Briefing

BeeLlama.cpp: Advanced DFlash, TurboQuant, and Vision for Qwen 3.6 27B on RTX 3090

ai-dev
by /u/Anbeeld · Llama

Clone BeeLlama.cpp, build with your GPU, and run Qwen 3.6 27B Q5 + 200k KV cache + vision for high performance.

What to do now

Download the repo, compile, and test the Qwen 3.6 27B Q5 model with vision on your RTX 3090.

Summary

BeeLlama.cpp is a performance‑focused llama.cpp fork that adds DFlash speculative decoding, TurboQuant KV‑cache compression, adaptive draft control, and full multimodal support. The fork supports Qwen 3.6 27B Q5 with a 200 k context window and vision on a single RTX 3090 or 4090.

Key features include DFlash draft generation with cross‑attention, TurboQuant compression up to 7.5×, reasoning‑loop protection, sampled DFlash verification, DDTree branch verification, request‑level overrides, and copy‑spec model‑free speculation. The repository provides documentation and a quickstart guide for the Qwen 3.6 setup.

Key changes

  • DFlash speculative decoding via --spec-type dflash
  • TurboQuant KV cache compression up to 7.5×
  • Adaptive draft-max control
  • Full multimodal support with --mmproj
  • Reasoning-loop protection
  • Sampled DFlash verification
  • DDTree branch verification
  • Request-level speculative overrides

Affects

internal

Customer impact

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