Multimodal · Hugging Face

SmolLM3 7B on MMMU: score, rank and what it means

SmolLM3 7B scores 40.3 on MMMU, placing it #594 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
40.3
0–100 scale
Rank
#594
of 600
Percentile
1th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
46.6
points

Score distribution

The chart shows the top 10 models on MMMU, with SmolLM3 7B highlighted. Longer bars mean higher scores.

GPT-5.2 Max 86.9
GPT-5.1 Reasoning 86.2
GPT-5.2 85.3
Claude Sonnet 4.5 Reasoning 85.2
GPT-5.1 Max 85.1
Grok 4 Pro 84.9
Claude Opus 4.5 Reasoning 84.6
Claude Sonnet 4.5 Pro 84.5
GPT-5.2 Pro 84.4
GPT-5.2 Vision 84.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
3 GPT-5.2 OpenAI 2000000 $19.71 88.0
4 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
5 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
6 Grok 4 Pro xAI 1000000 $19.00 85.4
7 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
8 Claude Sonnet 4.5 Pro Anthropic 1000000 $18.73 86.7
9 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
10 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4

What this score means

On MMMU, SmolLM3 7B sits at #594 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 46.6 points. The median model in this index scores 70.0, which puts SmolLM3 7B below the midpoint.

Hugging Face models average 51.0 on this benchmark. SmolLM3 7B is 10.7 points below that provider line, so it is a weaker result than the average Hugging Face model.

Among small open-weight models, the average is 52.4. SmolLM3 7B is 12.1 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 40.3 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 $0.19 per million input tokens, SmolLM3 7B is below the median input price of $4.00 across the 600 models scored on MMMU. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
SmolLM3 8B Hugging Face 32768 $0.21 44.0
Arctic 1.5B Snowflake 32768 $0.15 43.2
Zephyr 7B Hugging Face 32768 $0.23 42.5
Pythia 8B EleutherAI 32768 $0.16 41.4
SmolLM3 7B Hugging Face 16384 $0.19 44.3
StableLM 2 1.5B Stability AI 16384 $0.13 38.3
Zephyr 1.5B Hugging Face 32768 $0.10 38.0

Other benchmarks for SmolLM3 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 53.6 577 4th
GPQA Diamond 41.8 578 4th
SWE-bench Verified 27.6 587 2th
HumanEval 47.7 585 3th
MATH-500 44.4 579 4th
AIME 2025 26.6 589 2th
LiveCodeBench 30.7 582 3th
IFEval 57.7 584 3th
TruthfulQA 52.1 586 2th
HellaSwag 65.1 584 3th
Arena Elo 1133.2 590 2th

FAQ

What score does SmolLM3 7B get on MMMU?

SmolLM3 7B scores 40.3 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does SmolLM3 7B rank on MMMU?

It ranks #594 of 600 models, in the 1st percentile. The leader is GPT-5.2 Max at 86.9.

Is SmolLM3 7B good at MMMU?

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 MMMU score calculated?

MMMU is a multimodal 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 SmolLM3 7B cost?

SmolLM3 7B costs $0.19 per million input tokens and $1.03 per million output tokens.

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