2026-10-16 · America/Los_Angeles · 社区动态 · #8

[Research] 2,788 tokens/s on a single RTX 5090 with a diffusion LLM — Introducing ORL (fully open source) [R]

Hey r/MachineLearning! We're excited to share ORL (On-Policy Residual Learning), our new research on making diffusion language models (dLLMs) significantly faster without sacrificing generation quality. With ORL and our custom inference engine dlmrt, we've achieved: 2,788 tokens/s on a single RTX 5090 — LLaDA-2.1-mini + ORL, NVFP4 7,708 tokens/s on 8× B200 — DiffusionGemma 26B MoE + ORL, NVFP4 Up to 6.9× higher end-to-end throughput on our QwenDLM-4B model, at comparable or better quality 1.74× faster than DFlash speculative decoding at matched accuracy in our single-request H100 comparison…

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