Coding · Mistral AI

Mistral Small 3 7B on LiveCodeBench: score, rank and what it means

Mistral Small 3 7B scores 44.1 on LiveCodeBench, placing it #507 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
44.1
0–100 scale
Rank
#507
of 600
Percentile
16th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
41.0
points

Score distribution

The chart shows the top 10 models on LiveCodeBench, with Mistral Small 3 7B 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, Mistral Small 3 7B sits at #507 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 41.0 points. The median model in this index scores 64.7, which puts Mistral Small 3 7B below the midpoint.

Mistral AI models average 58.1 on this benchmark. Mistral Small 3 7B is 14.0 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 41.2. Mistral Small 3 7B is 2.9 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 44.1 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 $0.89 per million input tokens, Mistral Small 3 7B is below 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
Hunyuan-Large 7B Tencent 32768 $1.08 57.7
Llama 3 Baseten 8B Baseten 4096 $1.02 57.0
QwQ 7B Alibaba Cloud 8192 $1.11 58.1
Llama 3.1 Turbo 7B Together AI 8192 $0.98 56.4
Mistral Small 3 7B Mistral AI 4096 $0.89 55.2
GLM-4.6 1.5B Zhipu AI 4096 $0.92 54.7
Llama 3 Novita 8B Novita AI 16384 $0.99 55.5

Other benchmarks for Mistral Small 3 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 58.8 540 10th
GPQA Diamond 48.9 535 11th
SWE-bench Verified 43.1 490 18th
HumanEval 60.5 496 17th
MATH-500 55.6 513 15th
AIME 2025 47.4 474 21th
IFEval 65.8 522 13th
TruthfulQA 60.6 523 13th
HellaSwag 72.1 494 18th
MMMU 50.8 546 9th
Arena Elo 1246.3 496 17th

FAQ

What score does Mistral Small 3 7B get on LiveCodeBench?

Mistral Small 3 7B scores 44.1 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does Mistral Small 3 7B rank on LiveCodeBench?

It ranks #507 of 600 models, in the 16th percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is Mistral Small 3 7B good at LiveCodeBench?

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 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 Mistral Small 3 7B cost?

Mistral Small 3 7B costs $0.89 per million input tokens and $4.71 per million output tokens.

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