Instruction following · Mistral AI

Codestral on IFEval: score, rank and what it means

Codestral scores 85.9 on IFEval, placing it #160 of 600 models in the index. The benchmark average is 78.6 and the leader is Claude Opus 4.5 Pro at 96.1.

Score
85.9
0–100 scale
Rank
#160
of 600
Percentile
73th
within the index
Benchmark avg
78.6
all models
Leader
96.1
Claude Opus 4.5 Pro
Gap to leader
10.2
points

Score distribution

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

Claude Opus 4.5 Pro 96.1
Claude Opus 4.5 Reasoning 95.9
GPT-5.2 Pro 95.6
GPT-5.2 Max 95.2
GPT-5.2 Reasoning 95.0
GPT-5.1 Pro 94.8
Gemini 3 Pro Max 94.7
GPT-5.1 Reasoning 94.6
Claude Opus 4.5 Max 94.5
o4 Reasoning 94.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
2 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
3 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
4 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
5 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
6 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
7 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9
8 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
9 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
10 o4 Reasoning OpenAI 1000000 $19.69 87.5

What this score means

On IFEval, Codestral sits at #160 of 600. The leader, Claude Opus 4.5 Pro, scores 96.1, so the gap to the top is 10.2 points. The median model in this index scores 81.2, which puts Codestral above the midpoint.

Mistral AI models average 76.5 on this benchmark. Codestral is 9.4 points above that provider line, so it is a stronger result than the average Mistral AI model.

Among multimodal models, the average is 85.2. Codestral is 0.7 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 85.9 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 $4.19 per million input tokens, Codestral is above the median input price of $4.00 across the 600 models scored on IFEval. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
ERNIE 4.5 Pro Baidu 1000000 $13.89 80.5
Kimi K1.5 Base Moonshot AI 65536 $4.34 77.4
Llama 3.1 Turbo Instruct Together AI 32768 $4.21 76.7
Reka Core Pro Reka AI 65536 $13.44 79.9
Codestral Mistral AI 65536 $4.19 77.6
ERNIE 4.0 Max Baidu 32768 $12.40 78.9
Claude Sonnet 4.5 Mini Anthropic 32768 $11.43 76.5

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
LiveCodeBench 67.3 241 60th
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 IFEval?

Codestral scores 85.9 on IFEval in this index. The benchmark average is 78.6 and the top score is 96.1.

How does Codestral rank on IFEval?

It ranks #160 of 600 models, in the 73rd percentile. The leader is Claude Opus 4.5 Pro at 96.1.

Is Codestral good at IFEval?

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 IFEval score calculated?

IFEval is a instruction following 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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