Model comparison
Llama 4 Scout vs Mistral Medium 3.1
Mistral Medium 3.1 is the stronger model overall, scoring 31.5 to 27.4 on the Noometry Index. Llama 4 Scout costs 5.3× less per token, which makes it the better buy when Mistral Medium 3.1's lead doesn't matter for your workload.
Last verified . 1 shared benchmarks.
Meta
Mistral AISummary
- They share 1 benchmark with published results for both. Llama 4 Scout scores higher in 0 categories and Mistral Medium 3.1 in 2 categories; one gap is clear of the uncertainty.
- The widest gap is in writing & preference, where Mistral Medium 3.1 leads 55.6 to 37.1.
- Llama 4 Scout is cheaper at $0.10 / $0.30 per million input/output tokens, against $0.40 / $2 for Mistral Medium 3.1.
- Mistral Medium 3.1 accepts more context: 131K tokens versus 128K.
- Llama 4 Scout has downloadable open weights; the other is API-only.
Side by side
| Llama 4 Scout | Mistral Medium 3.1 | |
|---|---|---|
| Provider | Meta | Mistral AI |
| Noometry Index | 27.4 | 31.5 |
| Released | 2025-04-05 | — |
| Weights | Open | Proprietary |
| Context window | 128K | 131K |
| Max output | 4K | 105K |
| Input $ / M tokens | $0.10 | $0.40 |
| Output $ / M tokens | $0.30 | $2 |
| Results tracked | 43 | 3 |
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Category by category
Coding Not comparable
Llama 4 Scout: 19.9 (#334), Mistral Medium 3.1: —
| Benchmark | Llama 4 Scout | Mistral Medium 3.1 |
|---|---|---|
| SWE-bench Verified (bash only) | 9.1% | — |
| SciCode | 17% | — |
| LMArena Coding | 1286 | — |
| BigCodeBench Complete | 43.1% | — |
Agentic & Tool Use Not comparable
Llama 4 Scout: 24.4 (#109), Mistral Medium 3.1: —
| Benchmark | Llama 4 Scout | Mistral Medium 3.1 |
|---|---|---|
| Berkeley Function Calling Leaderboard | 28.1% | — |
Reasoning Too close to call
Llama 4 Scout: 9.2 (#339), Mistral Medium 3.1: 10.1 (#336)
| Benchmark | Llama 4 Scout | Mistral Medium 3.1 |
|---|---|---|
| ARC-AGI-2 | 0% | — |
| Kagi LLM Benchmark | 36.9% | — |
| NYT Connections (extended) | — | 6.5% |
| ARC-AGI-1 | 0.5% | — |
| CritPt | 0% | — |
| Thematic Generalization | — | 20.3% |
| LMArena Hard Prompts | 1266 | — |
| DTBench | 57.9% | — |
| LMCA | 12% | — |
| Epoch Capabilities Index | 129.64 | — |
| ForecastBench | 57.5 | — |
Math Not comparable
Llama 4 Scout: 18.4 (#280), Mistral Medium 3.1: —
| Benchmark | Llama 4 Scout | Mistral Medium 3.1 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 7.8% | — |
| Omni-MATH | 37.3% | — |
| LMArena Math | 1286 | — |
| MATH Level 5 | 62.3% | — |
| FrontierMath (Feb 2025 set) | 0% | — |
Knowledge Not comparable
Llama 4 Scout: 31.8 (#208), Mistral Medium 3.1: —
| Benchmark | Llama 4 Scout | Mistral Medium 3.1 |
|---|---|---|
| GPQA Diamond | 51.8% | — |
| MMLU-Pro | 74.2% | — |
| Vectara Hallucination Rate | 7.7% | — |
| GPQA (HELM) | 50.7% | — |
| LMArena Expert | 1236 | — |
Multimodal Not comparable
Llama 4 Scout: 31.6 (#98), Mistral Medium 3.1: —
| Benchmark | Llama 4 Scout | Mistral Medium 3.1 |
|---|---|---|
| LMArena Vision | 1118 | — |
| SpatialViz-Bench | 34.2% | — |
Multilingual Not comparable
Llama 4 Scout: 41.3 (#207), Mistral Medium 3.1: —
| Benchmark | Llama 4 Scout | Mistral Medium 3.1 |
|---|---|---|
| LMArena Non-English | 1253 | — |
| LMArena Chinese | 1256 | — |
| LMArena French | 1283 | — |
| LMArena German | 1274 | — |
| LMArena Japanese | 1209 | — |
| LMArena Korean | 1207 | — |
| LMArena Russian | 1263 | — |
| LMArena Spanish | 1277 | — |
Instruction Following Not comparable
Llama 4 Scout: 66.0 (#212), Mistral Medium 3.1: —
| Benchmark | Llama 4 Scout | Mistral Medium 3.1 |
|---|---|---|
| IFEval | 81.8% | — |
| LMArena Instruction Following | 1248 | — |
Long Context Not comparable
Llama 4 Scout: 27.5 (#289), Mistral Medium 3.1: —
| Benchmark | Llama 4 Scout | Mistral Medium 3.1 |
|---|---|---|
| Fiction.LiveBench | 36% | — |
| LMArena Longer Query | 1265 | — |
Writing & Preference Mistral Medium 3.1 leads
Llama 4 Scout: 37.1 (#256), Mistral Medium 3.1: 55.6 (#140)
| Benchmark | Llama 4 Scout | Mistral Medium 3.1 |
|---|---|---|
| EQ-Bench Creative Writing | 783 | 1476 |
| LMArena Text | 1279 | — |
| LMArena Creative Writing | 1249 | — |
| WildBench | 78% | — |
| LMArena Multi-Turn | 1281 | — |
Frequently asked questions
Is Llama 4 Scout better than Mistral Medium 3.1?
Mistral Medium 3.1 is the stronger model overall, scoring 31.5 to 27.4 on the Noometry Index. Llama 4 Scout costs 5.3× less per token, which makes it the better buy when Mistral Medium 3.1's lead doesn't matter for your workload.
Which is cheaper, Llama 4 Scout or Mistral Medium 3.1?
Llama 4 Scout is cheaper. It lists at $0.10 per million input tokens and $0.30 per million output tokens; Mistral Medium 3.1 lists at $0.40 and $2.
Which has the bigger context window?
Mistral Medium 3.1 does, with 131K tokens against 128K.
How many benchmarks do Llama 4 Scout and Mistral Medium 3.1 share?
1 benchmark has published results for both models. Llama 4 Scout has 43 scored results on Noometry and Mistral Medium 3.1 has 3.