Multimodal · Stability AI

StableLM 2 7B on MMMU: score, rank and what it means

StableLM 2 7B scores 46.0 on MMMU, placing it #581 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
46.0
0–100 scale
Rank
#581
of 600
Percentile
3th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
40.9
points

Score distribution

The chart shows the top 10 models on MMMU, with StableLM 2 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, StableLM 2 7B sits at #581 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 40.9 points. The median model in this index scores 70.0, which puts StableLM 2 7B below the midpoint.

Stability AI models average 54.2 on this benchmark. StableLM 2 7B is 8.2 points below that provider line, so it is a weaker result than the average Stability AI model.

Among small open-weight models, the average is 52.4. StableLM 2 7B is 6.4 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 46.0 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 $0.28 per million input tokens, StableLM 2 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
OLMo 2 1.5B Allen Institute for AI 16384 $0.28 44.0
Embed 4 Nano Cohere 8192 $1.48 49.7
Nemotron Nano 8B NVIDIA 8192 $0.46 48.1
Phi-4 1.5B Microsoft 8192 $0.42 48.1
StableLM 2 7B Stability AI 8192 $0.28 44.3
Llama 3 Hyperbolic 1.5B Hyperbolic 32768 $0.45 48.4
Yi-Large 1.5B 01.AI 8192 $0.42 46.8

Other benchmarks for StableLM 2 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 50.2 594 1th
GPQA Diamond 40.7 583 3th
SWE-bench Verified 30.9 578 4th
HumanEval 45.2 589 2th
MATH-500 42.6 588 2th
AIME 2025 28.2 587 2th
LiveCodeBench 28.2 587 2th
IFEval 57.7 585 3th
TruthfulQA 52.7 584 3th
HellaSwag 65.2 582 3th
Arena Elo 1155.7 582 3th

FAQ

What score does StableLM 2 7B get on MMMU?

StableLM 2 7B scores 46.0 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does StableLM 2 7B rank on MMMU?

It ranks #581 of 600 models, in the 3rd percentile. The leader is GPT-5.2 Max at 86.9.

Is StableLM 2 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 StableLM 2 7B cost?

StableLM 2 7B costs $0.28 per million input tokens and $1.47 per million output tokens.

Related