The Large Model Systems Organization develops large models and systems that are open, accessible, and scalable.
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Win on TCO: How AMD Instinct™ MI355X Achieves Cost-Competitive Distributed Inference Through SGLang with MoRI
The SGLang and AMD team has worked closely to unlock competitive Total Cost of Ownership (TCO) for large-scale DeepSeek-R1 disaggregated inference on AMD Instinct™ MI355X GPUs. Building on SGLang's se...
Updating 1T parameters in seconds — P2P weight transfer in Large Scale Distributed RL
We introduced a RDMA-based, Peer to Peer weight update mechanism for RL workloads in SGLang as a supplement to traditional NCCL broadcast methods, compatible with all major open source models. By util...
DeepSeek-V4 on Day 0: From Fast Inference to Verified RL with SGLang and Miles
We are thrilled to announce Day-0 support for DeepSeek-V4 across both inference and RL training. SGLang and Miles form the first open-source stack to serve and train DeepSeek-V4 on launch day — with s...
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