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Llama.cpp Adds Nvidia DFlash Decoding to Double Local Inference Speeds

aiai-infrastructureai-inference-platforms 3 posts · 3 accounts

Llama.cpp has integrated DFlash speculative decoding support led by an NVIDIA team, delivering 2x faster inference speeds for local artificial intelligence models.

The update joins existing decoding methods in the open-source framework, including multi-token prediction, Eagle3 and ngram-based techniques, broadening optimization tools for developers running local model workloads.

From the sources (3 posts)

@ggerganov

llama.cpp recently added DFlash support to its speculative decoding arsenal. Along with MTP, Eagle3 and various ngram-based techniques, the local model performance takes another step up. Special thanks to NVIDIA team and Ruixiang Wang spec

@teknium

Super useful for local users!

@nvidiartxspark

Local AI just got faster. ⚡️ We worked with @ggerganov to add DFlash support in llama.cpp delivering ~2x faster inference.

Preview built on a synthetic news corpus (16 weeks, Apr–Jul 2026). Impact calls are model reads, not price data.

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