Model comparison
Llama 4 Scout vs Mixtral 8x7B
Llama 4 Scout and Mixtral 8x7B score almost the same on the Noometry Index (27.7 vs 27.1), so choose on price, context window or the category you care about most.
Last verified . 27 shared benchmarks.
Meta
Mistral AISummary
- They share 27 benchmarks with published results for both. Llama 4 Scout scores higher in 5 categories and Mixtral 8x7B in 3 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Llama 4 Scout leads 31.9 to 11.0.
- The biggest single-benchmark swing is MATH Level 5: 62.3% for Llama 4 Scout and 10% for Mixtral 8x7B.
- Llama 4 Scout is cheaper at $0.10 / $0.30 per million input/output tokens, against $0.70 / $0.70 for Mixtral 8x7B.
- Llama 4 Scout accepts more context: 128K tokens versus 32K.
Side by side
| Llama 4 Scout | Mixtral 8x7B | |
|---|---|---|
| Provider | Meta | Mistral AI |
| Noometry Index | 27.7 | 27.1 |
| Released | 2025-04-05 | 2023-12-11 |
| Weights | Open | Open |
| Context window | 128K | 32K |
| Max output | 4K | 32K |
| Input $ / M tokens | $0.10 | $0.70 |
| Output $ / M tokens | $0.30 | $0.70 |
| Results tracked | 43 | 38 |
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Category by category
Coding Mixtral 8x7B leads
Llama 4 Scout: 20.2 (#339), Mixtral 8x7B: 32.8 (#269)
| Benchmark | Llama 4 Scout | Mixtral 8x7B |
|---|---|---|
| LMArena Coding | 1286 | 1126 |
| SWE-bench Verified (bash only) | 9.1% | — |
| SciCode | 17% | — |
| BigCodeBench Complete | 43.1% | — |
| HumanEval+ | — | 39.6% |
| MBPP+ | — | 49.7% |
Agentic & Tool Use Not comparable
Llama 4 Scout: 24.6 (#119), Mixtral 8x7B: —
| Benchmark | Llama 4 Scout | Mixtral 8x7B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 28.1% | — |
Reasoning Mixtral 8x7B leads
Llama 4 Scout: 9.1 (#345), Mixtral 8x7B: 18.2 (#285)
| Benchmark | Llama 4 Scout | Mixtral 8x7B |
|---|---|---|
| LMArena Hard Prompts | 1266 | 1115 |
| DTBench | 57.9% | 49.6% |
| Epoch Capabilities Index | 129.64 | 118.47 |
| ForecastBench | 57.5 | 56.3 |
| ARC-AGI-2 | 0% | — |
| Kagi LLM Benchmark | 36.9% | — |
| ARC-AGI-1 | 0.5% | — |
| CritPt | 0% | — |
| LMCA | 12% | — |
| Adversarial NLI | — | 55.2% |
| HellaSwag | — | 86.7% |
| PIQA | — | 83.6% |
| WinoGrande | — | 77.2% |
Math Too close to call
Llama 4 Scout: 19.6 (#286), Mixtral 8x7B: 18.8 (#289)
| Benchmark | Llama 4 Scout | Mixtral 8x7B |
|---|---|---|
| Omni-MATH | 37.3% | 10.5% |
| LMArena Math | 1287 | 1147 |
| MATH Level 5 | 62.3% | 10% |
| OTIS Mock AIME 2024-2025 | 7.8% | — |
| FrontierMath (Feb 2025 set) | 0% | — |
| GSM8K | — | 74.4% |
Knowledge Llama 4 Scout leads
Llama 4 Scout: 31.9 (#217), Mixtral 8x7B: 11.0 (#301)
| Benchmark | Llama 4 Scout | Mixtral 8x7B |
|---|---|---|
| GPQA Diamond | 51.8% | 30.6% |
| MMLU-Pro | 74.2% | 33.5% |
| GPQA (HELM) | 50.7% | 29.6% |
| LMArena Expert | 1235 | 1088 |
| Vectara Hallucination Rate | 7.7% | — |
| ARC (AI2) Challenge | — | 87.3% |
| MMLU | — | 70.6% |
| OpenBookQA | — | 85.8% |
| TriviaQA | — | 82.2% |
Multimodal Not comparable
Llama 4 Scout: 32.2 (#102), Mixtral 8x7B: —
| Benchmark | Llama 4 Scout | Mixtral 8x7B |
|---|---|---|
| LMArena Vision | 1118 | — |
| SpatialViz-Bench | 34.2% | — |
Multilingual Llama 4 Scout leads
Llama 4 Scout: 41.0 (#212), Mixtral 8x7B: 29.6 (#266)
| Benchmark | Llama 4 Scout | Mixtral 8x7B |
|---|---|---|
| LMArena Non-English | 1252 | 1077 |
| LMArena Chinese | 1255 | 1055 |
| LMArena French | 1282 | 1166 |
| LMArena German | 1272 | 1114 |
| LMArena Japanese | 1206 | 931 |
| LMArena Korean | 1207 | 968 |
| LMArena Russian | 1263 | 1090 |
| LMArena Spanish | 1278 | 1111 |
Instruction Following Llama 4 Scout leads
Llama 4 Scout: 65.8 (#217), Mixtral 8x7B: 51.0 (#297)
| Benchmark | Llama 4 Scout | Mixtral 8x7B |
|---|---|---|
| IFEval | 81.8% | 57.5% |
| LMArena Instruction Following | 1248 | 1109 |
Long Context Mixtral 8x7B leads
Llama 4 Scout: 27.5 (#294), Mixtral 8x7B: 33.4 (#260)
| Benchmark | Llama 4 Scout | Mixtral 8x7B |
|---|---|---|
| LMArena Longer Query | 1265 | 1103 |
| Fiction.LiveBench | 36% | — |
Writing & Preference Llama 4 Scout leads
Llama 4 Scout: 37.0 (#261), Mixtral 8x7B: 34.2 (#270)
| Benchmark | Llama 4 Scout | Mixtral 8x7B |
|---|---|---|
| LMArena Text | 1279 | 1132 |
| LMArena Creative Writing | 1249 | 1109 |
| WildBench | 78% | 67.3% |
| LMArena Multi-Turn | 1280 | 1115 |
| EQ-Bench Creative Writing | 783 | — |
Frequently asked questions
Is Llama 4 Scout better than Mixtral 8x7B?
Llama 4 Scout and Mixtral 8x7B score almost the same on the Noometry Index (27.7 vs 27.1), so choose on price, context window or the category you care about most.
Which is cheaper, Llama 4 Scout or Mixtral 8x7B?
Llama 4 Scout is cheaper. It lists at $0.10 per million input tokens and $0.30 per million output tokens; Mixtral 8x7B lists at $0.70 and $0.70.
Is Llama 4 Scout or Mixtral 8x7B better for coding?
Mixtral 8x7B scores higher on coding benchmarks: 32.8 versus 20.2 in the Noometry coding category.
Which has the bigger context window?
Llama 4 Scout does, with 128K tokens against 32K.
How many benchmarks do Llama 4 Scout and Mixtral 8x7B share?
27 benchmarks have published results for both models. Llama 4 Scout has 43 scored results on Noometry and Mixtral 8x7B has 38.