Math benchmark

# Omni-MATH leaderboard

> Omni-MATH results for 57 AI models, led by GPT-5 Mini at 72.2%. What the benchmark measures, who runs it, and a source for every score.
- Canonical page: https://noometry.com/benchmarks/omni-math
- Last updated: 2026-10-10
- Title: Omni-MATH Leaderboard (October 2026): Scores by Model

As of October 2026, GPT-5 Mini has the highest published Omni-MATH score on Noometry at 72.2%, out of 57 models with results.

Last verified October 10, 2026

## About Omni-MATH

Olympiad-level problems across 33 sub-domains and ten difficulty levels. HELM Capabilities run.

- **Category:** [Math](https://noometry.com/best/math)
- **Introduced:** 2024
- **Size:** 4,428 problems
- **Format:** Final answer
- **Unit:** Percent (random guessing ≈ 0%)
- **Official site:** [crfm.stanford.edu](https://crfm.stanford.edu/helm/capabilities/latest/)

## Top 15 models

Top models on Omni-MATH

1.  GPT-5 Mini 72.2%
2.  o4-mini 72%
3.  Qwen3 235B-A22B 71.8%
4.  o3 71.4%
5.  gpt-oss-120b 68.8%
6.  Kimi K2 (Jul 2025) 65.4%
7.  GPT-5 64.7%
8.  Claude Opus 4 61.6%
9.  Grok 4 60.3%
10.  Claude Sonnet 4 60.2%
11.  gpt-oss-20b 56.5%
12.  Claude Haiku 4.5 56.1%
13.  Gemini 3 Pro 55.5%
14.  Claude Sonnet 4.5 55.3%
15.  GPT-5 Nano 54.6%
16.  505560657075

Sponsored placements are available on pages like this one. [Advertise on Noometry](https://noometry.com/advertise)

## All results

Omni-MATH results by model
| # | Model | Provider | Score | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- | --- |
| 1 | [GPT-5 Mini](https://noometry.com/models/gpt-5-mini) | [OpenAI](https://noometry.com/providers/openai) | 72.2% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 2 | [o4-mini](https://noometry.com/models/o4-mini) | [OpenAI](https://noometry.com/providers/openai) | 72% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 3 | [Qwen3 235B-A22B](https://noometry.com/models/qwen3-235b-a22b) |  [![](/logos/alibaba.svg) Alibaba (Qwen)](https://noometry.com/providers/alibaba) | 71.8% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 4 | [o3](https://noometry.com/models/o3) | [OpenAI](https://noometry.com/providers/openai) | 71.4% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 5 | [gpt-oss-120b](https://noometry.com/models/gpt-oss-120b) | [OpenAI](https://noometry.com/providers/openai) | 68.8% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 6 | [Kimi K2 (Jul 2025)](https://noometry.com/models/kimi-k2) | [Moonshot AI](https://noometry.com/providers/moonshot) | 65.4% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 7 | [GPT-5](https://noometry.com/models/gpt-5) | [OpenAI](https://noometry.com/providers/openai) | 64.7% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 8 | [Claude Opus 4](https://noometry.com/models/claude-opus-4) | [Anthropic](https://noometry.com/providers/anthropic) | 61.6% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 9 | [Grok 4](https://noometry.com/models/grok-4) | [xAI](https://noometry.com/providers/xai) | 60.3% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 10 | [Claude Sonnet 4](https://noometry.com/models/claude-sonnet-4) | [Anthropic](https://noometry.com/providers/anthropic) | 60.2% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 11 | [gpt-oss-20b](https://noometry.com/models/gpt-oss-20b) | [OpenAI](https://noometry.com/providers/openai) | 56.5% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 12 | [Claude Haiku 4.5](https://noometry.com/models/claude-haiku-4-5) | [Anthropic](https://noometry.com/providers/anthropic) | 56.1% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 13 | [Gemini 3 Pro](https://noometry.com/models/gemini-3-pro) |  [![](/logos/google.svg) Google](https://noometry.com/providers/google) | 55.5% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 14 | [Claude Sonnet 4.5](https://noometry.com/models/claude-sonnet-4-5) | [Anthropic](https://noometry.com/providers/anthropic) | 55.3% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 15 | [GPT-5 Nano](https://noometry.com/models/gpt-5-nano) | [OpenAI](https://noometry.com/providers/openai) | 54.6% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 16 | [GPT-4.1 mini](https://noometry.com/models/gpt-4-1-mini) | [OpenAI](https://noometry.com/providers/openai) | 49.1% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 17 | [Gemini 2.5 Flash-Lite](https://noometry.com/models/gemini-2-5-flash-lite) |  [![](/logos/google.svg) Google](https://noometry.com/providers/google) | 48% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 18 | [GPT-4.1](https://noometry.com/models/gpt-4-1) | [OpenAI](https://noometry.com/providers/openai) | 47.1% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 19 | [Qwen3-Next 80B-A3B Instruct](https://noometry.com/models/qwen3-next-80b-a3b-instruct) |  [![](/logos/alibaba.svg) Alibaba (Qwen)](https://noometry.com/providers/alibaba) | 46.7% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 20 | [Grok 3](https://noometry.com/models/grok-3) | [xAI](https://noometry.com/providers/xai) | 46.4% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 21 | [GPT-5.1](https://noometry.com/models/gpt-5-1) | [OpenAI](https://noometry.com/providers/openai) | 46.4% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 22 | [Gemini 2.0 Flash (Feb 2025)](https://noometry.com/models/gemini-2-0-flash) |  [![](/logos/google.svg) Google](https://noometry.com/providers/google) | 45.9% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 23 | [DeepSeek-R1](https://noometry.com/models/deepseek-r1) |  [![](/logos/deepseek.svg) DeepSeek](https://noometry.com/providers/deepseek) | 42.4% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 24 | [Llama 4 Maverick](https://noometry.com/models/llama-4-maverick) |  [![](/logos/meta.svg) Meta](https://noometry.com/providers/meta) | 42.2% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 25 | [Gemini 2.5 Pro](https://noometry.com/models/gemini-2-5-pro) |  [![](/logos/google.svg) Google](https://noometry.com/providers/google) | 41.6% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 26 | [DeepSeek-V3](https://noometry.com/models/deepseek-v3) |  [![](/logos/deepseek.svg) DeepSeek](https://noometry.com/providers/deepseek) | 40.3% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 27 | [GLM-4.5-Air](https://noometry.com/models/glm-4-5-air) | [Z.ai (Zhipu)](https://noometry.com/providers/zai) | 39.1% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 28 | [Gemini 2.5 Flash](https://noometry.com/models/gemini-2-5-flash) |  [![](/logos/google.svg) Google](https://noometry.com/providers/google) | 38.5% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 29 | [Gemini 2.0 Flash-Lite](https://noometry.com/models/gemini-2-0-flash-lite) |  [![](/logos/google.svg) Google](https://noometry.com/providers/google) | 37.4% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 30 | [Llama 4 Scout](https://noometry.com/models/llama-4-scout) |  [![](/logos/meta.svg) Meta](https://noometry.com/providers/meta) | 37.3% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 31 | [GPT-4.1 nano](https://noometry.com/models/gpt-4-1-nano) | [OpenAI](https://noometry.com/providers/openai) | 36.7% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 32 | [Gemini 1.5 Pro (May 2024)](https://noometry.com/models/gemini-1-5-pro) |  [![](/logos/google.svg) Google](https://noometry.com/providers/google) | 36.4% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 33 | [Nova Premier 1.0](https://noometry.com/models/nova-premier-1-0) | [Amazon](https://noometry.com/providers/amazon) | 35% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 34 | [Claude 3.7 Sonnet](https://noometry.com/models/claude-3-7-sonnet) | [Anthropic](https://noometry.com/providers/anthropic) | 33% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 35 | [Qwen2.5 72B Instruct](https://noometry.com/models/qwen2-5-72b-instruct) |  [![](/logos/alibaba.svg) Alibaba (Qwen)](https://noometry.com/providers/alibaba) | 33% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 36 | [Grok-3 mini](https://noometry.com/models/grok-3-mini) | [xAI](https://noometry.com/providers/xai) | 31.8% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 37 | [Gemini 1.5 Flash (May 2024)](https://noometry.com/models/gemini-1-5-flash) |  [![](/logos/google.svg) Google](https://noometry.com/providers/google) | 30.4% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 38 | [Granite 4.0 H Small](https://noometry.com/models/ibm-granite-h-small) | [IBM](https://noometry.com/providers/ibm) | 29.6% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 39 | [Qwen2.5 7B Instruct](https://noometry.com/models/qwen2-5-7b-instruct) |  [![](/logos/alibaba.svg) Alibaba (Qwen)](https://noometry.com/providers/alibaba) | 29.4% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 40 | [GPT-4o](https://noometry.com/models/gpt-4o) | [OpenAI](https://noometry.com/providers/openai) | 29.3% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 41 | [Mistral Large](https://noometry.com/models/mistral-large) |  [![](/logos/mistral.svg) Mistral AI](https://noometry.com/providers/mistral) | 28.1% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 42 | [GPT-4o mini](https://noometry.com/models/gpt-4o-mini) | [OpenAI](https://noometry.com/providers/openai) | 28% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 43 | [Claude 3.5 Sonnet](https://noometry.com/models/claude-3-5-sonnet) | [Anthropic](https://noometry.com/providers/anthropic) | 27.6% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 44 | [Llama 3.1-405B](https://noometry.com/models/llama-3-1-405b) |  [![](/logos/meta.svg) Meta](https://noometry.com/providers/meta) | 24.9% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 45 | [Mistral Small 3.1](https://noometry.com/models/mistral-small-3-1) |  [![](/logos/mistral.svg) Mistral AI](https://noometry.com/providers/mistral) | 24.8% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 46 | [Amazon Nova Pro](https://noometry.com/models/amazon-nova-pro) | [Amazon](https://noometry.com/providers/amazon) | 24.2% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 47 | [Amazon Nova Lite](https://noometry.com/models/amazon-nova-lite) | [Amazon](https://noometry.com/providers/amazon) | 23.3% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 48 | [Claude 3.5 Haiku](https://noometry.com/models/claude-3-5-haiku) | [Anthropic](https://noometry.com/providers/anthropic) | 22.4% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 49 | [Amazon Nova Micro](https://noometry.com/models/amazon-nova-micro) | [Amazon](https://noometry.com/providers/amazon) | 21.4% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 50 | [Llama 3.1-70B](https://noometry.com/models/llama-3-1-70b) |  [![](/logos/meta.svg) Meta](https://noometry.com/providers/meta) | 21% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 51 | [Granite 4.0 Micro](https://noometry.com/models/granite-4-0-micro) | [IBM](https://noometry.com/providers/ibm) | 20.9% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 52 | [Mixtral 8x22B](https://noometry.com/models/mixtral-8x22b) |  [![](/logos/mistral.svg) Mistral AI](https://noometry.com/providers/mistral) | 16.3% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 53 | [Olmo 2 0325 32b Instruct](https://noometry.com/models/olmo-2-0325-32b-instruct) |  [![](/logos/ai2.svg) Allen Institute for AI (Ai2)](https://noometry.com/providers/ai2) | 16.1% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 54 | [OLMo 2 Furious 13B](https://noometry.com/models/olmo-2-furious-13b) |  [![](/logos/ai2.svg) Allen Institute for AI (Ai2)](https://noometry.com/providers/ai2) | 15.6% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 55 | [Llama 3.1-8B](https://noometry.com/models/llama-3-1-8b) |  [![](/logos/meta.svg) Meta](https://noometry.com/providers/meta) | 13.7% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 56 | [Mixtral 8x7B](https://noometry.com/models/mixtral-8x7b) |  [![](/logos/mistral.svg) Mistral AI](https://noometry.com/providers/mistral) | 10.5% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| 57 | [Mistral](https://noometry.com/models/mistral) |  [![](/logos/mistral.svg) Mistral AI](https://noometry.com/providers/mistral) | 7.2% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |

## Compare the leaders

-   [GPT-5 Mini vs o4-mini](https://noometry.com/compare/gpt-5-mini-vs-o4-mini)
-   [GPT-5 Mini vs Qwen3 235B-A22B](https://noometry.com/compare/gpt-5-mini-vs-qwen3-235b-a22b)
-   [GPT-5 Mini vs o3](https://noometry.com/compare/gpt-5-mini-vs-o3)
-   [GPT-5 Mini vs gpt-oss-120b](https://noometry.com/compare/gpt-5-mini-vs-gpt-oss-120b)
-   [o4-mini vs Qwen3 235B-A22B](https://noometry.com/compare/o4-mini-vs-qwen3-235b-a22b)
-   [o4-mini vs o3](https://noometry.com/compare/o3-vs-o4-mini)

## Other math benchmarks

-   [FrontierMath (Tiers 1-3)](https://noometry.com/benchmarks/frontiermath)
-   [FrontierMath Tier 4](https://noometry.com/benchmarks/frontiermath-tier-4)
-   [MathArena Final-Answer Competitions](https://noometry.com/benchmarks/matharena)
-   [OTIS Mock AIME 2024-2025](https://noometry.com/benchmarks/otis-mock-aime)
-   [ProofBench](https://noometry.com/benchmarks/proofbench)
-   [LMArena Math](https://noometry.com/benchmarks/arena-math)
-   [LiveBench Math](https://noometry.com/benchmarks/livebench-math)
-   [MATH Level 5](https://noometry.com/benchmarks/math-level-5)
-   [FrontierMath (Feb 2025 set)](https://noometry.com/benchmarks/frontiermath-2025-02) (reference)
-   [FrontierMath Erdős](https://noometry.com/benchmarks/frontiermath-erdos) (reference)
-   [FrontierMath Tier 4 (v1)](https://noometry.com/benchmarks/frontiermath-tier-4-v1) (reference)
-   [GSM8K](https://noometry.com/benchmarks/gsm8k) (reference)

## Frequently asked questions

### What does Omni-MATH measure?

Olympiad-level problems across 33 sub-domains and ten difficulty levels. HELM Capabilities run.

### Which model has the highest Omni-MATH score?

As of October 2026, GPT-5 Mini has the highest published Omni-MATH score on Noometry at 72.2%, out of 57 models with results.

### What is the best open-weight model on Omni-MATH?

Qwen3 235B-A22B has the highest Omni-MATH accuracy among open-weight models at 71.8%, ranking 3 of 57 overall.

### Cite this page

Noometry. (2026). Omni-MATH leaderboard. Retrieved October 10, 2026, from https://noometry.com/benchmarks/omni-math

Quote Noometry with a link back to this page. It is also available in [Markdown](https://noometry.com/md/benchmarks/omni-math.md).