Coding · Mistral AI

Codestral on LiveCodeBench: score, rank and what it means

Codestral scores 67.3 on LiveCodeBench, placing it #241 of 600 models in the index. The benchmark average is 61.0 and the leader is Claude Sonnet 4.5 Reasoning at 85.1.

Score
67.3
0–100 scale
Rank
#241
of 600
Percentile
60th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
17.8
points

Score distribution

The chart shows the top 10 models on LiveCodeBench, with Codestral highlighted. Longer bars mean higher scores.

Claude Sonnet 4.5 Reasoning 85.1
Grok 4 Reasoning 85.1
Claude Opus 4.5 85.0
GPT-5.2 Max 84.8
Grok 4 Turbo 84.7
GPT-5.1 Turbo 84.6
GPT-5.2 Pro 84.6
GPT-5.2 Reasoning 84.6
Claude Opus 4.5 Pro 84.1
Gemini 3 Pro Max 83.6

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
2 Grok 4 Reasoning xAI 2000000 $19.67 87.8
3 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
4 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
5 Grok 4 Turbo xAI 1000000 $19.21 86.7
6 GPT-5.1 Turbo OpenAI 2000000 $19.19 86.1
7 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
8 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
9 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On LiveCodeBench, Codestral sits at #241 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 17.8 points. The median model in this index scores 64.7, which puts Codestral above the midpoint.

Mistral AI models average 58.1 on this benchmark. Codestral is 9.2 points above that provider line, so it is a stronger result than the average Mistral AI model.

Among multimodal models, the average is 70.3. Codestral is 3.0 points below that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 67.3 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 $4.19 per million input tokens, Codestral is above the median input price of $4.00 across the 600 models scored on LiveCodeBench. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Seed-OSS ByteDance 32768 $3.74 75.3
Magistral Chat Mistral AI 128000 $4.33 76.8
Yi-Lightning Chat 01.AI 32768 $3.79 75.5
Llama 3 Modal Modal 32768 $3.82 74.9
Codestral Mistral AI 65536 $4.19 77.6
DeepSeek-Coder Base DeepSeek 32768 $3.53 74.1
Llama 3 Modal Chat Modal 65536 $3.55 73.3

Other benchmarks for Codestral

BenchmarkScoreRankPercentileRelative
MMLU-Pro 79.2 203 66th
GPQA Diamond 75.3 138 77th
SWE-bench Verified 67.7 152 75th
HumanEval 80.5 218 64th
MATH-500 82.1 161 73th
AIME 2025 71.4 230 62th
IFEval 85.9 160 73th
TruthfulQA 79.9 179 70th
HellaSwag 88.2 132 78th
MMMU 76.0 139 77th
Arena Elo 1391.6 242 60th

FAQ

What score does Codestral get on LiveCodeBench?

Codestral scores 67.3 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does Codestral rank on LiveCodeBench?

It ranks #241 of 600 models, in the 60th percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is Codestral good at LiveCodeBench?

Yes, relative to the index: it is above the median and inside the top half of scores. The result should be read alongside its price and context window.

How is the LiveCodeBench score calculated?

LiveCodeBench is a coding 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 cost?

Codestral costs $4.19 per million input tokens and $16.36 per million output tokens.

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