Mathematics · EleutherAI

GPT-NeoX 1.5B on MATH-500: score, rank and what it means

GPT-NeoX 1.5B scores 35.7 on MATH-500, placing it #597 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
35.7
0–100 scale
Rank
#597
of 600
Percentile
1th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
61.0
points

Score distribution

The chart shows the top 10 models on MATH-500, with GPT-NeoX 1.5B highlighted. Longer bars mean higher scores.

GPT-5.2 Max 96.7
GPT-5.1 Reasoning 95.9
GPT-5.1 Pro 95.1
o4 Reasoning 94.8
Grok 4 Max 94.6
Grok 4 Reasoning 94.4
Claude Opus 4.5 Max 94.2
Claude Opus 4.5 93.7
Gemini 3 Pro Reasoning 93.3
Claude Opus 4.5 Turbo 93.2

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-5.1 Pro OpenAI 200000 $19.77 87.8
4 o4 Reasoning OpenAI 1000000 $19.69 87.5
5 Grok 4 Max xAI 2000000 $19.70 86.6
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
8 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
9 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
10 Claude Opus 4.5 Turbo Anthropic 2000000 $19.57 85.7

What this score means

On MATH-500, GPT-NeoX 1.5B sits at #597 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 61.0 points. The median model in this index scores 76.0, which puts GPT-NeoX 1.5B below the midpoint.

EleutherAI models average 52.0 on this benchmark. GPT-NeoX 1.5B is 16.2 points below that provider line, so it is a weaker result than the average EleutherAI model.

Among small open-weight models, the average is 53.7. GPT-NeoX 1.5B is 18.0 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 35.7 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 $0.060 per million input tokens, GPT-NeoX 1.5B is below the median input price of $4.00 across the 600 models scored on MATH-500. 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
Molmo 1.5B Allen Institute for AI 8192 $0.21 42.8
Pythia 8B EleutherAI 32768 $0.16 41.4
SmolLM3 1.5B Hugging Face 8192 $0.04 36.8
GPT-NeoX 1.5B EleutherAI 32768 $0.06 36.4
Zephyr 1.5B Hugging Face 32768 $0.10 38.0
StableLM 2 1.5B Stability AI 16384 $0.13 38.3

Other benchmarks for GPT-NeoX 1.5B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 47.0 598 1th
GPQA Diamond 32.4 598 1th
SWE-bench Verified 18.3 600 1th
HumanEval 37.0 600 1th
AIME 2025 17.6 598 1th
LiveCodeBench 22.0 598 1th
IFEval 49.5 600 1th
TruthfulQA 44.3 599 1th
HellaSwag 58.1 598 1th
MMMU 38.6 598 1th
Arena Elo 1112.0 596 1th

FAQ

What score does GPT-NeoX 1.5B get on MATH-500?

GPT-NeoX 1.5B scores 35.7 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does GPT-NeoX 1.5B rank on MATH-500?

It ranks #597 of 600 models, in the 1st percentile. The leader is GPT-5.2 Max at 96.7.

Is GPT-NeoX 1.5B good at MATH-500?

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 MATH-500 score calculated?

MATH-500 is a mathematics 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 1.5B cost?

GPT-NeoX 1.5B costs $0.060 per million input tokens and $0.32 per million output tokens.

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