Mathematics · Mistral AI

Codestral 8B on MATH-500: score, rank and what it means

Codestral 8B scores 57.9 on MATH-500, placing it #492 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
57.9
0–100 scale
Rank
#492
of 600
Percentile
18th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
38.8
points

Score distribution

The chart shows the top 10 models on MATH-500, with Codestral 8B highlighted. Longer bars mean higher scores.

GPT-5.2 Max 96.7
GPT-5.1 Reasoning 95.9
GPT-5.1 Pro 95.1
o4 Reasoning 94.8
Grok 4 Max 94.6
Grok 4 Reasoning 94.4
Claude Opus 4.5 Max 94.2
Claude Opus 4.5 93.7
Gemini 3 Pro Reasoning 93.3
Claude Opus 4.5 Turbo 93.2

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-5.1 Pro OpenAI 200000 $19.77 87.8
4 o4 Reasoning OpenAI 1000000 $19.69 87.5
5 Grok 4 Max xAI 2000000 $19.70 86.6
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
8 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
9 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
10 Claude Opus 4.5 Turbo Anthropic 2000000 $19.57 85.7

What this score means

On MATH-500, Codestral 8B sits at #492 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 38.8 points. The median model in this index scores 76.0, which puts Codestral 8B below the midpoint.

Mistral AI models average 69.1 on this benchmark. Codestral 8B is 11.2 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 53.7. Codestral 8B is 4.2 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 57.9 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 MATH-500. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Hunyuan-Large 8B Tencent 4096 $1.29 58.7
Llama 3 Lambda 8B Lambda 4096 $1.03 57.2
Magistral 7B Mistral AI 32768 $1.22 58.9
MiniMax-Text 8B MiniMax 4096 $1.22 59.5
Codestral 8B Mistral AI 4096 $1.18 59.0
Llama 3.1 8B Meta AI 8192 $1.15 58.7
Command R+ 8B Cohere 8192 $1.21 57.7

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
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
MMMU 55.6 491 18th
Arena Elo 1253.3 486 19th

FAQ

What score does Codestral 8B get on MATH-500?

Codestral 8B scores 57.9 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Codestral 8B rank on MATH-500?

It ranks #492 of 600 models, in the 18th percentile. The leader is GPT-5.2 Max at 96.7.

Is Codestral 8B good at MATH-500?

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 MATH-500 score calculated?

MATH-500 is a mathematics 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.

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