DFlash2 quadruples Qwen 3.8 27B speed

The Atomic.chat team has integrated **DFlash2** into **llama.cpp** (PR #27342), delivering a dramatic speed boost for **Qwen 3.8 27B** on RTX 6000 GPUs. Testing four decoding setups on identical prompts, DFlash2 achieved a median 3x speedup (140.6 tokens/sec vs. baseline 47.4 tokens/sec), with peak gains reaching 4x. However, performance varies by task—some tests plateaued at just 1.5x while others soared. The team notes that video encoding can mask true token throughput, emphasizing raw tokens/sec and acceptance rates as the real metrics.

DFlash2 joins **mtp (Medusa Tree Parallelism)** and the original **DFlash** in the optimization toolkit, offering another lever for local LLM inference. Developed by Atomic.chat, the tool is open-source and designed for desktop/mobile apps running local models. While not a universal 4x miracle, DFlash2’s task-conditional gains make it a compelling addition for latency-sensitive applications like real-time chat or generative workflows. Full benchmarks and code are available on Hugging Face and the project’s blog.