Claude Fable 5 outpaces GPT-5.5 by 13 points on FrontierMath's toughest problems

· Source: The Decoder · Field: Technology & Digital — Artificial Intelligence & Machine Learning · Depth: Intermediate, quick

Summary

Anthropic's new model, Claude Fable 5, has achieved top scores on the challenging FrontierMath benchmark, significantly outperforming OpenAI's GPT-5.5. Fable 5 recorded 87 percent accuracy across tiers 1 through 3 and an impressive 88 percent on the hardest tier 4 (v2). This marks a substantial improvement for Anthropic, as its predecessor, Opus 4.5, scored below 10 percent on tier 4 as recently as early 2026. In comparison, GPT-5.5 reached approximately 75 percent on the same tier, placing Fable 5 13 points ahead. All models were tested using Epoch AI's standard scaffold with maximum reasoning effort, confirming FrontierMath's status as a premier benchmark for AI math reasoning. These benchmark gains align with recent real-world examples of AI models solving complex mathematical problems.

Key takeaway

For AI Scientists and Machine Learning Engineers evaluating advanced reasoning models, you should consider Claude Fable 5's superior performance on the FrontierMath benchmark. Its 13-point lead over GPT-5.5 on tier 4 suggests a significant capability advantage for complex mathematical tasks. You should investigate Fable 5 for applications requiring high-accuracy math reasoning, potentially shifting your model selection strategy for research or development projects involving intricate problem-solving.

Key insights

Claude Fable 5 demonstrates a significant leap in AI mathematical reasoning, surpassing GPT-5.5 on a leading benchmark.

Principles

Method

The models were tested on Epoch AI's standard scaffold, employing maximum reasoning effort to assess performance on FrontierMath's tiers.

In practice

Topics

Best for: AI Architect, AI Engineer, Research Scientist, AI Scientist, Machine Learning Engineer, Tech Journalist

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Editorial summary, takeaway, and curation by AIssential. Original article published by The Decoder.