Claude Optimized 36 Biological Models in Less Than 4 Weeks, Delivering an Average Speed Increase of Around 4 Times.
58 minutes ago
Beating AI Express: Anthropic has leveraged Claude to optimize the performance of 36 open-source biological models. In under four weeks, these models achieved an average speedup of around 4x, covering tasks including protein structure prediction, protein design, and genomic analysis. All related optimization code has been open-sourced. Claude did more than just modify Python code; it also wrote custom GPU kernels like FlashPairformer, directly boosting GPU computing efficiency at the low level. In official tests, some previously time-consuming calculations sped up by up to 3.2x. For different models, Claude individually identified bottlenecks, eliminating redundant computations or pre-caching frequently used data. The entire process was overseen by two Anthropic biological modeling researchers, neither of whom had prior experience in inference optimization or kernel engineering. Even when requiring identical results before and after optimization, the models still delivered an average speedup of roughly 1.6x; when allowing minor, normal-range differences in model outputs, the average speedup reached about 4x. Previously, a single protein design experiment at Anthropic required up to ~2,500 H100 GPU hours per target. After optimization, one H200 can achieve comparable results in 24 hours, with total costs of around $150 for the GPU plus Claude. Experiments that once needed thousands of GPU hours can now be completed in roughly one day.
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