Coding · Mistral AI

Magistral on SWE-bench Verified: score, rank and what it means

Magistral scores 66.5 on SWE-bench Verified, placing it #179 of 600 models in the index. The benchmark average is 57.5 and the leader is GPT-5.2 Pro at 81.7.

Score
66.5
0–100 scale
Rank
#179
of 600
Percentile
70th
within the index
Benchmark avg
57.5
all models
Leader
81.7
GPT-5.2 Pro
Gap to leader
15.2
points

Score distribution

The chart shows the top 10 models on SWE-bench Verified, with Magistral highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 81.7
Claude Opus 4.5 Pro 81.1
GPT-5.2 Max 80.5
Claude Sonnet 4.5 Max 80.2
GPT-5.2 80.2
GPT-5.1 Pro 80.1
o4 Max 79.8
Claude Sonnet 4.5 Reasoning 79.6
Claude Opus 4.5 Max 79.5
Claude Opus 4.5 Reasoning 79.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
3 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
4 Claude Sonnet 4.5 Max Anthropic 1000000 $19.90 87.2
5 GPT-5.2 OpenAI 2000000 $19.71 88.0
6 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
7 o4 Max OpenAI 2000000 $19.51 86.2
8 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
9 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
10 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2

What this score means

On SWE-bench Verified, Magistral sits at #179 of 600. The leader, GPT-5.2 Pro, scores 81.7, so the gap to the top is 15.2 points. The median model in this index scores 61.0, which puts Magistral above the midpoint.

Mistral AI models average 54.7 on this benchmark. Magistral is 11.8 points above that provider line, so it is a stronger result than the average Mistral AI model.

Among multimodal models, the average is 66.4. Magistral is 0.1 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 66.5 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 $4.75 per million input tokens, Magistral is above the median input price of $4.00 across the 600 models scored on SWE-bench Verified. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Command R+ Chat Cohere 32768 $4.02 76.0
Qwen3 Base Alibaba Cloud 65536 $4.33 77.4
Llama 4 Maverick Chat Meta AI 128000 $5.09 79.7
ERNIE 4.5 Pro Baidu 1000000 $13.89 80.5
Magistral Mistral AI 200000 $4.75 79.8
Phi-4 Microsoft 200000 $3.96 75.4
GLM-4.5 Zhipu AI 200000 $4.55 78.2

Other benchmarks for Magistral

BenchmarkScoreRankPercentileRelative
MMLU-Pro 82.1 120 80th
GPQA Diamond 75.8 126 79th
HumanEval 85.1 111 82th
MATH-500 85.4 101 83th
AIME 2025 74.2 174 71th
LiveCodeBench 75.3 92 85th
IFEval 86.1 152 75th
TruthfulQA 82.0 129 79th
HellaSwag 87.9 146 76th
MMMU 77.4 109 82th
Arena Elo 1427.8 125 79th

FAQ

What score does Magistral get on SWE-bench Verified?

Magistral scores 66.5 on SWE-bench Verified in this index. The benchmark average is 57.5 and the top score is 81.7.

How does Magistral rank on SWE-bench Verified?

It ranks #179 of 600 models, in the 70th percentile. The leader is GPT-5.2 Pro at 81.7.

Is Magistral good at SWE-bench Verified?

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 SWE-bench Verified score calculated?

SWE-bench Verified 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 cost?

Magistral costs $4.75 per million input tokens and $21.16 per million output tokens.

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