# SGLang v0.5.15

- Product: SGLang (https://whatsnew.fyi/product/sglang)
- Vendor: LMSYS
- Date: 2026-07-10
- Version: v0.5.15
- Original notes: https://github.com/sgl-project/sglang/releases/tag/v0.5.15
- Permalink: https://whatsnew.fyi/product/sglang/releases/v0.5.15

What's New is an index, not a publisher: every entry below links to the vendor's own release notes, which are the authoritative source. Entries are labelled where they are hand-curated sample data, pre-releases, or drawn from a secondary source such as a developer blog.

Reuse: the summaries, labels and curation here are © What's New. Quote freely with attribution and a link back; wholesale republication of the corpus is not permitted — terms: https://whatsnew.fyi/terms. The vendors' own release notes remain their publishers'.

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- **added** — Add support for Hunyuan 3 (Hy3) model
- **added** — Add support for Hierarchical Reasoning Model (HRM-Text)
- **added** — Add support for NVIDIA LocateAnything-3B model
- **added** — Add support for Baidu Unlimited-OCR model
- **added** — Add support for JoyEcho multi-shot audio/video model
- **added** — Add support for Qwen3.6 NVFP4 quantization
- **added** — Add native web search support via Exa integration
- **added** — Add FlashKDA prefill backend for safe-gate KDA linear attention
- **added** — Add ReplaySSM buffered output-only decode for linear attention
- **added** — Add FlashInfer all-to-all support for routed MoE runner
- **added** — Add decode context parallelism for MLA models including DeepSeek V3 and Kimi K2
- **changed** — Enable Spec V2 by default with zero-overhead scheduling via CUDA-graphable DSA draft-extend, dropped D2H/H2D syncs, and fused metadata ops
- **changed** — Enable Breakable CUDA Graph by default as capture path to reduce per-step kernel-launch overhead
- **changed** — Introduce IndexShare MTP to reuse indexer top-k across draft steps for up to 1.9x lower draft-step cost at long context
- **changed** — Implement TopK V2 fusing top-k selection with page-table transform supporting runtime k up to 2048
- **changed** — Fuse indexer prologue from 12 kernels to 4 for approximately 8% faster decode at batch size 1
- **changed** — Add shape-specialized JIT router GEMM and CuteDSL BF16 GEMM for Blackwell
- **changed** — Extend FlashInfer autotune to cover draft-model graphs
- **changed** — Enable FlashMLA sparse prefill by default for DeepSeek-V4 reaching over 10% throughput gain on long context
- **changed** — Add non-paged indexer support for DeepSeek-V4 long context prefill with over 5% end-to-end throughput gain
- **changed** — Upgrade transformers to 5.12.1 and upgrade tvm-ffi, sgl-deep-gemm, and tilelang dependencies

#### Highlights

**GLM-5.2 NVFP4, tuned for production**: We took time this cycle to tune GLM-5.2 NVFP4 on Blackwell for optimized production serving. It now runs at **500+ tok/s/user on 8x B300, 450 on 4x GB300** (bs=1). Run GLM-5.2 with our [cookbook](https://docs.sglang.io/cookbook/autoregressive/GLM/GLM-5.2).

  * **Spec V2 by default**: zero-overhead scheduling via CUDA-graphable DSA draft-extend, dropped D2H/H2D syncs, fused metadata ops. +11% end-to-end TPS ([#29413](https://github.com/sgl-project/sglang/pull/29413), [#29343](https://github.com/sgl-project/sglang/pull/29343), [#29166](https://github.com/sgl-project/sglang/pull/29166), [#29077](https://github.com/sgl-project/sglang/pull/29077)).
  * **IndexShare MTP**: reuses the indexer top-k across draft steps, up to 1.9x lower draft-step cost at long context ([#29959](https://github.com/sgl-project/sglang/pull/29959), [#29787](https://github.com/sgl-project/sglang/pull/29787), [#29654](https://github.com/sgl-project/sglang/pull/29654)).
  * **TopK V2**: fuses top-k selection with the page-table transform, runtime k up to 2048 ([#30274](https://github.com/sgl-project/sglang/pull/30274), [#26788](https://github.com/sgl-project/sglang/pull/26788)).
  * **Indexer prologue fusion**: 12 kernels to 4, ~8% faster decode at bs=1 ([#27705](https://github.com/sgl-project/sglang/pull/27705)).
  * **GEMM**: shape-specialized JIT router GEMM + CuteDSL BF16 GEMM for Blackwell ([#21531](https://github.com/sgl-project/sglang/pull/21531), [#30117](https://github.com/sgl-project/sglang/pull/30117)).
  * **FlashInfer autotune**: now covers draft-model graphs ([#29595](https://github.com/sgl-project/sglang/pull/29595)).


**New Model Support**: [Hunyuan 3 (Hy3)](https://docs.sglang.io/cookbook/autoregressive/Tencent/Hy3), Hierarchical Reasoning Model (HRM-Text), NVIDIA LocateAnything-3B, [Baidu Unlimited-OCR](https://docs.sglang.io/cookbook/autoregressive/Baidu/Unlimited-OCR), [JoyEcho](https://docs.sglang.io/cookbook/diffusion/JoyEcho/JoyEcho) multi-shot A/V, plus [Qwen3.6](https://docs.sglang.io/cookbook/autoregressive/Qwen/Qwen3.6) NVFP4 support.

**Native web search (Exa)**: Built-in `web_search` support backed by Exa ([#29342](https://github.com/sgl-project/sglang/pull/29342)).

**Breakable CUDA Graph on by default**: Breakable CUDA Graph is now the default capture path, reducing per-step kernel-launch overhead ([#29458](https://github.com/sgl-project/sglang/pull/29458)); full CUDA Graph support for the prefill phase lands as experimental ([#27988](https://github.com/sgl-project/sglang/pull/27988)).

**Linear-attention kernels (KDA / GDN)**: New FlashKDA prefill backend for safe-gate KDA linear attention ([#29472](https://github.com/sgl-project/sglang/pull/29472)), plus ReplaySSM buffered output-only decode for linear attention ([#28451](https://github.com/sgl-project/sglang/pull/28451)).

**FlashInfer A2A for routed MoE**: Adds FlashInfer all-to-all with the `flashinfer_trtllm_routed` MoE runner ([#22394](https://github.com/sgl-project/sglang/pull/22394)).

**DeepSeek-V4 Optimization**: 
* Optimizes C128 state-pool allocation using the request state pool ([#28612](https://github.com/sgl-project/sglang/pull/28612)).
* FlashMLA sparse prefill is now enabled by default for DeepSeek-V4, reaching >10% throghput gain on long context. ([#29775](https://github.com/sgl-project/sglang/pull/29775)).
* Non paged indexer support for long context prefill, with >5% e2e throughput gain.([#29619](https://github.com/sgl-project/sglang/pull/29619)).

**Decode Context Parallelism**: decode context parallelism lands for MLA models, including DeepSeek V3 and Kimi K2 series ([#14194](https://github.com/sgl-project/sglang/pull/14194)).

**Dependency upgrades**: `transformers` bumped to 5.12.1 ([#29393](https://github.com/sgl-project/sglang/pull/29393)); `tvm-ffi` / `sgl-deep-gemm` / `tilelang` upgraded ([#29554](https://github.com/sgl-project/sglang/pull/29554)).
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