Mistral Large vs o1
Pricing, benchmarks, and use case comparison
Quick take
- •Mistral Large is meaningfully stronger at speed (70 vs 30 on our capability index).
- •Mistral Large is 87% cheaper on input tokens, which compounds fast on high-volume or agentic workloads.
- •Mistral Large has a 128000 context window vs 200,000 tokens (100,000 max output) - better for whole-repo or long-document work.
Specs comparison
| Mistral Large | o1 | |
|---|---|---|
| Provider | Mistral AI | OpenAI |
| Type | Closed source | Closed source |
| Context window | ✓128000 | 200,000 tokens (100,000 max output) |
| Input / 1M tokens | ✓2.00 | $15.00 |
| Output / 1M tokens | 6.00 | $60.00 |
| Release date | 2024-02 | 2024-12 |
Benchmarks
| Benchmark | Mistral Large | o1 |
|---|---|---|
| MMLU | 84.0% | - |
| HumanEval | 92.0% | - |
| AIME 2024 | - | 74% |
| GPQA Diamond | - | 77.3% |
| Codeforces | - | ~89th percentile |
Scores sourced from official provider release posts and independent benchmark aggregators.
Which should you choose?
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
Choose o1 if...
- →Hard, multi-step math, science, and logic problems that reward deliberate reasoning
- →Competitive programming and algorithmic problem solving
- →Existing o1-based pipelines already validated for reasoning tasks