# Grok 4.20 Multi-Agent vs Mistral Large

> Grok 4.20 Multi-Agent is the stronger model overall, scoring 46.2 to 31.9 on the Noometry Index.

- Canonical page: https://noometry.com/compare/grok-4-20-multi-agent-vs-mistral-large
- Last updated: 2026-10-12
- Shared benchmarks: 17

## Summary

- They share 17 benchmarks with published results for both. Grok 4.20 Multi-Agent scores higher in 8 categories and Mistral Large in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Grok 4.20 Multi-Agent leads 43.9 to 15.8.
- Grok 4.20 Multi-Agent is cheaper at $1.25 / $2.50 per million input/output tokens, against $2 / $6 for Mistral Large.
- Grok 4.20 Multi-Agent accepts more context: 1M tokens versus 131K.
- Mistral Large has downloadable open weights; the other is API-only.

## Snapshot

| | Grok 4.20 Multi-Agent | Mistral Large |
|---|---|---|
| Provider | xAI | Mistral AI |
| Noometry Index | 46.2 | 31.9 |
| Rank | 65 | 263 |
| Context | 1M | 131K |
| Input $/M | $1.25 | $2 |
| Output $/M | $2.50 | $6 |
| Weights | Proprietary | Open |

## Coding

- Grok 4.20 Multi-Agent: 43.0 (#92)
- Mistral Large: 34.3 (#240)

| Benchmark | Grok 4.20 Multi-Agent | Mistral Large |
|---|---|---|
| LMArena Coding | 1457 | 1277 |
| SciCode | — | 36.2% |
| BigCodeBench Instruct | — | 30% |
| LiveBench Coding | — | 47.1% |
| BigCodeBench Complete | — | 38.3% |
| ALE-Bench | — | 264.7 |
| HumanEval+ | — | 62.2% |
| MBPP+ | — | 59.5% |

## Agentic & Tool Use

- Grok 4.20 Multi-Agent: —
- Mistral Large: 28.6 (#89)

| Benchmark | Grok 4.20 Multi-Agent | Mistral Large |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 38.4% |
| LMArena Search | 1204 | — |

## Reasoning

- Grok 4.20 Multi-Agent: 43.9 (#48)
- Mistral Large: 15.8 (#310)

| Benchmark | Grok 4.20 Multi-Agent | Mistral Large |
|---|---|---|
| LMArena Hard Prompts | 1448 | 1257 |
| SimpleBench | — | 22.5% |
| NYT Connections (extended) | 89.6% | — |
| CritPt | — | 0% |
| LiveBench Reasoning | — | 43.5% |
| DTBench | — | 65.1% |
| LiveBench Data Analysis | — | 50.1% |
| LMCA | — | 16.7% |
| Epoch Capabilities Index | — | 128.52 |
| ForecastBench | — | 57.1 |
| LiveBench | — | 48.4% |

## Math

- Grok 4.20 Multi-Agent: 39.4 (#104)
- Mistral Large: 18.2 (#291)

| Benchmark | Grok 4.20 Multi-Agent | Mistral Large |
|---|---|---|
| LMArena Math | 1442 | 1262 |
| OTIS Mock AIME 2024-2025 | — | 8.5% |
| Omni-MATH | — | 28.1% |
| LiveBench Math | — | 42.5% |
| MATH Level 5 | — | 50.3% |
| FrontierMath (Feb 2025 set) | — | 0.3% |

## Knowledge

- Grok 4.20 Multi-Agent: 40.4 (#119)
- Mistral Large: 30.1 (#230)

| Benchmark | Grok 4.20 Multi-Agent | Mistral Large |
|---|---|---|
| LMArena Expert | 1445 | 1232 |
| GPQA Diamond | — | 51.3% |
| MMLU-Pro | — | 59.9% |
| Confabulations | — | 21.4% |
| Vectara Hallucination Rate | — | 4.5% |
| GPQA (HELM) | — | 43.5% |
| MMLU | — | 80% |

## Multimodal

- Grok 4.20 Multi-Agent: 40.5 (#48)
- Mistral Large: —

| Benchmark | Grok 4.20 Multi-Agent | Mistral Large |
|---|---|---|
| LMArena Vision | 1259 | — |

## Multilingual

- Grok 4.20 Multi-Agent: 54.4 (#43)
- Mistral Large: 40.0 (#219)

| Benchmark | Grok 4.20 Multi-Agent | Mistral Large |
|---|---|---|
| LMArena Non-English | 1440 | 1237 |
| LMArena Chinese | 1475 | 1240 |
| LMArena French | 1466 | 1325 |
| LMArena German | 1456 | 1254 |
| LMArena Japanese | 1405 | 1188 |
| LMArena Korean | 1416 | 1202 |
| LMArena Russian | 1457 | 1257 |
| LMArena Spanish | 1447 | 1268 |

## Instruction Following

- Grok 4.20 Multi-Agent: 74.8 (#84)
- Mistral Large: 67.9 (#191)

| Benchmark | Grok 4.20 Multi-Agent | Mistral Large |
|---|---|---|
| LMArena Instruction Following | 1420 | 1249 |
| LiveBench Instruction Following | — | 67.9% |
| IFEval | — | 87.7% |

## Long Context

- Grok 4.20 Multi-Agent: 43.7 (#88)
- Mistral Large: 38.3 (#199)

| Benchmark | Grok 4.20 Multi-Agent | Mistral Large |
|---|---|---|
| LMArena Longer Query | 1431 | 1261 |

## Writing & Preference

- Grok 4.20 Multi-Agent: 64.0 (#59)
- Mistral Large: 40.7 (#242)

| Benchmark | Grok 4.20 Multi-Agent | Mistral Large |
|---|---|---|
| LMArena Text | 1450 | 1266 |
| LMArena Creative Writing | 1436 | 1243 |
| LMArena Multi-Turn | 1452 | 1260 |
| Short-Story Creative Writing | — | 69% |
| EQ-Bench Creative Writing | — | 985 |
| WildBench | — | 80.1% |
| LiveBench Language | — | 39.4% |

## FAQ

### Is Grok 4.20 Multi-Agent better than Mistral Large?

Grok 4.20 Multi-Agent is the stronger model overall, scoring 46.2 to 31.9 on the Noometry Index.

### Which is cheaper, Grok 4.20 Multi-Agent or Mistral Large?

Grok 4.20 Multi-Agent is cheaper. It lists at $1.25 per million input tokens and $2.50 per million output tokens; Mistral Large lists at $2 and $6.

### Is Grok 4.20 Multi-Agent or Mistral Large better for coding?

Grok 4.20 Multi-Agent scores higher on coding benchmarks: 43.0 versus 34.3 in the Noometry coding category.

### Which has the bigger context window?

Grok 4.20 Multi-Agent does, with 1M tokens against 131K.

### How many benchmarks do Grok 4.20 Multi-Agent and Mistral Large share?

17 benchmarks have published results for both models. Grok 4.20 Multi-Agent has 20 scored results on Noometry and Mistral Large has 51.