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lued/Qwen3.8-27B-DFlash2-W8
Qwen3.8-27B-DFlash2-W8 is a machine learning model from lued. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for vllm. The card lists the license as apache-2.0.
<div align="center" <h1Qwen3.8-27B DFlash2 drafter · W8A16</h1 <p<strongThe DFlash2 speculative-decoding drafter, quantized W8A16 for Ampere-class GPUs.</strong</p </div
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From the Hugging Face model README
[!NOTE] This is a numerical W8A16 quantization of the z-lab/Qwen3.8-27B-DFlash2 drafter (mirror of incoai/Qwen3.8-27B-DFlash2). Model credit belongs to the z-lab / incoai DFlash2 team and the Qwen base; this repository changes numerics only.
[!WARNING] This is a draft model, not a standalone LLM. It is the speculative-drafting component of DFlash2 decoding: it proposes tokens that the target checkpoint verifies before any are emitted. It never emits unverified tokens. Serve it only as the
--speculative-configdrafter of a DFlash2-compatible target.
The DFlash2 drafter (PR vllm#52816, open as of 2026-08-19) is a 5-layer, block-diffusion draft model with a top-K candidate selector, trained to predict the target's next tokens at fixed layers. Quantizing it W8A16 drops it from 3.58 GiB (BF16) to 2.02 GiB with no measurable effect on drafting (W8 vs BF16 drafter acceptance is equal: 2.65 vs 2.72/draft at the llama-benchy prose floor, same session).
| Property | Value |
|---|---|
| Architecture | DFlash2DraftModel (5 sliding-attention layers, block size 8) |
| Quantization | Data-free symmetric RTN W8A16, group size 128 |
| Packed | mlp.*, self_attn.*, fc projections: 36 tensors |
| Preserved BF16 | candidate_selector.* codebooks, *_conv.* kernels, norms: 45 tensors |
| Draft audit | DRAFT AUDIT PASS (dequant round-trip within INT8 bound; preserved bit-identical; no mtp.*/lm_head) |
| Worst error ratio | 0.749 |
| Size | 2.02 GiB (was 3.58 GiB BF16) |
| Source | z-lab/Qwen3.8-27B-DFlash2 commit 50307d4c4cde6860d4eee73e2547cd786fe8e8a4 (verified unchanged 2026-08-19) |
The quantization was produced by the int8-w8a16-dflash2 family toolkit
(tools/quantize_draft_w8a16.py); the exact target set and ignore list are
recorded in this repository's recipe.yaml and config.json.
Serve it as the DFlash2 drafter of the matching quantized target
lued/Qwen3.8-27B-INT8-W8A16-DFlash2
by repo ID (both resolve from your HF cache):
{"method": "dflash", "model": "lued/Qwen3.8-27B-DFlash2-W8", "num_speculative_tokens": 7}