Multimodal · EleutherAI

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

GPT-NeoX scores 60.5 on MMMU, placing it #424 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
60.5
0–100 scale
Rank
#424
of 600
Percentile
29th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
26.4
points

Score distribution

The chart shows the top 10 models on MMMU, with GPT-NeoX 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 sits at #424 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 26.4 points. The median model in this index scores 70.0, which puts GPT-NeoX below the midpoint.

EleutherAI models average 50.0 on this benchmark. GPT-NeoX is 10.5 points above that provider line, so it is a stronger result than the average EleutherAI model.

Among open-weight models, the average is 65.1. GPT-NeoX is 4.6 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 60.5 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 $1.57 per million input tokens, GPT-NeoX 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
Kimi K1.5 8B Moonshot AI 8192 $1.54 62.2
StableLM 2 Chat Stability AI 8192 $1.79 64.6
Zephyr Instruct Hugging Face 4096 $1.66 62.4
Embed 4 Pro Cohere 4096 $5.05 63.5
GPT-NeoX EleutherAI 16384 $1.57 61.7
SmolLM3 Instruct Hugging Face 8192 $1.69 63.6
SmolLM3 Chat Hugging Face 16384 $1.61 62.1

Other benchmarks for GPT-NeoX

BenchmarkScoreRankPercentileRelative
MMLU-Pro 67.6 422 30th
GPQA Diamond 54.6 468 22th
SWE-bench Verified 46.4 449 25th
HumanEval 64.9 442 26th
MATH-500 64.0 425 29th
AIME 2025 55.8 411 32th
LiveCodeBench 52.7 418 30th
IFEval 69.8 464 23th
TruthfulQA 67.6 422 30th
HellaSwag 75.0 442 26th
Arena Elo 1277.8 448 25th

FAQ

What score does GPT-NeoX get on MMMU?

GPT-NeoX scores 60.5 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does GPT-NeoX rank on MMMU?

It ranks #424 of 600 models, in the 29th percentile. The leader is GPT-5.2 Max at 86.9.

Is GPT-NeoX 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 cost?

GPT-NeoX costs $1.57 per million input tokens and $7.57 per million output tokens.

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