Multimodal · EleutherAI

GPT-NeoX 7B on MMMU: score, rank and what it means

GPT-NeoX 7B scores 42.3 on MMMU, placing it #588 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
42.3
0–100 scale
Rank
#588
of 600
Percentile
2th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
44.6
points

Score distribution

The chart shows the top 10 models on MMMU, with GPT-NeoX 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, GPT-NeoX 7B sits at #588 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 44.6 points. The median model in this index scores 70.0, which puts GPT-NeoX 7B below the midpoint.

EleutherAI models average 50.0 on this benchmark. GPT-NeoX 7B is 7.7 points below that provider line, so it is a weaker result than the average EleutherAI model.

Among small open-weight models, the average is 52.4. GPT-NeoX 7B is 10.1 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 42.3 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 $0.20 per million input tokens, GPT-NeoX 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
Zephyr 8B Hugging Face 8192 $0.22 43.0
GPT-NeoX 8B EleutherAI 16384 $0.25 43.7
Molmo 1.5B Allen Institute for AI 8192 $0.21 42.8
Nemotron Nano 1.5B NVIDIA 8192 $0.10 41.5
GPT-NeoX 7B EleutherAI 8192 $0.20 42.4
Phi-3.5 1.5B Microsoft 32768 $0.25 44.5
SmolLM3 8B Hugging Face 32768 $0.21 44.0

Other benchmarks for GPT-NeoX 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 48.5 595 1th
GPQA Diamond 37.1 594 1th
SWE-bench Verified 26.4 590 2th
HumanEval 43.7 592 1th
MATH-500 42.9 587 2th
AIME 2025 28.9 586 2th
LiveCodeBench 24.0 595 1th
IFEval 56.4 587 2th
TruthfulQA 52.4 585 3th
HellaSwag 64.1 589 2th
Arena Elo 1130.2 593 1th

FAQ

What score does GPT-NeoX 7B get on MMMU?

GPT-NeoX 7B scores 42.3 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does GPT-NeoX 7B rank on MMMU?

It ranks #588 of 600 models, in the 2nd percentile. The leader is GPT-5.2 Max at 86.9.

Is GPT-NeoX 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 GPT-NeoX 7B cost?

GPT-NeoX 7B costs $0.20 per million input tokens and $0.89 per million output tokens.

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