Safety · Mistral AI

Codestral on TruthfulQA: score, rank and what it means

Codestral scores 79.9 on TruthfulQA, placing it #179 of 600 models in the index. The benchmark average is 73.6 and the leader is GPT-5.1 Max at 91.1.

Score
79.9
0–100 scale
Rank
#179
of 600
Percentile
70th
within the index
Benchmark avg
73.6
all models
Leader
91.1
GPT-5.1 Max
Gap to leader
11.2
points

Score distribution

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

GPT-5.1 Max 91.1
Gemini 3 Pro Reasoning 90.3
GPT-5.1 Reasoning 90.0
GPT-5.2 Pro 90.0
GPT-5.2 89.7
Gemini 3 Pro Max 89.6
Grok 4 Reasoning 89.4
Qwen3-Max Max 89.3
GPT-5.1 89.2
GPT-5.1 Turbo 89.2

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
2 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
3 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
4 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
5 GPT-5.2 OpenAI 2000000 $19.71 88.0
6 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9
7 Grok 4 Reasoning xAI 2000000 $19.67 87.8
8 Qwen3-Max Max Alibaba Cloud 400000 $18.53 85.9
9 GPT-5.1 OpenAI 2000000 $19.01 86.0
10 GPT-5.1 Turbo OpenAI 2000000 $19.19 86.1

What this score means

On TruthfulQA, Codestral sits at #179 of 600. The leader, GPT-5.1 Max, scores 91.1, so the gap to the top is 11.2 points. The median model in this index scores 76.3, which puts Codestral above the midpoint.

Mistral AI models average 71.0 on this benchmark. Codestral is 8.9 points above that provider line, so it is a stronger result than the average Mistral AI model.

Among multimodal models, the average is 80.1. Codestral is 0.2 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 79.9 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 TruthfulQA. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Llama 3.3 Groq Groq 32768 $3.98 76.8
Nemotron 4 NVIDIA 65536 $4.18 76.6
Gemini 3 Pro Mini Google DeepMind 128000 $12.27 78.1
MiniMax-M2 Instruct MiniMax 128000 $5.11 79.4
Codestral Mistral AI 65536 $4.19 77.6
DeepSeek-Coder Chat DeepSeek 200000 $4.20 77.3
Llama 4 Scout Instruct Meta AI 32768 $4.59 79.1

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
IFEval 85.9 160 73th
HellaSwag 88.2 132 78th
MMMU 76.0 139 77th
Arena Elo 1391.6 242 60th

FAQ

What score does Codestral get on TruthfulQA?

Codestral scores 79.9 on TruthfulQA in this index. The benchmark average is 73.6 and the top score is 91.1.

How does Codestral rank on TruthfulQA?

It ranks #179 of 600 models, in the 70th percentile. The leader is GPT-5.1 Max at 91.1.

Is Codestral good at TruthfulQA?

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 TruthfulQA score calculated?

TruthfulQA is a safety 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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