Reasoning · Mistral AI

Codestral 7B on GPQA Diamond: score, rank and what it means

Codestral 7B scores 54.0 on GPQA Diamond, placing it #480 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
54.0
0–100 scale
Rank
#480
of 600
Percentile
20th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
33.0
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with Codestral 7B highlighted. Longer bars mean higher scores.

GPT-5.2 Reasoning 87.0
GPT-5.1 Max 86.4
Claude Opus 4.5 Pro 86.0
GPT-5.1 Reasoning 85.6
Claude Sonnet 4.5 Reasoning 85.2
GPT-5.2 84.9
o4 Turbo 84.8
Claude Opus 4.5 Max 84.6
Grok 4 Turbo 84.5
Claude Sonnet 4.5 Max 84.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 GPT-5.2 OpenAI 2000000 $19.71 88.0
7 o4 Turbo OpenAI 2000000 $19.34 86.6
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 Grok 4 Turbo xAI 1000000 $19.21 86.7
10 Claude Sonnet 4.5 Max Anthropic 1000000 $19.90 87.2

What this score means

On GPQA Diamond, Codestral 7B sits at #480 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 33.0 points. The median model in this index scores 68.8, which puts Codestral 7B below the midpoint.

Mistral AI models average 63.3 on this benchmark. Codestral 7B is 9.3 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 49.3. Codestral 7B is 4.7 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 54.0 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 $1.05 per million input tokens, Codestral 7B is below the median input price of $4.00 across the 600 models scored on GPQA Diamond. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
GLM-4.5 8B Zhipu AI 32768 $1.46 61.3
Llama 3.3 8B Meta AI 8192 $1.26 60.1
DeepSeek-Coder 7B DeepSeek 32768 $1.14 57.3
Llama 3 DeepInfra 7B DeepInfra 16384 $0.95 55.6
Codestral 7B Mistral AI 32768 $1.05 57.0
DeepSeek-Coder 8B DeepSeek 32768 $1.26 58.7
Gemma 3 7B Google DeepMind 32768 $0.90 55.9

Other benchmarks for Codestral 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 60.2 526 12th
SWE-bench Verified 44.0 478 20th
HumanEval 62.3 465 23th
MATH-500 57.0 497 17th
AIME 2025 42.8 525 13th
LiveCodeBench 48.0 465 23th
IFEval 69.0 473 21th
TruthfulQA 61.0 519 14th
HellaSwag 73.9 457 24th
MMMU 55.1 495 18th
Arena Elo 1243.9 500 17th

FAQ

What score does Codestral 7B get on GPQA Diamond?

Codestral 7B scores 54.0 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does Codestral 7B rank on GPQA Diamond?

It ranks #480 of 600 models, in the 20th percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is Codestral 7B good at GPQA Diamond?

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 GPQA Diamond score calculated?

GPQA Diamond is a reasoning 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 7B cost?

Codestral 7B costs $1.05 per million input tokens and $5.23 per million output tokens.

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