Zephyr Instruct on MATH-500: score, rank and what it means
Zephyr Instruct scores 62.9 on MATH-500, placing it #437 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.
Score distribution
The chart shows the top 10 models on MATH-500, with Zephyr Instruct highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg 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, Zephyr Instruct sits at #437 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 33.8 points. The median model in this index scores 76.0, which puts Zephyr Instruct below the midpoint.
Hugging Face models average 53.8 on this benchmark. Zephyr Instruct is 9.1 points above that provider line, so it is a stronger result than the average Hugging Face model.
Among open-weight models, the average is 70.8. Zephyr Instruct is 7.9 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 62.9 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 $1.66 per million input tokens, Zephyr Instruct 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.
| Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|
| GLM-4.5 7B | Zhipu AI | 8192 | $1.32 | 60.2 |
| Mistral Large 3 7B | Mistral AI | 32768 | $1.44 | 61.1 |
| Firefunction Mini | Fireworks AI | 32768 | $4.63 | 63.2 |
| GPT-NeoX Chat | EleutherAI | 16384 | $1.49 | 60.1 |
| Zephyr Instruct | Hugging Face | 4096 | $1.66 | 62.4 |
| Qwen3 8B | Alibaba Cloud | 8192 | $1.66 | 61.9 |
| Llama 4 Scout 8B | Meta AI | 8192 | $1.46 | 61.2 |
Other benchmarks for Zephyr Instruct
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 65.8 | 440 | 27th | |
| GPQA Diamond | 59.3 | 412 | 31th | |
| SWE-bench Verified | 51.3 | 412 | 31th | |
| HumanEval | 65.1 | 441 | 27th | |
| AIME 2025 | 56.9 | 405 | 33th | |
| LiveCodeBench | 50.0 | 449 | 25th | |
| IFEval | 71.8 | 433 | 28th | |
| TruthfulQA | 66.4 | 440 | 27th | |
| HellaSwag | 75.7 | 431 | 28th | |
| MMMU | 60.9 | 422 | 30th | |
| Arena Elo | 1301.5 | 416 | 31th |
FAQ
What score does Zephyr Instruct get on MATH-500?
Zephyr Instruct scores 62.9 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.
How does Zephyr Instruct rank on MATH-500?
It ranks #437 of 600 models, in the 27th percentile. The leader is GPT-5.2 Max at 96.7.
Is Zephyr Instruct 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 Zephyr Instruct cost?
Zephyr Instruct costs $1.66 per million input tokens and $6.50 per million output tokens.