Multimodal · Hugging Face

SmolLM3 Base on MMMU: score, rank and what it means

SmolLM3 Base scores 59.4 on MMMU, placing it #435 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
59.4
0–100 scale
Rank
#435
of 600
Percentile
28th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
27.5
points

Score distribution

The chart shows the top 10 models on MMMU, with SmolLM3 Base 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 Base sits at #435 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 27.5 points. The median model in this index scores 70.0, which puts SmolLM3 Base below the midpoint.

Hugging Face models average 51.0 on this benchmark. SmolLM3 Base is 8.4 points above that provider line, so it is a stronger result than the average Hugging Face model.

Among open-weight models, the average is 65.1. SmolLM3 Base is 5.7 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 59.4 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 $1.38 per million input tokens, SmolLM3 Base 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
Mistral Large 3 8B Mistral AI 16384 $1.62 61.6
GLM-4.5 7B Zhipu AI 8192 $1.32 60.2
Embed 4 Turbo Cohere 4096 $5.13 64.0
Llama 3.1 8B Meta AI 8192 $1.15 58.7
SmolLM3 Base Hugging Face 16384 $1.38 60.4
Auto Mini OpenRouter 4096 $4.24 61.6
Kimi K2 7B Moonshot AI 16384 $1.72 62.7

Other benchmarks for SmolLM3 Base

BenchmarkScoreRankPercentileRelative
MMLU-Pro 63.7 480 20th
GPQA Diamond 55.0 464 23th
SWE-bench Verified 45.5 461 23th
HumanEval 63.2 457 24th
MATH-500 60.1 463 23th
AIME 2025 54.8 416 31th
LiveCodeBench 52.5 420 30th
IFEval 71.3 437 27th
TruthfulQA 65.7 450 25th
HellaSwag 73.6 464 23th
Arena Elo 1280.0 446 26th

FAQ

What score does SmolLM3 Base get on MMMU?

SmolLM3 Base scores 59.4 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does SmolLM3 Base rank on MMMU?

It ranks #435 of 600 models, in the 28th percentile. The leader is GPT-5.2 Max at 86.9.

Is SmolLM3 Base 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 Base cost?

SmolLM3 Base costs $1.38 per million input tokens and $7.55 per million output tokens.

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