Coding benchmark

# WeirdML leaderboard

> WeirdML results for 119 AI models, led by GPT-6 Astra at 93.6%. What the benchmark measures, who runs it, and a source for every score.
- Canonical page: https://noometry.com/benchmarks/weirdml
- Last updated: 2026-10-10
- Title: WeirdML Leaderboard (October 2026): Scores by Model

As of October 2026, GPT-6 Astra has the highest published WeirdML score on Noometry at 93.6%, out of 119 models with results.

Last verified October 10, 2026

## About WeirdML

Unusual machine-learning tasks the model must solve by writing and iterating on working PyTorch code.

- **Category:** [Coding](https://noometry.com/best/coding)
- **Introduced:** 2025
- **Format:** Code + execution
- **Unit:** Percent (random guessing ≈ 0%)
- **Official site:** [htihle.github.io](https://htihle.github.io/weirdml.html)

## Top 15 models

Top models on WeirdML

1.  GPT-6 Astra 93.6%
2.  Claude Fable 5.1 92.9%
3.  Claude Fable 5 91.9%
4.  Claude Opus 5 91.8%
5.  GPT-5.6 Sol 89.4%
6.  GPT-5.5 84.9%
7.  Gemini 3.8 Flash 84.8%
8.  Claude Opus 4.8 82.9%
9.  Kimi K3 82.6%
10.  GPT-5.3 Codex 79.3%
11.  GPT-5.6 Terra 78.3%
12.  Claude Opus 4.6 78%
13.  GPT-5.4 77.7%
14.  Claude Opus 4.7 76.4%
15.  GLM-5.3 75.4%
16.  707580859095

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

## All results

WeirdML results by model
| # | Model | Provider | Score | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- | --- |
| 1 | [GPT-6 Astra](https://noometry.com/models/gpt-6-astra) | [OpenAI](https://noometry.com/providers/openai) | 93.6% | promax | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 2 | [Claude Fable 5.1](https://noometry.com/models/claude-fable-5-1) | [Anthropic](https://noometry.com/providers/anthropic) | 92.9% | max | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 3 | [Claude Fable 5](https://noometry.com/models/claude-fable-5) | [Anthropic](https://noometry.com/providers/anthropic) | 91.9% | max | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 4 | [Claude Opus 5](https://noometry.com/models/claude-opus-5) | [Anthropic](https://noometry.com/providers/anthropic) | 91.8% | max | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 5 | [GPT-5.6 Sol](https://noometry.com/models/gpt-5-6-sol) | [OpenAI](https://noometry.com/providers/openai) | 89.4% | promax | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 6 | [GPT-5.5](https://noometry.com/models/gpt-5-5) | [OpenAI](https://noometry.com/providers/openai) | 84.9% | xhigh | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 7 | [Gemini 3.8 Flash](https://noometry.com/models/gemini-3-8-flash) |  [![](/logos/google.svg) Google](https://noometry.com/providers/google) | 84.8% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 8 | [Claude Opus 4.8](https://noometry.com/models/claude-opus-4-8) | [Anthropic](https://noometry.com/providers/anthropic) | 82.9% | xhigh | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 9 | [Kimi K3](https://noometry.com/models/kimi-k3) | [Moonshot AI](https://noometry.com/providers/moonshot) | 82.6% | max | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 10 | [GPT-5.3 Codex](https://noometry.com/models/gpt-5-3-codex) | [OpenAI](https://noometry.com/providers/openai) | 79.3% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 11 | [GPT-5.6 Terra](https://noometry.com/models/gpt-5-6-terra) | [OpenAI](https://noometry.com/providers/openai) | 78.3% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 12 | [Claude Opus 4.6](https://noometry.com/models/claude-opus-4-6) | [Anthropic](https://noometry.com/providers/anthropic) | 78% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 13 | [GPT-5.4](https://noometry.com/models/gpt-5-4) | [OpenAI](https://noometry.com/providers/openai) | 77.7% | xhigh | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 14 | [Claude Opus 4.7](https://noometry.com/models/claude-opus-4-7) | [Anthropic](https://noometry.com/providers/anthropic) | 76.4% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 15 | [GLM-5.3](https://noometry.com/models/glm-5-3) | [Z.ai (Zhipu)](https://noometry.com/providers/zai) | 75.4% | max | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 16 | [GPT-5.2](https://noometry.com/models/gpt-5-2) | [OpenAI](https://noometry.com/providers/openai) | 72.2% | xhigh | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 17 | [Gemini 3.1 Pro Preview](https://noometry.com/models/gemini-3-1-pro-preview) |  [![](/logos/google.svg) Google](https://noometry.com/providers/google) | 72.1% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 18 | [GLM-5.2](https://noometry.com/models/glm-5-2) | [Z.ai (Zhipu)](https://noometry.com/providers/zai) | 70.1% | max | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 19 | [Gemini 3 Pro](https://noometry.com/models/gemini-3-pro) |  [![](/logos/google.svg) Google](https://noometry.com/providers/google) | 69.9% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 20 | [Claude Sonnet 5](https://noometry.com/models/claude-sonnet-5) | [Anthropic](https://noometry.com/providers/anthropic) | 68.8% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 21 | [Grok 4.6](https://noometry.com/models/grok-4-6) | [xAI](https://noometry.com/providers/xai) | 67.3% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 22 | [DeepSeek V4 Pro](https://noometry.com/models/deepseek-v4-pro) |  [![](/logos/deepseek.svg) DeepSeek](https://noometry.com/providers/deepseek) | 66.2% | max | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 23 | [Claude Sonnet 4.6](https://noometry.com/models/claude-sonnet-4-6) | [Anthropic](https://noometry.com/providers/anthropic) | 66.1% | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 24 | [Claude Opus 4.5](https://noometry.com/models/claude-opus-4-5) | [Anthropic](https://noometry.com/providers/anthropic) | 63.7% | 16K | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 25 | [DeepSeek V4 Flash](https://noometry.com/models/deepseek-v4-flash) |  [![](/logos/deepseek.svg) DeepSeek](https://noometry.com/providers/deepseek) | 63% | max | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 26 | [Gemini 3.5 Flash](https://noometry.com/models/gemini-3-5-flash) |  [![](/logos/google.svg) Google](https://noometry.com/providers/google) | 62.6% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 27 | [Gemini 3 Flash Preview](https://noometry.com/models/gemini-3-flash-preview) |  [![](/logos/google.svg) Google](https://noometry.com/providers/google) | 61.6% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 28 | [GPT-5.6 Luna](https://noometry.com/models/gpt-5-6-luna) | [OpenAI](https://noometry.com/providers/openai) | 60.9% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 29 | [GPT-5.1](https://noometry.com/models/gpt-5-1) | [OpenAI](https://noometry.com/providers/openai) | 60.8% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 30 | [GPT-5](https://noometry.com/models/gpt-5) | [OpenAI](https://noometry.com/providers/openai) | 60.7% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 31 | [GPT-5 Pro](https://noometry.com/models/gpt-5-pro) | [OpenAI](https://noometry.com/providers/openai) | 60.4% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 32 | [GPT-5.4 mini](https://noometry.com/models/gpt-5-4-mini) | [OpenAI](https://noometry.com/providers/openai) | 60.3% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 33 | [Muse Spark 1.2](https://noometry.com/models/muse-spark-1-2) |  [![](/logos/meta.svg) Meta](https://noometry.com/providers/meta) | 60.3% | xhigh | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 34 | [o3-pro](https://noometry.com/models/o3-pro) | [OpenAI](https://noometry.com/providers/openai) | 58.2% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 35 | [GPT-5.4 Pro](https://noometry.com/models/gpt-5-4-pro) | [OpenAI](https://noometry.com/providers/openai) | 57.4% | none | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 36 | [GLM-5.1](https://noometry.com/models/glm-5-1) | [Z.ai (Zhipu)](https://noometry.com/providers/zai) | 57.1% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 37 | [Gemini 3.6 Flash](https://noometry.com/models/gemini-3-6-flash) |  [![](/logos/google.svg) Google](https://noometry.com/providers/google) | 56.1% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 38 | [Kimi K2.6](https://noometry.com/models/kimi-k2-6) | [Moonshot AI](https://noometry.com/providers/moonshot) | 55.9% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 39 | [GPT-5-Codex](https://noometry.com/models/gpt-5-codex) | [OpenAI](https://noometry.com/providers/openai) | 54.5% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 40 | [Kimi K2.7 Code](https://noometry.com/models/kimi-k2-7-code) | [Moonshot AI](https://noometry.com/providers/moonshot) | 54.1% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 41 | [Gemini 2.5 Pro](https://noometry.com/models/gemini-2-5-pro) |  [![](/logos/google.svg) Google](https://noometry.com/providers/google) | 54% | 16K | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 42 | [GPT-5 Mini](https://noometry.com/models/gpt-5-mini) | [OpenAI](https://noometry.com/providers/openai) | 52.7% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 43 | [o4-mini](https://noometry.com/models/o4-mini) | [OpenAI](https://noometry.com/providers/openai) | 52.6% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 44 | [o3](https://noometry.com/models/o3) | [OpenAI](https://noometry.com/providers/openai) | 52.4% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 45 | [Gemma 4 31B IT](https://noometry.com/models/gemma-4-31b-it) |  [![](/logos/google.svg) Google](https://noometry.com/providers/google) | 52.3% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 46 | [Grok 4.20 (Non-Reasoning)](https://noometry.com/models/grok-4-20) | [xAI](https://noometry.com/providers/xai) | 52.3% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 47 | [Gemini 3.1 Flash Lite](https://noometry.com/models/gemini-3-1-flash-lite) |  [![](/logos/google.svg) Google](https://noometry.com/providers/google) | 52.2% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 48 | [Grok 4.3](https://noometry.com/models/grok-4-3) | [xAI](https://noometry.com/providers/xai) | 49.9% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 49 | [GPT-5.4 nano](https://noometry.com/models/gpt-5-4-nano) | [OpenAI](https://noometry.com/providers/openai) | 49.2% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 50 | [GLM-5](https://noometry.com/models/glm-5) | [Z.ai (Zhipu)](https://noometry.com/providers/zai) | 48.2% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 51 | [gpt-oss-120b](https://noometry.com/models/gpt-oss-120b) | [OpenAI](https://noometry.com/providers/openai) | 48.2% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 52 | [gpt-oss-120b](https://noometry.com/models/gpt-oss-120b) | [OpenAI](https://noometry.com/providers/openai) | 48.2% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 53 | [Claude Sonnet 4.5](https://noometry.com/models/claude-sonnet-4-5) | [Anthropic](https://noometry.com/providers/anthropic) | 47.7% | 16K | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 54 | [o1](https://noometry.com/models/o1) | [OpenAI](https://noometry.com/providers/openai) | 47.6% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 55 | [DeepSeek-V3.2-Speciale](https://noometry.com/models/deepseek-v3-2-speciale) |  [![](/logos/deepseek.svg) DeepSeek](https://noometry.com/providers/deepseek) | 46.7% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 56 | [Grok 4.5](https://noometry.com/models/grok-4-5) | [xAI](https://noometry.com/providers/xai) | 46.4% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 57 | [Claude Sonnet 4](https://noometry.com/models/claude-sonnet-4) | [Anthropic](https://noometry.com/providers/anthropic) | 46.1% | 16K | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 58 | [Claude Opus 4.1](https://noometry.com/models/claude-opus-4-1) | [Anthropic](https://noometry.com/providers/anthropic) | 45.9% | 16K | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 59 | [Grok 4](https://noometry.com/models/grok-4) | [xAI](https://noometry.com/providers/xai) | 45.7% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 60 | [Kimi K2.5](https://noometry.com/models/kimi-k2-5) | [Moonshot AI](https://noometry.com/providers/moonshot) | 45.6% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 61 | [Claude Haiku 4.5](https://noometry.com/models/claude-haiku-4-5) | [Anthropic](https://noometry.com/providers/anthropic) | 45.4% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 62 | [Claude Opus 4](https://noometry.com/models/claude-opus-4) | [Anthropic](https://noometry.com/providers/anthropic) | 43.7% | 16K | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 63 | [Mistral Medium](https://noometry.com/models/mistral-medium) |  [![](/logos/mistral.svg) Mistral AI](https://noometry.com/providers/mistral) | 43.7% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 64 | [o3-mini](https://noometry.com/models/o3-mini) | [OpenAI](https://noometry.com/providers/openai) | 43.7% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 65 | [Nemotron 3 Ultra](https://noometry.com/models/nemotron-3-ultra) |  [![](/logos/nvidia.svg) NVIDIA](https://noometry.com/providers/nvidia) | 43.5% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 66 | [Mercury 2](https://noometry.com/models/mercury-2) | [Inception](https://noometry.com/providers/inception) | 43.2% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 67 | [Grok 4 Fast](https://noometry.com/models/grok-4-fast) | [xAI](https://noometry.com/providers/xai) | 42.9% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 68 | [Kimi K2 (Jul 2025)](https://noometry.com/models/kimi-k2) | [Moonshot AI](https://noometry.com/providers/moonshot) | 42.8% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 69 | [Grok-3 mini](https://noometry.com/models/grok-3-mini) | [xAI](https://noometry.com/providers/xai) | 42.6% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 70 | [Grok-3 mini](https://noometry.com/models/grok-3-mini) | [xAI](https://noometry.com/providers/xai) | 42.6% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 71 | [Gemini 2.5 Flash](https://noometry.com/models/gemini-2-5-flash) |  [![](/logos/google.svg) Google](https://noometry.com/providers/google) | 41.9% | 16k | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 72 | [DeepSeek-R1](https://noometry.com/models/deepseek-r1) |  [![](/logos/deepseek.svg) DeepSeek](https://noometry.com/providers/deepseek) | 41.6% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 73 | [Qwen3-Coder 480B-A35B Instruct](https://noometry.com/models/qwen3-coder-480b-a35b-instruct) |  [![](/logos/alibaba.svg) Alibaba (Qwen)](https://noometry.com/providers/alibaba) | 41.2% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 74 | [Qwen3 235B-A22B](https://noometry.com/models/qwen3-235b-a22b) |  [![](/logos/alibaba.svg) Alibaba (Qwen)](https://noometry.com/providers/alibaba) | 41% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 75 | [gpt-oss-20b](https://noometry.com/models/gpt-oss-20b) | [OpenAI](https://noometry.com/providers/openai) | 40.9% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 76 | [GLM-4.5](https://noometry.com/models/glm-4-5) | [Z.ai (Zhipu)](https://noometry.com/providers/zai) | 40.6% | thinking | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 77 | [Claude 3.5 Sonnet](https://noometry.com/models/claude-3-5-sonnet) | [Anthropic](https://noometry.com/providers/anthropic) | 40% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 78 | [Qwen3.5 27B](https://noometry.com/models/qwen3-5-27b) |  [![](/logos/alibaba.svg) Alibaba (Qwen)](https://noometry.com/providers/alibaba) | 39.5% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 79 | [DeepSeek-V3.2-Exp](https://noometry.com/models/deepseek-v3-2-exp) |  [![](/logos/deepseek.svg) DeepSeek](https://noometry.com/providers/deepseek) | 39.5% | thinking | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 80 | [GPT-4.5](https://noometry.com/models/gpt-4-5) | [OpenAI](https://noometry.com/providers/openai) | 39.4% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 81 | [GPT-4.1](https://noometry.com/models/gpt-4-1) | [OpenAI](https://noometry.com/providers/openai) | 39% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 82 | [Gemini 3.5 Flash Lite](https://noometry.com/models/gemini-3-5-flash-lite) |  [![](/logos/google.svg) Google](https://noometry.com/providers/google) | 39% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 83 | [DeepSeek-V3.1](https://noometry.com/models/deepseek-v3-1) |  [![](/logos/deepseek.svg) DeepSeek](https://noometry.com/providers/deepseek) | 38.4% | thinking | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 84 | [GPT-5 Nano](https://noometry.com/models/gpt-5-nano) | [OpenAI](https://noometry.com/providers/openai) | 38.1% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 85 | [Nemotron 3 Super](https://noometry.com/models/nemotron-3-super) |  [![](/logos/nvidia.svg) NVIDIA](https://noometry.com/providers/nvidia) | 38% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 86 | [GPT-4.1 mini](https://noometry.com/models/gpt-4-1-mini) | [OpenAI](https://noometry.com/providers/openai) | 37.6% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 87 | [Grok 3](https://noometry.com/models/grok-3) | [xAI](https://noometry.com/providers/xai) | 37.2% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 88 | [MiniMax-M2.7](https://noometry.com/models/minimax-m2-7) |  [![](/logos/minimax.svg) MiniMax](https://noometry.com/providers/minimax) | 37% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 89 | [o1-mini](https://noometry.com/models/o1-mini) | [OpenAI](https://noometry.com/providers/openai) | 36.3% | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 90 | [DeepSeek-V3](https://noometry.com/models/deepseek-v3) |  [![](/logos/deepseek.svg) DeepSeek](https://noometry.com/providers/deepseek) | 36.1% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 91 | [Gemini 2.5 Flash-Lite](https://noometry.com/models/gemini-2-5-flash-lite) |  [![](/logos/google.svg) Google](https://noometry.com/providers/google) | 35.2% | 16K | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 92 | [Gemma 4 26B A4B IT](https://noometry.com/models/gemma-4-26b-a4b-it) |  [![](/logos/google.svg) Google](https://noometry.com/providers/google) | 35.2% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 93 | [Qwen3.6 35B-A3B](https://noometry.com/models/qwen3-6-35b-a3b) |  [![](/logos/alibaba.svg) Alibaba (Qwen)](https://noometry.com/providers/alibaba) | 34.5% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 94 | [Qwen3 Coder Next](https://noometry.com/models/qwen3-coder-next) |  [![](/logos/alibaba.svg) Alibaba (Qwen)](https://noometry.com/providers/alibaba) | 34.4% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 95 | [Inkling](https://noometry.com/models/inkling) | [T Thinking Machines Lab](https://noometry.com/providers/thinking-machines) | 32.3% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 96 | [Claude 3.5 Haiku](https://noometry.com/models/claude-3-5-haiku) | [Anthropic](https://noometry.com/providers/anthropic) | 30.7% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 97 | [Qwen3-30B-A3B](https://noometry.com/models/qwen3-30b-a3b) |  [![](/logos/alibaba.svg) Alibaba (Qwen)](https://noometry.com/providers/alibaba) | 29.8% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 98 | [Gemini 2.0 Flash (Feb 2025)](https://noometry.com/models/gemini-2-0-flash) |  [![](/logos/google.svg) Google](https://noometry.com/providers/google) | 25.8% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 99 | [GPT-4o](https://noometry.com/models/gpt-4o) | [OpenAI](https://noometry.com/providers/openai) | 25.1% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 100 | [Gemini 1.5 Flash (May 2024)](https://noometry.com/models/gemini-1-5-flash) |  [![](/logos/google.svg) Google](https://noometry.com/providers/google) | 24.9% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 101 | [Llama 4 Maverick](https://noometry.com/models/llama-4-maverick) |  [![](/logos/meta.svg) Meta](https://noometry.com/providers/meta) | 24.5% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 102 | [Grok-2 (Dec 2024)](https://noometry.com/models/grok-2) | [xAI](https://noometry.com/providers/xai) | 22.2% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 103 | [Gemini 1.5 Pro (May 2024)](https://noometry.com/models/gemini-1-5-pro) |  [![](/logos/google.svg) Google](https://noometry.com/providers/google) | 22.2% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 104 | [Llama 3.1-405B](https://noometry.com/models/llama-3-1-405b) |  [![](/logos/meta.svg) Meta](https://noometry.com/providers/meta) | 21.4% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 105 | [Claude 3 Opus](https://noometry.com/models/claude-3-opus) | [Anthropic](https://noometry.com/providers/anthropic) | 19.2% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 106 | [GPT-4.1 nano](https://noometry.com/models/gpt-4-1-nano) | [OpenAI](https://noometry.com/providers/openai) | 19% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 107 | [GPT-4 Turbo](https://noometry.com/models/gpt-4-turbo) | [OpenAI](https://noometry.com/providers/openai) | 18% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 108 | [Qwen2.5 72B Instruct](https://noometry.com/models/qwen2-5-72b-instruct) |  [![](/logos/alibaba.svg) Alibaba (Qwen)](https://noometry.com/providers/alibaba) | 16% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 109 | [Llama-3.3-70B-Instruct](https://noometry.com/models/llama-3-3-70b-instruct) |  [![](/logos/meta.svg) Meta](https://noometry.com/providers/meta) | 14.4% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 110 | [GPT-4](https://noometry.com/models/gpt-4) | [OpenAI](https://noometry.com/providers/openai) | 12.4% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 111 | [GPT-4o mini](https://noometry.com/models/gpt-4o-mini) | [OpenAI](https://noometry.com/providers/openai) | 11.8% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 112 | [Qwen2-72B](https://noometry.com/models/qwen2-72b) |  [![](/logos/alibaba.svg) Alibaba (Qwen)](https://noometry.com/providers/alibaba) | 11.3% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 113 | [Claude 3 Sonnet](https://noometry.com/models/claude-3-sonnet) | [Anthropic](https://noometry.com/providers/anthropic) | 10.2% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 114 | [Claude 3 Haiku](https://noometry.com/models/claude-3-haiku) | [Anthropic](https://noometry.com/providers/anthropic) | 9.8% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 115 | [Llama 3.1-70B](https://noometry.com/models/llama-3-1-70b) |  [![](/logos/meta.svg) Meta](https://noometry.com/providers/meta) | 9% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 116 | [Claude 2.1](https://noometry.com/models/claude-2-1) | [Anthropic](https://noometry.com/providers/anthropic) | 7.1% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 117 | [GPT-3.5-turbo](https://noometry.com/models/gpt-3-5-turbo) | [OpenAI](https://noometry.com/providers/openai) | 3.5% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 118 | [Mixtral 8x22B](https://noometry.com/models/mixtral-8x22b) |  [![](/logos/mistral.svg) Mistral AI](https://noometry.com/providers/mistral) | 3.2% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 119 | [Llama 3.1-8B](https://noometry.com/models/llama-3-1-8b) |  [![](/logos/meta.svg) Meta](https://noometry.com/providers/meta) | 1.7% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |

## Compare the leaders

-   [GPT-6 Astra vs Claude Fable 5.1](https://noometry.com/compare/claude-fable-5-1-vs-gpt-6-astra)
-   [GPT-6 Astra vs Claude Fable 5](https://noometry.com/compare/claude-fable-5-vs-gpt-6-astra)
-   [GPT-6 Astra vs Claude Opus 5](https://noometry.com/compare/claude-opus-5-vs-gpt-6-astra)
-   [GPT-6 Astra vs GPT-5.6 Sol](https://noometry.com/compare/gpt-5-6-sol-vs-gpt-6-astra)
-   [Claude Fable 5.1 vs Claude Fable 5](https://noometry.com/compare/claude-fable-5-vs-claude-fable-5-1)
-   [Claude Fable 5.1 vs Claude Opus 5](https://noometry.com/compare/claude-fable-5-1-vs-claude-opus-5)

## Other coding benchmarks

-   [SWE-bench Verified](https://noometry.com/benchmarks/swe-bench-verified)
-   [DeepSWE](https://noometry.com/benchmarks/deepswe)
-   [FrontierCode](https://noometry.com/benchmarks/frontiercode)
-   [SWE-bench Verified (bash only)](https://noometry.com/benchmarks/swe-bench-bash-only)
-   [Aider Polyglot](https://noometry.com/benchmarks/aider-polyglot)
-   [LMArena WebDev](https://noometry.com/benchmarks/arena-webdev)
-   [CursorBench](https://noometry.com/benchmarks/cursorbench)
-   [SWE-bench Multilingual](https://noometry.com/benchmarks/swe-bench-multilingual)
-   [FrontierSWE](https://noometry.com/benchmarks/frontierswe)
-   [SciCode](https://noometry.com/benchmarks/scicode)
-   [GSO](https://noometry.com/benchmarks/gso-bench)
-   [LMArena Coding](https://noometry.com/benchmarks/arena-coding)

## Frequently asked questions

### What does WeirdML measure?

Unusual machine-learning tasks the model must solve by writing and iterating on working PyTorch code.

### Which model has the highest WeirdML score?

As of October 2026, GPT-6 Astra has the highest published WeirdML score on Noometry at 93.6%, out of 119 models with results.

### What is the best open-weight model on WeirdML?

Kimi K3 has the highest WeirdML accuracy among open-weight models at 82.6%, ranking 9 of 119 overall.

### Cite this page

Noometry. (2026). WeirdML leaderboard. Retrieved October 10, 2026, from https://noometry.com/benchmarks/weirdml

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