Preference · Mistral AI

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

Mistral Small 3 7B scores 1246.3 on Arena Elo, placing it #496 of 600 models in the index. The benchmark average is 1349.9 and the leader is Claude Opus 4.5 Max at 1501.9.

Score
1246.3
0–100 scale
Rank
#496
of 600
Percentile
17th
within the index
Benchmark avg
1349.9
all models
Leader
1501.9
Claude Opus 4.5 Max
Gap to leader
255.6
points

Score distribution

The chart shows the top 10 models on Arena Elo, with Mistral Small 3 7B highlighted. Longer bars mean higher scores.

Claude Opus 4.5 Max 1501.9
GPT-5.2 Reasoning 1500.4
GPT-5.2 Turbo 1500.3
Claude Opus 4.5 Reasoning 1497.5
GPT-5.2 Max 1495.3
Gemini 3 Pro Turbo 1494.9
Grok 4 Max 1491.4
Claude Opus 4.5 1491.2
GPT-5.1 Pro 1490.0
Grok 4 Reasoning 1487.6

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
2 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
3 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
4 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
5 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
6 Gemini 3 Pro Turbo Google DeepMind 400000 $19.62 86.4
7 Grok 4 Max xAI 2000000 $19.70 86.6
8 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
9 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
10 Grok 4 Reasoning xAI 2000000 $19.67 87.8

What this score means

On Arena Elo, Mistral Small 3 7B sits at #496 of 600. The leader, Claude Opus 4.5 Max, scores 1501.9, so the gap to the top is 255.6 points. The median model in this index scores 1373.8, which puts Mistral Small 3 7B below the midpoint.

Mistral AI models average 1329.1 on this benchmark. Mistral Small 3 7B is 82.8 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 1224.7. Mistral Small 3 7B is 21.6 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 1246.3 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 $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 Arena Elo. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Llama 3 Hyperbolic 7B Hyperbolic 4096 $0.94 55.6
Gemma 3 8B Google DeepMind 16384 $0.96 56.5
Mixtral Groq 8B Groq 32768 $0.77 54.8
Nemotron 4 8B NVIDIA 4096 $1.06 57.9
Mistral Small 3 7B Mistral AI 4096 $0.89 55.2
Llama 3.1 Turbo 7B Together AI 8192 $0.98 56.4
Llama 3 Hyperbolic 8B Hyperbolic 16384 $0.92 56.0

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
LiveCodeBench 44.1 507 16th
IFEval 65.8 522 13th
TruthfulQA 60.6 523 13th
HellaSwag 72.1 494 18th
MMMU 50.8 546 9th

FAQ

What score does Mistral Small 3 7B get on Arena Elo?

Mistral Small 3 7B scores 1246.3 on Arena Elo in this index. The benchmark average is 1349.9 and the top score is 1501.9.

How does Mistral Small 3 7B rank on Arena Elo?

It ranks #496 of 600 models, in the 17th percentile. The leader is Claude Opus 4.5 Max at 1501.9.

Is Mistral Small 3 7B good at Arena Elo?

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 Arena Elo score calculated?

Arena Elo is a preference 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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