Flame Machine Learning - Analyze: leaderboard

Textbook-grounded five-option multiple-choice problems at the Bloom Analyze level (questions that ask the model to break a problem into parts and relate them) from the 970-problem Flame Machine Learning benchmark (Islam et al., 2026). The paper's Bloom-level weighted accuracy in percent, zero-shot at temperature 0; higher is better.

Metric: Accuracy (%; the paper's Bloom-level weighted accuracy on the Analyze 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

#ModelScoreOverall rank
1Gemini 3.1 Pro (Preview)100#91
2Claude Opus 4.690#100
3GPT-5.486#121
4GPT-4.1 Mini85#775
5Qwen 3 32B76#960
6Gemini 2.5 Flash Lite76#958
7DeepSeek R1 Distill Qwen 32B63#1780
8Claude Haiku 4.561#568
9DeepSeek R1 Distill Qwen 14B48#2594
10Qwen 3 8B47#1838
11Gemma 3 27B (IT)43#1306
12Gemma 3 12B (IT)33#1849

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=flame-machine-learning-analyze · How It Works · Data refreshed daily, snapshot 2026-11-12.