Multimodal · Mistral AI

Codestral 8B on MMMU: score, rank and what it means

Codestral 8B scores 55.6 on MMMU, placing it #491 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
55.6
0–100 scale
Rank
#491
of 600
Percentile
18th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
31.3
points

Score distribution

The chart shows the top 10 models on MMMU, with Codestral 8B 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, Codestral 8B sits at #491 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 31.3 points. The median model in this index scores 70.0, which puts Codestral 8B below the midpoint.

Mistral AI models average 64.8 on this benchmark. Codestral 8B is 9.2 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. Codestral 8B is 3.2 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 55.6 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 $1.18 per million input tokens, Codestral 8B 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 Anyscale 7B Anyscale 4096 $0.98 56.2
Llama 3.3 Groq 7B Groq 16384 $1.01 56.7
Nova Lite Nano Amazon 8192 $3.29 59.5
Fusion Nano OpenRouter 8192 $2.96 56.8
Codestral 8B Mistral AI 4096 $1.18 59.0
Nemotron 4 8B NVIDIA 4096 $1.06 57.9
Llama 3 Lambda 8B Lambda 4096 $1.03 57.2

Other benchmarks for Codestral 8B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 65.7 441 27th
GPQA Diamond 53.3 488 19th
SWE-bench Verified 46.1 451 25th
HumanEval 62.8 459 24th
MATH-500 57.9 492 18th
AIME 2025 49.9 461 23th
LiveCodeBench 49.5 453 25th
IFEval 70.4 451 25th
TruthfulQA 65.4 455 24th
HellaSwag 72.0 495 18th
Arena Elo 1253.3 486 19th

FAQ

What score does Codestral 8B get on MMMU?

Codestral 8B scores 55.6 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does Codestral 8B rank on MMMU?

It ranks #491 of 600 models, in the 18th percentile. The leader is GPT-5.2 Max at 86.9.

Is Codestral 8B 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 Codestral 8B cost?

Codestral 8B costs $1.18 per million input tokens and $5.35 per million output tokens.

Related