Coding · Mistral AI

Codestral Base on HumanEval: score, rank and what it means

Codestral Base scores 79.7 on HumanEval, placing it #240 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.

Score
79.7
0–100 scale
Rank
#240
of 600
Percentile
60th
within the index
Benchmark avg
74.0
all models
Leader
96.8
GPT-5.2 Pro
Gap to leader
17.1
points

Score distribution

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

GPT-5.2 Pro 96.8
Gemini 3 Pro Pro 95.0
o4 Max 94.6
Grok 4 Reasoning 93.8
Claude Opus 4.5 93.7
GPT-5.2 Max 93.6
Claude Opus 4.5 Pro 93.4
Grok 4 Max 93.4
GPT-5.2 Turbo 93.2
GPT-5.1 Reasoning 92.9

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 Gemini 3 Pro Pro Google DeepMind 200000 $19.80 87.3
3 o4 Max OpenAI 2000000 $19.51 86.2
4 Grok 4 Reasoning xAI 2000000 $19.67 87.8
5 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
6 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
7 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
8 Grok 4 Max xAI 2000000 $19.70 86.6
9 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
10 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3

What this score means

On HumanEval, Codestral Base sits at #240 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 17.1 points. The median model in this index scores 77.4, which puts Codestral Base above the midpoint.

Mistral AI models average 71.6 on this benchmark. Codestral Base is 8.1 points above that provider line, so it is a stronger result than the average Mistral AI model.

Among open-weight models, the average is 72.4. Codestral Base is 7.3 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 79.7 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 $3.31 per million input tokens, Codestral Base is below the median input price of $4.00 across the 600 models scored on HumanEval. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
MiniMax-Text Base MiniMax 128000 $3.66 74.9
Seed-OSS Chat ByteDance 65536 $3.49 74.4
Llama 3 Anyscale Anyscale 65536 $3.94 74.7
Llama 3 Hyperbolic Chat Hyperbolic 200000 $3.64 75.1
Codestral Base Mistral AI 8192 $3.31 73.1
GPT-5.2 Nano OpenAI 128000 $9.73 73.5
Hunyuan-Turbo Turbo Tencent 65536 $11.60 77.4

Other benchmarks for Codestral Base

BenchmarkScoreRankPercentileRelative
MMLU-Pro 74.1 348 42th
GPQA Diamond 70.4 252 58th
SWE-bench Verified 62.6 264 56th
MATH-500 77.4 267 56th
AIME 2025 68.7 283 53th
LiveCodeBench 65.7 279 54th
IFEval 79.2 347 42th
TruthfulQA 74.3 347 42th
HellaSwag 83.3 311 48th
MMMU 68.3 339 44th
Arena Elo 1371.7 310 48th

FAQ

What score does Codestral Base get on HumanEval?

Codestral Base scores 79.7 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.

How does Codestral Base rank on HumanEval?

It ranks #240 of 600 models, in the 60th percentile. The leader is GPT-5.2 Pro at 96.8.

Is Codestral Base good at HumanEval?

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 HumanEval score calculated?

HumanEval 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 Base cost?

Codestral Base costs $3.31 per million input tokens and $16.95 per million output tokens.

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