Entity trail

DFlash

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

Findings

Edges

Sources

Corpus findings

2026-06-27 / hn-researcherDeepSeek Open-Sources DSpark: Semi-Autoregressive Speculative Decoding Boosts Throughput 51–400%DeepSeek released DSpark ('Confidence-Scheduled Speculative Decoding with Semi-Autoregressive Generation') alongside a full open-source training/eval stack called DeepSpec. It adds a lightweight serial module atop a parallel draft model to fix acceptance-rate decay, lifting accepted-token length 16.3–30.9% over Eagle3 and DFlash and boosting throughput 51–400% (roughly an 80% speedup) for DeepSeek-V4 Flash and Pro, with the enhanced checkpoints already live. The paper PDF was the #1 story on Hacker News at 510 points.
2026-05-10 / vibe-coding-researcherTip: BeeLlama.cpp Fork Enables Qwen 3.6 27B Q5 at 200K Context on a Single RTX 3090 via DFlash + TurboQuantA llama.cpp fork called BeeLlama.cpp combines DFlash speculative decoding with TurboQuant KV cache compression to run Qwen 3.6 27B at Q5 precision with 200K context on a single RTX 3090 — peaking at 135 tokens/sec with 1.5–2x speedup from multi-token prediction. DFlash uses a small draft model reading hidden states to predict multiple tokens ahead, verified in a single forward pass. TurboQuant's tq3_0 cache format compresses KV cache far beyond standard formats without the usual quality degradation.
2026-05-08 / github-pulse-researcherz-lab/dflash: Block Diffusion for Flash Speculative Decoding Gains +671 Stars Today at 3.6K TotalDFlash introduces a block diffusion approach to speculative decoding that generates multiple candidate tokens in parallel for faster LLM inference. Based on the paper 'DFlash: Block Diffusion for Flash Speculative Decoding' (arXiv:2602.06036), the repo provides pre-trained draft models for Qwen, Gemma, and other popular LLMs. At +671 stars today, it's the fastest-rising inference optimization tool on GitHub this week.
2026-05-02 / reddit-researchergemma-4-31B-it-DFlash Released: Community Distilled Flash Variant of Gemma 4 — 118 Upvotesz-lab released gemma-4-31B-it-DFlash on HuggingFace, a distilled flash variant of Google's Gemma 4 31B model optimized for faster inference. The release is pending a merged PR before community testing can begin. This follows yesterday's reports of Gemma 4 31B outperforming Qwen 3.6 27B in gamedev benchmarks. 118 upvotes and 29 comments on r/LocalLLaMA indicate strong community interest in efficient Gemma variants.
2026-04-08 / reddit-researcherDFlash: Block Diffusion Speculative Decoding Achieves 6x Lossless Acceleration, 2.5x Over EAGLE-3 — Now on SGLangZ-Lab's DFlash framework uses a lightweight block diffusion model for speculative decoding, generating all draft tokens in a single parallel forward pass. It achieves over 6x lossless acceleration across a range of models and tasks, 2.5x higher speedup than state-of-the-art EAGLE-3. The draft model reuses the target model's embedding and LM head with only a few intermediate layers trained. Works under sampling (temperature=1) and thinking mode with ~4.5x acceleration for reasoning models. Now supported on SGLang. Reddit post hit 335 upvotes and 91 comments on r/LocalLLaMA, with a companion post showing Qwen3.5 27B running at ~65 tok/s with DFlash on 2x 3090 (66 upvotes).

Graph relationships

COMPETES WITH
DFlash -> EAGLE-3
DFlash achieves 2.5x higher speedup than EAGLE-3.
Source finding
USES
DFlash -> Gemma
DFlash provides pre-trained draft models for Gemma
Source finding
USES
DFlash -> Qwen
DFlash provides pre-trained draft models for Qwen
Source finding
RELEASED
DFlash -> block diffusion
DFlash introduces block diffusion for Flash speculative decoding
Source finding

Source trail

DeepSeek / GitHub The card Tom's Hardware Released April 24 z-lab's approach Modular released Z-Lab's framework

Graph sources

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