Great to see! Later this year, RadixArk will roll out SGL-torchtpu as an additional @radixark PyTorch-native TPU backend, featuring eager execution, @PyTorch ecosystem compatibility, and MPMD support. It will let any AI researcher or engineer in the industry run LLMs with
RadixArk and Google Cloud are joining forces with the SGLang community to make TPU a drop-in, cost-efficient path to frontier inference.
SGL-JAX already serves the major open model families on the latest TPU generations: Gemma, Qwen, DeepSeek, GLM, Kimi, Ling, MiniMax, MiMo,
FBTriton is the Triton repo where Meta develops its experimental GPU optimization solutions (including TLX/torchTLX and autoWS). It has served as an optimization runway for Meta engineers and external partners, including NVIDIA, AMD, and academic collaborators, to co-design
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