SGLang Partners with Google Cloud to Bring High-Efficiency Inference to TPU
BanghuaZ · x · 2026-07-30
The SGLang team announced a partnership with Google Cloud to bring its inference framework to Google TPUs, offering a drop-in, cost-efficient path to frontier model inference.
Key Details:
- Broad Model Support: SGL-JAX already serves major open-source model families on the latest TPU generations, including Qwen, DeepSeek, Gemma, and Kimi, alongside multimodal models like Wan and Flux.
- Production Features: The TPU integration unlocks SGLang's core optimizations, including 5D parallelism, Radix Cache, HiCache, quantization, and speculative decoding.
- Seamless Migration: With the same API and features, teams already running SGLang can transition to TPUs with minimal friction using the PyTorch-native SGL-torchtpu path.
Related event: SGLang Joins Google Cloud and RadixArk to Bring TPU Inference(6 posts)→
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