GPT-NeoX Base on MMLU-Pro: score, rank and what it means
GPT-NeoX Base scores 65.2 on MMLU-Pro, placing it #450 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.
Score distribution
The chart shows the top 10 models on MMLU-Pro, with GPT-NeoX Base highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|---|
| 1 | GPT-5.2 Pro | OpenAI | 2000000 | $21.32 | 89.6 |
| 2 | GPT-5.1 Max | OpenAI | 2000000 | $20.50 | 87.9 |
| 3 | Claude Opus 4.5 Pro | Anthropic | 200000 | $20.98 | 89.1 |
| 4 | Claude Opus 4.5 Reasoning | Anthropic | 2000000 | $20.91 | 88.2 |
| 5 | Gemini 3 Pro Reasoning | Google DeepMind | 200000 | $19.69 | 87.5 |
| 6 | GPT-5.1 Reasoning | OpenAI | 400000 | $20.27 | 88.3 |
| 7 | GPT-5.2 | OpenAI | 2000000 | $19.71 | 88.0 |
| 8 | Claude Opus 4.5 Max | Anthropic | 1000000 | $20.90 | 87.8 |
| 9 | GPT-5.2 Vision | OpenAI | 1000000 | $19.03 | 87.4 |
| 10 | Gemini 3 Pro Max | Google DeepMind | 2000000 | $20.57 | 87.9 |
What this score means
On MMLU-Pro, GPT-NeoX Base sits at #450 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 26.4 points. The median model in this index scores 76.1, which puts GPT-NeoX Base below the midpoint.
EleutherAI models average 58.0 on this benchmark. GPT-NeoX Base is 7.2 points above that provider line, so it is a stronger result than the average EleutherAI model.
Among open-weight models, the average is 72.1. GPT-NeoX Base is 6.9 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 65.2 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 $1.22 per million input tokens, GPT-NeoX Base is below the median input price of $4.00 across the 600 models scored on MMLU-Pro. The models immediately around it in the ranking are shown below so you can compare score and price together.
| Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|
| MiniMax-M2 8B | MiniMax | 32768 | $1.65 | 61.7 |
| Zephyr Base | Hugging Face | 4096 | $1.26 | 59.5 |
| Pythia Instruct | EleutherAI | 8192 | $1.41 | 60.8 |
| Yi-Lightning 8B | 01.AI | 4096 | $1.16 | 59.2 |
| GPT-NeoX Base | EleutherAI | 16384 | $1.22 | 59.7 |
| Llama 4 Maverick 7B | Meta AI | 4096 | $1.52 | 61.9 |
| GLM-4.5 7B | Zhipu AI | 8192 | $1.32 | 60.2 |
Other benchmarks for GPT-NeoX Base
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| GPQA Diamond | 56.0 | 448 | 25th | |
| SWE-bench Verified | 47.8 | 437 | 27th | |
| HumanEval | 64.4 | 447 | 26th | |
| MATH-500 | 60.1 | 461 | 23th | |
| AIME 2025 | 46.3 | 486 | 19th | |
| LiveCodeBench | 49.1 | 455 | 24th | |
| IFEval | 70.8 | 443 | 26th | |
| TruthfulQA | 67.0 | 430 | 28th | |
| HellaSwag | 73.3 | 473 | 21th | |
| MMMU | 56.8 | 473 | 21th | |
| Arena Elo | 1256.7 | 479 | 20th |
FAQ
What score does GPT-NeoX Base get on MMLU-Pro?
GPT-NeoX Base scores 65.2 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.
How does GPT-NeoX Base rank on MMLU-Pro?
It ranks #450 of 600 models, in the 25th percentile. The leader is GPT-5.2 Pro at 91.6.
Is GPT-NeoX Base good at MMLU-Pro?
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 MMLU-Pro score calculated?
MMLU-Pro is a knowledge 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 Base cost?
GPT-NeoX Base costs $1.22 per million input tokens and $4.64 per million output tokens.