Safety · Mistral AI

Codestral 7B on TruthfulQA: score, rank and what it means

Codestral 7B scores 61.0 on TruthfulQA, placing it #519 of 600 models in the index. The benchmark average is 73.6 and the leader is GPT-5.1 Max at 91.1.

Score
61.0
0–100 scale
Rank
#519
of 600
Percentile
14th
within the index
Benchmark avg
73.6
all models
Leader
91.1
GPT-5.1 Max
Gap to leader
30.1
points

Score distribution

The chart shows the top 10 models on TruthfulQA, with Codestral 7B 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 7B sits at #519 of 600. The leader, GPT-5.1 Max, scores 91.1, so the gap to the top is 30.1 points. The median model in this index scores 76.3, which puts Codestral 7B below the midpoint.

Mistral AI models average 71.0 on this benchmark. Codestral 7B is 10.0 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 59.9. Codestral 7B is 1.1 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 61.0 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 $1.05 per million input tokens, Codestral 7B is below 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
Mixtral 8B Mistral AI 8192 $0.91 55.4
DeepSeek-V3.2 1.5B DeepSeek 4096 $1.02 56.9
Llama 4 Maverick 1.5B Meta AI 8192 $0.93 55.2
Mixtral Turbo 8B Together AI 4096 $0.75 54.1
Codestral 7B Mistral AI 32768 $1.05 57.0
Qwen3 1.5B Alibaba Cloud 4096 $0.84 53.5
Llama 3 Lambda 8B Lambda 4096 $1.03 57.2

Other benchmarks for Codestral 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 60.2 526 12th
GPQA Diamond 54.0 480 20th
SWE-bench Verified 44.0 478 20th
HumanEval 62.3 465 23th
MATH-500 57.0 497 17th
AIME 2025 42.8 525 13th
LiveCodeBench 48.0 465 23th
IFEval 69.0 473 21th
HellaSwag 73.9 457 24th
MMMU 55.1 495 18th
Arena Elo 1243.9 500 17th

FAQ

What score does Codestral 7B get on TruthfulQA?

Codestral 7B scores 61.0 on TruthfulQA in this index. The benchmark average is 73.6 and the top score is 91.1.

How does Codestral 7B rank on TruthfulQA?

It ranks #519 of 600 models, in the 14th percentile. The leader is GPT-5.1 Max at 91.1.

Is Codestral 7B good at TruthfulQA?

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 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 7B cost?

Codestral 7B costs $1.05 per million input tokens and $5.23 per million output tokens.

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