# Llama 4 Maverick vs Mistral Medium 3.5

> Mistral Medium 3.5 is the stronger model overall, scoring 39.6 to 30.6 on the Noometry Index. Llama 4 Maverick costs 9.9× less per token, which makes it the better buy when Mistral Medium 3.5's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/llama-4-maverick-vs-mistral-medium-3-5
- Last updated: 2026-10-10
- Shared benchmarks: 20

## Summary

- They share 20 benchmarks with published results for both. Llama 4 Maverick scores higher in 0 categories and Mistral Medium 3.5 in 9 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Mistral Medium 3.5 leads 58.6 to 39.0.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 55.9% for Llama 4 Maverick and 41.4% for Mistral Medium 3.5.
- Llama 4 Maverick is cheaper at $0.19 / $0.65 per million input/output tokens, against $1.50 / $7.50 for Mistral Medium 3.5.
- Mistral Medium 3.5 accepts more context: 262K tokens versus 128K.

## Snapshot

| | Llama 4 Maverick | Mistral Medium 3.5 |
|---|---|---|
| Provider | Meta | Mistral AI |
| Noometry Index | 30.6 | 39.6 |
| Rank | 276 | 151 |
| Context | 128K | 262K |
| Input $/M | $0.19 | $1.50 |
| Output $/M | $0.65 | $7.50 |
| Weights | Open | Open |

## Coding

- Llama 4 Maverick: 26.3 (#318)
- Mistral Medium 3.5: 35.7 (#208)

| Benchmark | Llama 4 Maverick | Mistral Medium 3.5 |
|---|---|---|
| LMArena Coding | 1302 | 1461 |
| SWE-bench Verified (bash only) | 21% | — |
| Aider Polyglot | 15.6% | — |
| LMArena WebDev | — | 1263 |
| SciCode | 33.1% | — |
| WeirdML | 24.5% | — |
| BigCodeBench Instruct | 49.7% | — |
| BigCodeBench Complete | 61.4% | — |
| ALE-Bench | 172.97 | — |

## Agentic & Tool Use

- Llama 4 Maverick: 27.9 (#86)
- Mistral Medium 3.5: —

| Benchmark | Llama 4 Maverick | Mistral Medium 3.5 |
|---|---|---|
| Berkeley Function Calling Leaderboard | 37.3% | — |

## Reasoning

- Llama 4 Maverick: 10.1 (#337)
- Mistral Medium 3.5: 16.6 (#290)

| Benchmark | Llama 4 Maverick | Mistral Medium 3.5 |
|---|---|---|
| Kagi LLM Benchmark | 55.9% | 41.4% |
| NYT Connections (extended) | 8% | 12.9% |
| LMArena Hard Prompts | 1281 | 1436 |
| Epoch Capabilities Index | 132.2 | 141.42 |
| ARC-AGI-2 | 0% | — |
| SimpleBench | 27.7% | — |
| ARC-AGI-1 | 4.4% | — |
| CritPt | 0% | — |
| EnigmaEval | 0.6% | — |
| DTBench | 61.9% | — |
| LMCA | 15.9% | — |
| ForecastBench | 57.5 | — |

## Math

- Llama 4 Maverick: 24.6 (#256)
- Mistral Medium 3.5: 36.4 (#113)

| Benchmark | Llama 4 Maverick | Mistral Medium 3.5 |
|---|---|---|
| LMArena Math | 1299 | 1432 |
| OTIS Mock AIME 2024-2025 | 20.6% | — |
| Omni-MATH | 42.2% | — |
| MATH Level 5 | 73% | — |
| FrontierMath (Feb 2025 set) | 0.7% | — |

## Knowledge

- Llama 4 Maverick: 33.3 (#196)
- Mistral Medium 3.5: 39.3 (#123)

| Benchmark | Llama 4 Maverick | Mistral Medium 3.5 |
|---|---|---|
| LMArena Expert | 1259 | 1431 |
| GPQA Diamond | 67% | — |
| Humanity's Last Exam | 5.7% | — |
| MMLU-Pro | 81% | — |
| Confabulations | 22.6% | — |
| Vectara Hallucination Rate | 8.2% | — |
| GPQA (HELM) | 65% | — |

## Multimodal

- Llama 4 Maverick: 30.9 (#100)
- Mistral Medium 3.5: 37.6 (#64)

| Benchmark | Llama 4 Maverick | Mistral Medium 3.5 |
|---|---|---|
| LMArena Vision | 1141 | 1222 |
| GeoBench | 52% | — |
| SpatialViz-Bench | 31.8% | — |

## Multilingual

- Llama 4 Maverick: 42.4 (#190)
- Mistral Medium 3.5: 52.1 (#93)

| Benchmark | Llama 4 Maverick | Mistral Medium 3.5 |
|---|---|---|
| LMArena Non-English | 1269 | 1405 |
| LMArena Chinese | 1277 | 1443 |
| LMArena French | 1258 | 1448 |
| LMArena German | 1291 | 1453 |
| LMArena Korean | 1203 | 1387 |
| LMArena Russian | 1286 | 1396 |
| LMArena Spanish | 1293 | 1406 |
| LMArena Japanese | 1207 | — |

## Instruction Following

- Llama 4 Maverick: 71.9 (#140)
- Mistral Medium 3.5: 74.7 (#87)

| Benchmark | Llama 4 Maverick | Mistral Medium 3.5 |
|---|---|---|
| LMArena Instruction Following | 1267 | 1414 |
| IFEval | 90.8% | — |

## Long Context

- Llama 4 Maverick: 31.4 (#274)
- Mistral Medium 3.5: 43.2 (#101)

| Benchmark | Llama 4 Maverick | Mistral Medium 3.5 |
|---|---|---|
| LMArena Longer Query | 1280 | 1414 |
| Fiction.LiveBench | 46.2% | — |

## Writing & Preference

- Llama 4 Maverick: 39.0 (#247)
- Mistral Medium 3.5: 58.6 (#113)

| Benchmark | Llama 4 Maverick | Mistral Medium 3.5 |
|---|---|---|
| LMArena Text | 1287 | 1421 |
| LMArena Creative Writing | 1266 | 1372 |
| LMArena Multi-Turn | 1289 | 1423 |
| Short-Story Creative Writing | 62% | — |
| EQ-Bench Creative Writing | 860 | — |
| WildBench | 80% | — |
| EQ-Bench 4 | — | 993 |

## FAQ

### Is Llama 4 Maverick better than Mistral Medium 3.5?

Mistral Medium 3.5 is the stronger model overall, scoring 39.6 to 30.6 on the Noometry Index. Llama 4 Maverick costs 9.9× less per token, which makes it the better buy when Mistral Medium 3.5's lead doesn't matter for your workload.

### Which is cheaper, Llama 4 Maverick or Mistral Medium 3.5?

Llama 4 Maverick is cheaper. It lists at $0.19 per million input tokens and $0.65 per million output tokens; Mistral Medium 3.5 lists at $1.50 and $7.50.

### Is Llama 4 Maverick or Mistral Medium 3.5 better for coding?

Mistral Medium 3.5 scores higher on coding benchmarks: 35.7 versus 26.3 in the Noometry coding category.

### Which has the bigger context window?

Mistral Medium 3.5 does, with 262K tokens against 128K.

### How many benchmarks do Llama 4 Maverick and Mistral Medium 3.5 share?

20 benchmarks have published results for both models. Llama 4 Maverick has 54 scored results on Noometry and Mistral Medium 3.5 has 22.