Coding · Mistral AI

Magistral 7B on LiveCodeBench: score, rank and what it means

Magistral 7B scores 51.3 on LiveCodeBench, placing it #436 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
51.3
0–100 scale
Rank
#436
of 600
Percentile
27th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
33.8
points

Score distribution

The chart shows the top 10 models on LiveCodeBench, with Magistral 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, Magistral 7B sits at #436 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 33.8 points. The median model in this index scores 64.7, which puts Magistral 7B below the midpoint.

Mistral AI models average 58.1 on this benchmark. Magistral 7B is 6.8 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. Magistral 7B is 10.1 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 51.3 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 $1.22 per million input tokens, Magistral 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
GLM-4.6 8B Zhipu AI 8192 $1.69 63.1
Qwen3 8B Alibaba Cloud 8192 $1.66 61.9
Firefunction Mini Fireworks AI 32768 $4.63 63.2
Llama 4 Scout 7B Meta AI 32768 $1.30 60.0
Magistral 7B Mistral AI 32768 $1.22 58.9
Llama 4 Maverick 8B Meta AI 4096 $1.64 63.4
Zephyr Chat Hugging Face 4096 $1.49 61.3

Other benchmarks for Magistral 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 64.7 458 24th
GPQA Diamond 57.6 432 28th
SWE-bench Verified 46.6 448 25th
HumanEval 61.1 486 19th
MATH-500 58.0 490 18th
AIME 2025 46.0 489 19th
IFEval 69.6 467 22th
TruthfulQA 62.0 504 16th
HellaSwag 73.1 478 20th
MMMU 57.8 459 24th
Arena Elo 1263.4 469 22th

FAQ

What score does Magistral 7B get on LiveCodeBench?

Magistral 7B scores 51.3 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does Magistral 7B rank on LiveCodeBench?

It ranks #436 of 600 models, in the 27th percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is Magistral 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 Magistral 7B cost?

Magistral 7B costs $1.22 per million input tokens and $5.57 per million output tokens.

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