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o4-mini vs Mistral Large 3
A detailed comparison of o4-mini (OpenAI) and Mistral Large 3 (Mistral) across pricing, performance, and features.
Pricing Comparison
| Metric | o4-mini | Mistral Large 3 | Difference |
|---|---|---|---|
| Input / 1M tokens | $1.10 | $2.00 | +82% |
| Output / 1M tokens | $4.40 | $5.00 | +14% |
| Context window | 200K | 128K | — |
| Max output | 100K | 16.384K | — |
Benchmark Comparison
| Benchmark | o4-mini | Mistral Large 3 |
|---|---|---|
| MMLU-Pro | 85% | 83% |
| HumanEval | 93.5% | 91% |
| GPQA | 76% | — |
Capabilities
| Capability | o4-mini | Mistral Large 3 |
|---|---|---|
| code | ✓ | ✓ |
| reasoning | ✓ | ✓ |
| text | ✓ | ✓ |
| tool-use | ✓ | ✓ |
| vision | ✓ | ✓ |
o4-mini Strengths
- ✓Affordable reasoning model
- ✓200K context window
- ✓Good for math and science
o4-mini Weaknesses
- ✗Slower than non-reasoning models
- ✗Reasoning tokens add to effective cost
Mistral Large 3 Strengths
- ✓Low output cost ($5/1M) for a flagship
- ✓Strong multilingual support
- ✓European data sovereignty option
Mistral Large 3 Weaknesses
- ✗Lower benchmarks than top-tier competitors
- ✗Smaller ecosystem
Quick Verdict
Best value: o4-mini is the more affordable option at $1.1/$4.4 per 1M tokens.
Higher benchmarks: Mistral Large 3 scores higher on average across available benchmarks (87.0% avg).
Larger context: o4-mini supports 200K tokens.
Choose o4-mini if cost matters most. Choose Mistral Large 3 if you need the best possible quality for complex tasks.