Preference · Mistral AI

Mistral Small 3 1.5B on Arena Elo: score, rank and what it means

Mistral Small 3 1.5B scores 1200.3 on Arena Elo, placing it #555 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
1200.3
0–100 scale
Rank
#555
of 600
Percentile
8th
within the index
Benchmark avg
1349.9
all models
Leader
1501.9
Claude Opus 4.5 Max
Gap to leader
301.6
points

Score distribution

The chart shows the top 10 models on Arena Elo, with Mistral Small 3 1.5B 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 1.5B sits at #555 of 600. The leader, Claude Opus 4.5 Max, scores 1501.9, so the gap to the top is 301.6 points. The median model in this index scores 1373.8, which puts Mistral Small 3 1.5B below the midpoint.

Mistral AI models average 1329.1 on this benchmark. Mistral Small 3 1.5B is 128.8 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 1.5B is 24.4 points below that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 1200.3 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 $0.42 per million input tokens, Mistral Small 3 1.5B 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
Seed-OSS 1.5B ByteDance 4096 $0.45 49.8
Arctic 7B Snowflake 8192 $0.49 50.3
Phi-3.5 8B Microsoft 16384 $0.59 51.2
Llama 3 Novita 1.5B Novita AI 4096 $0.41 49.1
Mistral Small 3 1.5B Mistral AI 32768 $0.42 49.2
DeepSeek-Coder 1.5B DeepSeek 16384 $0.58 51.0
Llama 3.1 Cerebras 1.5B Cerebras 4096 $0.48 50.2

Other benchmarks for Mistral Small 3 1.5B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 56.3 566 6th
GPQA Diamond 44.3 569 5th
SWE-bench Verified 34.7 561 7th
HumanEval 50.9 568 5th
MATH-500 48.7 569 5th
AIME 2025 36.6 558 7th
LiveCodeBench 34.5 572 5th
IFEval 62.5 551 8th
TruthfulQA 56.1 564 6th
HellaSwag 68.5 554 8th
MMMU 48.0 565 6th

FAQ

What score does Mistral Small 3 1.5B get on Arena Elo?

Mistral Small 3 1.5B scores 1200.3 on Arena Elo in this index. The benchmark average is 1349.9 and the top score is 1501.9.

How does Mistral Small 3 1.5B rank on Arena Elo?

It ranks #555 of 600 models, in the 8th percentile. The leader is Claude Opus 4.5 Max at 1501.9.

Is Mistral Small 3 1.5B 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 1.5B cost?

Mistral Small 3 1.5B costs $0.42 per million input tokens and $1.58 per million output tokens.

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