 70 on our capability index).
- •Mistral Large is 60% cheaper on input tokens, which compounds fast on high-volume or agentic workloads.
- •Mistral Large has a 128000 context window vs 1,050,000 tokens (128,000 max output) - better for whole-repo or long-document work.
Specs comparison
| GPT-5.5 | Mistral Large | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Type | Closed source | Closed source |
| Context window | 1,050,000 tokens (128,000 max output) | ✓128000 |
| Input / 1M tokens | $5.00 | ✓2.00 |
| Output / 1M tokens | $30.00 | 6.00 |
| Release date | 2026-04 | 2024-02 |
Benchmarks
| Benchmark | GPT-5.5 | Mistral Large |
|---|---|---|
| SWE-bench Verified | 82.6% | - |
| SWE-bench Pro | 58.6% | - |
| MMLU | - | 84.0% |
| HumanEval | - | 92.0% |
Scores sourced from official provider release posts and independent benchmark aggregators.
Which should you choose?
Choose GPT-5.5 if...
- →Complex professional coding, data analysis, and multi-tool agentic workflows
- →Long-document or large-codebase tasks needing a 1M+ context window
- →You want OpenAI's recommended default frontier model for new projects
Choose Mistral Large if...
- →You need a strong European-built flagship with open weights
- →Your work is multilingual or requires nuanced reasoning
- →You want structured/JSON output and solid coding ability
- →You need the option to self-host for data sovereignty