Mistral Large vs o1
2026 - Pricing, benchmarks, and use case comparison
Quick take
- •Mistral Large is 80% cheaper on input tokens - better for high-volume workloads.
- •o1 has a 200K context window - 2x larger than Mistral Large's 128K. Better for long documents and large codebases.
Specs comparison
| Mistral Large | o1 | |
|---|---|---|
| Provider | Mistral AI | OpenAI |
| Type | Closed source | Closed source |
| Context window | 128K | ✓200K |
| Input / 1M tokens | ✓$3.00 | $15.00 |
| Output / 1M tokens | $9.00 | $60.00 |
| Release date | 2024-07 | 2024-09 |
Benchmarks
| Benchmark | Mistral Large | o1 |
|---|---|---|
| MMLU | 84.0% | - |
| HumanEval | 92.0% | 92.4% |
| GPQA Diamond | - | 78.3% |
| SWE-bench Verified | - | 48.9% |
Scores sourced from official provider release posts.
Strengths
Mistral Large
- ✓Native multilingual support across 12+ languages
- ✓Reliable function calling and tool use
- ✓Strong coding across 80+ programming languages
- ✓EU-based inference for data compliance
- ✓128K context at competitive pricing
o1
- ✓Best-in-class math and physics
- ✓Strong competitive coding (Codeforces, HumanEval)
- ✓Scientific reasoning (GPQA top performer)
- ✓Multi-step logic and planning
- ✓200K context for long technical documents
Which should you choose?
Choose Mistral Large if you need...
- →Multilingual European deployments
- →Tool-calling and agentic pipelines
- →Code generation and review
- →GDPR-compliant AI applications
Choose o1 if you need...
- →Math and science problems
- →Competitive programming
- →Complex multi-step reasoning
- →Research assistance