Mistral AI, released Oct 6, 2026
Mistral Large 4price, context, benchmarks and release details
- Input, per 1M tokens
- $0.68Mistral API pricingOfficial Mistral Serverless API Standard rate, displayed sale price where applicable; cache, Batch, specialist units and hosted third-party models excluded
Retrieved Oct 9, 2026 · factual citation
Open source ↗ - Output, per 1M tokens
- $2.09Mistral API pricingOfficial Mistral Serverless API Standard rate, displayed sale price where applicable; cache, Batch, specialist units and hosted third-party models excluded
Retrieved Oct 9, 2026 · factual citation
Open source ↗ - Context window
- 1Mmodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Max output
- 262Kmodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Released
- Oct 6, 2026models.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗
How the score breaks down
Weights: reasoning 30%, math 15%, coding 40%, preference 15%. Results use fixed 0–100 scales before averaging, and thin evidence is pulled toward 50. Method si-v3-retained-evidence-2, computed Oct 9, 2026, 05:13 UTC.
Around it on the leaderboard
- 51 MiMo-V2.5-Pro 62.6
- 52 Muse Spark 1.2 62.3
- 53 Mistral Large 4 62.2
- 54 Qwen3.8 27B 61.9
- 55 GPT-6 Luna 61.6
Benchmark results
17 benchmarks, 17 resultsEach row shows the best published result. Where a model was tested at several settings, such as reasoning effort, open the row to see each one. Hover or tap a value for its source.
Open source ↗ 48.0
Open source ↗ 80.5
Open source ↗ 68.0
Open source ↗ 94.0
Open source ↗ 80.8
Open source ↗ 93.0
Open source ↗ 98.0
Open source ↗ 97.1
Open source ↗ 90.0
Open source ↗ 89.3
Open source ↗ 66.2
Open source ↗ 78.3
Open source ↗ 76.1
Open source ↗ 68.2
Open source ↗ 60.0
Open source ↗ 43.3
Open source ↗ 75.7
Normalization uses a fixed 0–100 scale for each unit, independent of other models. Compare evaluation conditions before reading a small gap as decisive. “Lab-reported” marks the provider's own published figure.
Details and sources
- Open weights
- Nomodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - License
- not yet reported
- Input modalities
- text, imagemodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - First seen by SuperIndex
- Oct 8, 2026
- Coverage
- 51% of expected source weight
Reported (2)
- LiveBenchOct 8, 2026
- LMArena / ArenaOct 9, 2026
Awaiting (4)
- ARC Prize17% of weight
- Humanity’s Last Exam17% of weight
- Official model cards via models.dev6% of weight
- Terminal-Bench9% of weight
Confidence rises as pending sources publish. Some sources never cover some models, so confidence reaches 100% at 80% of expected weight.