SGLang 首发支持 DiffusionGemma，文本扩散模型加速生成
文本扩散模型大幅提升生成效率，适合需要低延迟批量推理的 AI 应用开发者，建议立即在 SGLang 中体验。
SGLang 宣布 Day-0 支持 Google 的 DiffusionGemma 模型，这是 Gemma 4 的文本扩散变体（26B A4B MoE）。
与传统逐 token 解码不同，DiffusionGemma 通过并行去噪 token 块实现极低批处理生成速度。该模型支持离散文本扩散、多模态输入（文本、图像、视频）输出文本、稀疏 MoE 架构（8/128 专家）以及可配置思考模式。
开发者现在即可通过 SGLang 运行该模型。
🎉 SGLang has Day-0 support for DiffusionGemma, a text-diffusion variant of @googlegemma 's Gemma 4 (26B A4B MoE), built for blazing low-batch generation speed!
Instead of token-by-token decoding, it denoises blocks of tokens in parallel for much faster generation. 1️⃣ Discrete text diffusion: block-parallel multi-canvas sampling 2️⃣ Multimodal: text, image & video in, text out 3️⃣ Sparse MoE (8 of 128 experts): strong reasoning, low memory 4️⃣ Configurable thinking mode
Run it now with SGLang!
This report is categorized under AITOP's "Models" desk. Key entities and technical topics under continuous tracking include SGLang, DiffusionGemma, Gemma 4, 文本扩散.
Source attribution: curated from LMSYS Org (SGLang) (@lmsysorg). Cross-source corroboration: 8 independent sources have covered this development (including Sundar Pichai, Philipp Schmid, vLLM), confirming industry-wide signal strength.
