XStack: A Benchmark for ML Repo Migration
arXiv — cs.AI · Linrong Cai, Taiming Lu, Haozhe Chen, Zhuang Liu · Published on Readzer
Summary
The paper introduces XStack, a benchmark for evaluating AI agents on migrating machine learning repositories between PyTorch on NVIDIA GPUs and JAX on Google TPUs. Agents receive a PyTorch repository and a clean TPU machine, and must deliver a JAX repository that meets grading criteria based on the source repository's published result. Results show that migration remains unreliable, with Claude Opus 5 passing 75%, GPT-5.6-sol 45%, and all other agents at most 40%.
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Why it matters by industry
- Artificial intelligence
This benchmark directly addresses cross-framework and cross-hardware migration, a key challenge for AI model deployment and portability, relevant to model and agent development.