Coding · Mistral AI

Mistral Small 3 8B on SWE-bench Verified: score, rank and what it means

Mistral Small 3 8B scores 40.7 on SWE-bench Verified, placing it #514 of 600 models in the index. The benchmark average is 57.5 and the leader is GPT-5.2 Pro at 81.7.

Score
40.7
0–100 scale
Rank
#514
of 600
Percentile
14th
within the index
Benchmark avg
57.5
all models
Leader
81.7
GPT-5.2 Pro
Gap to leader
41.0
points

Score distribution

The chart shows the top 10 models on SWE-bench Verified, with Mistral Small 3 8B 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, Mistral Small 3 8B sits at #514 of 600. The leader, GPT-5.2 Pro, scores 81.7, so the gap to the top is 41.0 points. The median model in this index scores 61.0, which puts Mistral Small 3 8B below the midpoint.

Mistral AI models average 54.7 on this benchmark. Mistral Small 3 8B 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 39.0. Mistral Small 3 8B is 1.7 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 40.7 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 $0.99 per million input tokens, Mistral Small 3 8B is below 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
Mixtral 8B Mistral AI 8192 $0.91 55.4
Llama 3.3 Groq 7B Groq 16384 $1.01 56.7
Nemotron 4 8B NVIDIA 4096 $1.06 57.9
Llama 3 Modal 7B Modal 4096 $0.88 55.2
Mistral Small 3 8B Mistral AI 8192 $0.99 57.2
Llama 3 Hyperbolic 7B Hyperbolic 4096 $0.94 55.6
Seed-OSS 8B ByteDance 8192 $1.05 57.1

Other benchmarks for Mistral Small 3 8B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 62.6 494 18th
GPQA Diamond 51.8 501 17th
HumanEval 61.3 478 20th
MATH-500 55.5 516 14th
AIME 2025 47.5 473 21th
LiveCodeBench 45.8 489 19th
IFEval 68.9 477 21th
TruthfulQA 62.9 494 18th
HellaSwag 73.5 468 22th
MMMU 58.3 453 25th
Arena Elo 1253.4 485 19th

FAQ

What score does Mistral Small 3 8B get on SWE-bench Verified?

Mistral Small 3 8B scores 40.7 on SWE-bench Verified in this index. The benchmark average is 57.5 and the top score is 81.7.

How does Mistral Small 3 8B rank on SWE-bench Verified?

It ranks #514 of 600 models, in the 14th percentile. The leader is GPT-5.2 Pro at 81.7.

Is Mistral Small 3 8B good at SWE-bench Verified?

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 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 Mistral Small 3 8B cost?

Mistral Small 3 8B costs $0.99 per million input tokens and $5.38 per million output tokens.

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