№ 0399Reddit post
On/off speculative decoding test incl. Glimmer
Ran matched on/off speculative-decoding pairs across Gemma 4, Qwen3.6 and Muse Glimmer; Glimmer's DFlash drafter made a 7900 XTX 9% slower, keeping only 24.55% of drafted tokens.
KitchenAmoeba4438 held model, quant, card and corpus fixed per pair. Gemma and Qwen gained 1.65x to 2.54x with no measurable accuracy change; he attributes Glimmer's regression to the AMD/Vulkan backend rather than the model, given open llama.cpp issues.
An in-depth on-and-off MTP test (Includes Muse Glimmer!)
Eleven matched on/off pairs across Gemma 4 and Qwen3.6, holding model, quant, card, corpus and concurrency fixed inside each pair. Speed: 1.65x to 2.54x, every pair. Accuracy: nothing the paired intervals could separate from ordinary run-to-run movement. Muse Glimmer is the one that lost. Meta's matching DFlash drafter made the same 7900 XTX 9% slower, keeping 24.55% of drafted tokens against roughly four in five for the Gemma and Qwen heads. Acceptance fell across the run instead of warming up. Meta's model card reports 3.1x on an RTX 5090, and there are open llama.cpp issues for DFlash on AMD and under Vulkan, so I read it as the backend rather than the model. Acceptance turned out to be a poor predictor of speed. It moved under four points across five models while the multiple nearly doubled. What tracks the multiple is how bandwidth-bound the target is: a heavier quant gains more, and the two mixture-of-experts pairs gained least. Worth knowing before you benchmark anything: -md mtp-head.gguf silently disables speculation. Use -hf REPO:QUANT -hfd REPO, then read speculative from /slots and confirm it is true. Per-pair table, intervals, acceptance counters and the raw predic



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