community Reddit LocalLLaMA 2026-07-07T16:40 正文 thin 0 words

I tested freshly merged DFlash in llama.cpp on Qwen 3.6 27B Local AI win. 4.44x faster at 36K context. Here are my findings RTX 6000 PRO.

英文标题:I tested freshly merged DFlash in llama.cpp on Qwen 3.6 27B Local AI win. 4.44x faster at 36K context. Here are my findings RTX 6000 PRO.

Hey guys, A month ago I posted my MTP benchmarks here (3.34x on Gemma 4). DFlash support just merged into llama.cpp (PR #22105), so I ran it on the same rig with the Qwen 3.6 27B and it beat my best MTP numbers at every draft length. DFlash is speculative decoding with a block diffusion drafte
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Hey guys, A month ago I posted my MTP benchmarks here (3.34x on Gemma 4). DFlash support just merged into llama.cpp (PR #22105), so I ran it on the same rig with the Qwen 3.6 27B and it beat my best MTP numbers at every draft length. DFlash is speculative decoding with a block diffusion drafte

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English / 原文

Hey guys, A month ago I posted my MTP benchmarks here (3.34x on Gemma 4). DFlash support just merged into llama.cpp (PR #22105), so I ran it on the same rig with the Qwen 3.6 27B and it beat my best MTP numbers at every draft length. DFlash is speculative decoding with a block diffusion drafte