Highlights

950 PRs from 245 contributors.

New models

What's new

• DeepSeek-V4.1 gets up to 2.3x more throughput per GPU on H200, and now runs on AMD MI350X / MI355X with up to 1.9x throughput from DSpark (#41251, #41308).
• Qwen3.8-Flash-Next decodes 12% faster on B200, and GLM-5.3-Flash with DFlash 10% faster on B300 (#42175, #42489).
• MiMo-V2.6-Pro gets 1.85x decode throughput with DFlash on B300 (#41886).
• Models load 10x faster with the new InstantTensor loader (#40453).
• PD disaggregation gets up to 27% more throughput and half the p95 TTFT on long-prompt workloads (#40703).
• HiSparse now supports EAGLE and MTP for long-context serving with the KV cache in CPU memory (#37771).
• GLM-5.2 and GLM-5.3 can now combine decode context parallelism with MTP, with up to 2.1x faster decoding on GLM-5.3 (#43735).
• SGLang now runs on Apple Silicon Macs with the standard PyTorch backend, alongside MLX (#36780).
• MiniMax-H3 and Qwen-Image 2.1 now run in ComfyUI with SGLang Diffusion, which also loads community GGUF checkpoints and LoRAs (#43504, #43581, #42556, #39523, #42174).
• Important fix: Hybrid linear models could resume from wrong mamba states when speculative decoding and structured output were used together. Thanks to @Wirick and Baseten for finding it (#43029).

To upgrade

SGLang now requires Python 3.11 or newer.

uv pip install --prerelease=allow sglang==0.5.22

Full Release Notes

[余略，详见 https://github.com/sgl-project/sglang/releases/tag/v0.5.22]