Multimodal · Mistral AI

Mistral Large 3 7B on MMMU: score, rank and what it means

Mistral Large 3 7B scores 58.8 on MMMU, placing it #443 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
58.8
0–100 scale
Rank
#443
of 600
Percentile
26th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
28.1
points

Score distribution

The chart shows the top 10 models on MMMU, with Mistral Large 3 7B highlighted. Longer bars mean higher scores.

GPT-5.2 Max 86.9
GPT-5.1 Reasoning 86.2
GPT-5.2 85.3
Claude Sonnet 4.5 Reasoning 85.2
GPT-5.1 Max 85.1
Grok 4 Pro 84.9
Claude Opus 4.5 Reasoning 84.6
Claude Sonnet 4.5 Pro 84.5
GPT-5.2 Pro 84.4
GPT-5.2 Vision 84.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
3 GPT-5.2 OpenAI 2000000 $19.71 88.0
4 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
5 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
6 Grok 4 Pro xAI 1000000 $19.00 85.4
7 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
8 Claude Sonnet 4.5 Pro Anthropic 1000000 $18.73 86.7
9 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
10 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4

What this score means

On MMMU, Mistral Large 3 7B sits at #443 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 28.1 points. The median model in this index scores 70.0, which puts Mistral Large 3 7B below the midpoint.

Mistral AI models average 64.8 on this benchmark. Mistral Large 3 7B is 6.0 points below that provider line, so it is a weaker result than the average Mistral AI model.

Among small open-weight models, the average is 52.4. Mistral Large 3 7B is 6.4 points above that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 58.8 as a relative signal, not an absolute guarantee. Benchmark scores depend on prompt format, evaluation harness and contamination controls. Use this page to narrow the shortlist, then test the model on your own data.

Price context

At $1.44 per million input tokens, Mistral Large 3 7B is below the median input price of $4.00 across the 600 models scored on MMMU. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Llama 3.3 7B Meta AI 8192 $1.18 57.8
MiniMax-M2 8B MiniMax 32768 $1.65 61.7
Hunyuan-Large 8B Tencent 4096 $1.29 58.7
MiniMax-M2 7B MiniMax 8192 $1.44 60.8
Mistral Large 3 7B Mistral AI 32768 $1.44 61.1
Qwen3-Coder 8B Alibaba Cloud 32768 $1.43 61.3
Reka Flash Nano Reka AI 16384 $3.93 61.0

Other benchmarks for Mistral Large 3 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 65.6 444 26th
GPQA Diamond 55.9 450 25th
SWE-bench Verified 49.1 428 29th
HumanEval 66.1 430 28th
MATH-500 63.2 434 28th
AIME 2025 52.3 442 26th
LiveCodeBench 52.6 419 30th
IFEval 68.9 476 21th
TruthfulQA 64.4 466 22th
HellaSwag 75.6 432 28th
Arena Elo 1286.0 438 27th

FAQ

What score does Mistral Large 3 7B get on MMMU?

Mistral Large 3 7B scores 58.8 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does Mistral Large 3 7B rank on MMMU?

It ranks #443 of 600 models, in the 26th percentile. The leader is GPT-5.2 Max at 86.9.

Is Mistral Large 3 7B good at MMMU?

It is below the median for this benchmark, so test it carefully before relying on it for this capability. The result should be read alongside its price and context window.

How is the MMMU score calculated?

MMMU is a multimodal benchmark. Scores in this index are modelled estimates on a 0–100 scale (or Elo for Arena), derived from capability tier and benchmark difficulty. They are not official leaderboard results.

What does Mistral Large 3 7B cost?

Mistral Large 3 7B costs $1.44 per million input tokens and $7.37 per million output tokens.

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