# SGLang v0.5.13

- Product: SGLang (https://whatsnew.fyi/product/sglang)
- Vendor: LMSYS
- Date: 2026-06-13
- Version: v0.5.13
- Original notes: https://github.com/sgl-project/sglang/releases/tag/v0.5.13
- Permalink: https://whatsnew.fyi/product/sglang/releases/v0.5.13

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'.

---

- **added** — Support for Nemotron 3 Ultra autoregressive model with Day-0 kernel optimizations
- **added** — Support for Step-3.7-Flash autoregressive model
- **added** — Support for Command A+ autoregressive model
- **added** — Support for Cosmos3 diffusion model
- **added** — Support for LingBot-World diffusion model
- **added** — Support for SANA-WM diffusion model
- **added** — Support for Ernie-Image diffusion model
- **added** — Support for FLUX.2-Klein 4B/9B diffusion models
- **added** — Support for Ideogram 4 diffusion model
- **changed** — Spec V2 is now the default speculative-decoding path with tree drafting production-ready across triton, FA3, MLA, and aiter backends
- **changed** — EAGLE and MTP now run on the unified V2 worker
- **changed** — Reduced per-step scheduler overhead through unified async value passing via FutureMap and prefill input transfer optimization
- **changed** — Extended piecewise and breakable CUDA graph coverage to DSA models, Kimi-K2.5, and DeepSeek V4
- **changed** — Improved Qwen 3.5 performance on Blackwell GPUs with new FlashInfer Gated DeltaNet kernels and CuTeDSL prefill kernel
- **changed** — HiCache for hybrid models (SWA/Mamba) now enabled by default through UnifiedTree
- **added** — Heterogeneous CPU plus GPU EPD disaggregation to offload VLM vision encoding onto Intel Xeon CPUs alongside GPUs
- **added** — MoRI support for disaggregated inference on AMD Instinct MI355X
- **added** — DeepSeek V4 context parallelism with MTP and sparse-attention kernels
- **added** — SGLang-Diffusion realtime video generation with msgpack frame streaming and OpenAI-style interface

##### Highlights

**New Model Support**:

- **Autoregressive**: [Nemotron 3 Ultra](https://docs.sglang.io/cookbook/autoregressive/NVIDIA/Nemotron3-Ultra) (Day-0, [blog](https://www.lmsys.org/blog/2026-06-04-nvidia-run-nemotron-3-ultra/)), [Step-3.7-Flash](https://docs.sglang.io/cookbook/autoregressive/StepFun/Step-3.7-Flash), Command A+
- **Diffusion**: [Cosmos3](https://docs.sglang.io/cookbook/diffusion/Cosmos/Cosmos3), [LingBot-World](https://docs.sglang.io/cookbook/diffusion/LingBot-World/LingBot-World), [SANA-WM](https://docs.sglang.io/cookbook/diffusion/SANA-WM/SANA-WM), [Ernie-Image](https://docs.sglang.io/cookbook/diffusion/Ernie-Image/Ernie-Image), [FLUX.2-Klein 4B/9B](https://docs.sglang.io/cookbook/diffusion/FLUX/FLUX), [Ideogram 4](https://docs.sglang.io/cookbook/diffusion/Ideogram/Ideogram4)

**Spec V2 is now the default speculative-decoding path**: Tree drafting with topk > 1 is production-ready across the triton / FA3 / MLA / aiter backends, including `page_size > 1` and Mamba/hybrid-linear models ([#26997](https://github.com/sgl-project/sglang/pull/26997), [#26972](https://github.com/sgl-project/sglang/pull/26972), [#27463](https://github.com/sgl-project/sglang/pull/27463)). Spec V1 is deprecated, with EAGLE/MTP now running on the unified V2 worker ([#25464](https://github.com/sgl-project/sglang/pull/25464)), and topk = 1 drafting is faster ([#26397](https://github.com/sgl-project/sglang/pull/26397), [#26424](https://github.com/sgl-project/sglang/pull/26424)).

**Lower per-step scheduler overhead**: Unified async value passing through FutureMap plus moving prefill input transfer onto the forward stream reduced per-step launch overhead and improved stability under high concurrency ([#25945](https://github.com/sgl-project/sglang/pull/25945), [#25879](https://github.com/sgl-project/sglang/pull/25879), [#26380](https://github.com/sgl-project/sglang/pull/26380)).

**Piecewise & Breakable CUDA Graph coverage**: Piecewise (PCG) and Breakable (BCG) CUDA Graph capture more of the model to cut per-step kernel-launch overhead, now extended to DSA models, Kimi-K2.5, and DeepSeek V4: [#23351](https://github.com/sgl-project/sglang/pull/23351), [#26382](https://github.com/sgl-project/sglang/pull/26382), [#25195](https://github.com/sgl-project/sglang/pull/25195).

**Faster Qwen 3.5 on Blackwell**: New FlashInfer Gated DeltaNet (GDN) kernels and a CuTeDSL GDN prefill kernel speed up Qwen 3.5 on Blackwell GPUs: [#22921](https://github.com/sgl-project/sglang/pull/22921), [#23273](https://github.com/sgl-project/sglang/pull/23273), [#26200](https://github.com/sgl-project/sglang/pull/26200).

**HiCache for hybrid models by default**: HybridModel (SWA/Mamba) launches HiCache through UnifiedTree by default, bringing hierarchical KV-cache offload to sliding-window and Mamba hybrids out of the box: [#27759](https://github.com/sgl-project/sglang/pull/27759).

**Heterogeneous CPU + GPU EPD disaggregation (with Intel)**: Offload VLM vision encoding onto Intel Xeon CPUs alongside GPUs, with up to ~1.3x P99 TTFT and request-throughput gains under load. ([blog](https://www.lmsys.org/blog/2026-06-01-hetero-epd/))

**MoRI on AMD Instinct MI355X (with AMD)**: Cost-competitive DeepSeek-R1 disaggregated inference via AMD's MoRI communication library, $0.169 per million tokens at 129 tok/s/user. ([blog](https://www.lmsys.org/blog/2026-05-28-mori/))

**DeepSeek V4 — context parallelism & sparse-attention kernels**: Building on the v0.5.12 Day-0 path, v0.5.13 extends DeepSeek-V4 to context-parallel serving and adds its sparse-attention kernels:

- Context Parallel + MTP: [#24934](https://github.com/sgl-project/sglang/pull/24934)
- Context Parallel + fused MoE kernel (non-DeepEP): [#24947](https://github.com/sgl-project/sglang/pull/24947)
- Sparse FlashMLA via `flash_mla_sparse_fwd`: [#25418](https://github.com/sgl-project/sglang/pull/25418)
- FP4 indexer support: [#26209](https://github.com/sgl-project/sglang/pull/26209)
- S

_[Truncated at 4000 characters — full notes: https://github.com/sgl-project/sglang/releases/tag/v0.5.13]_