vLLM Muse Glimmer speculative decoding needs 6 patches, boosts speed from 25 to 57 tok/s
j4ys0nj · reddit · 2026-08-11
A developer shares the detailed process of enabling DFlash speculative decoding for Muse Glimmer on vLLM. The official recipe has 6 issues, including unregistered config names, incorrect Qwen3Config defaults, unmapped tensor renames, and wrong model wrapper assumptions. After patching via Dockerfile, speed improved from 25 to 57 tok/s. The post provides specific code and explanations for each patch.
More from Infra
- Can a Single NVIDIA DGX Replace All Your AI Subscriptions? — jackedAJ · 2026-08-11
- MacBook + DGX Spark: Testing Heterogeneous Inference and KV Cache Shipping — HankYeomans · 2026-08-11
- RTX 3060 Tests: How GPU Memory Allocation Shifts LLM Execution Strategy — Abhishekcur · 2026-08-11
- CXMT 17nm DDR5 Yield Exceeds 90%, But US PC Makers Restrict Procurement — teortaxesTex · 2026-08-11
- Open-Source Models Cut Inference Costs 8x, Compute Becomes New Bottleneck — latticecut · 2026-08-11
- llama.cpp Adds CI Targets for ROCm 7.14, Boosting AMD GPU Inference — pmttyji · 2026-08-11