Flame Machine Learning - Evaluate: leaderboard

Metric: Accuracy (%; the paper's Bloom-level weighted accuracy on the Evaluate problems of the 970-problem textbook-grounded Machine Learning multiple-choice set, zero-shot, temperature 0). Source: arxiv.org. Saturation forecast: Estimated already saturated. 12 models tracked.

Top models

#ModelScore
1Gemini 3.1 Pro (Preview)98
2Claude Opus 4.690
3GPT-5.487
4GPT-4.1 Mini84
5Gemini 2.5 Flash Lite81
6Qwen 3 32B71
7Claude Haiku 4.568
8DeepSeek R1 Distill Qwen 32B62
9Qwen 3 8B52
10DeepSeek R1 Distill Qwen 14B51
11Gemma 3 27B (IT)47
12Gemma 3 12B (IT)40

Interactive version: theaggregate.ai/benchmark?slug=flame-machine-learning-evaluate · How It Works · Data refreshed daily, snapshot 2026-09-26.