OpenAI's Internal Model Solves Decade-Old Math Problems for Under $2,000 Each
Simon Willison · rss · 2026-08-02
Following Anthropic's recent cryptography work, OpenAI demonstrated the mathematical prowess of its next-generation internal model (codenamed Astra / GPT-5.6). They tasked the model with solving ten mathematical problems that had seen no progress for at least a decade, claiming the inference token cost was less than $2,000 each.
Demonstrating high transparency, OpenAI released an accompanying paper and open-sourced the Lean 4 formalizations of their results on GitHub. This breakthrough has caused a collective "Deep Blue" moment among mathematicians, echoing Terence Tao's vision of a "big mathematics" era characterized by massive human-AI collaboration.
More from AGI Musings
- AI's Impact on Professional Identity: Biologist Leaves Science — matdryhurst · 2026-08-02
- Deep Learning is Empirical: AI Takeoff is Compute-Bound, Not Intelligence-Bound — bronzeagepapi · 2026-08-02
- Prediction: Once AI Surpasses Humans in Math, We'll Get Useful ML Theory — kjgeras · 2026-08-02
- Safety Experts Warn: The World Will Fumble Its Way Into AI Disaster — davidmanheim · 2026-08-02
- Economists Skeptical: AI Faces Data Hurdles in Macroeconomics — soumitrashukla9 · 2026-08-02
- Why Is the LLM Transformation of Mathematics Going Unnoticed? — davidcrawshaw · 2026-08-02