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Kimi-K2.7-coder-DFLASH-preview
A DFlash (block-diffusion) speculative-decoding draft model for an ablated Kimi-K2.7-Code target. Research preview.
- Trained with SpecForge (online DFlash training).
- Trained on only ~55k samples (single corpus, a few epochs) — deliberately small; this is a preview.
- On our ablated Kimi-K2.7-Code target it already beats a misaligned EAGLE3 drafter (a K2.6 EAGLE3 head used on K2.7-Code): measured mean accept length ~2.5 vs ~1.9, ~1.3x single-stream decode speedup, with peaks of 4.6-5.2 on long free-form code bodies.
- Architecture:
DFlashDraftModel(5 layers, hidden 7168), train block size 16 / infer 8, target layer ids capture, mask token id 163838.
Serving (sglang)
Serve against the matching target with DFLASH speculative decoding:
python -m sglang.launch_server --model-path <kimi-k2.7-code-target> --tp 4 \
--speculative-algorithm DFLASH \
--speculative-draft-model-path Kimi-K2.7-coder-DFLASH-preview \
--speculative-eagle-topk 1 --speculative-dflash-block-size 8 --speculative-num-draft-tokens 8
Production / structured outputs
Stock sglang DFLASH rejects grammar-constrained requests (JSON schema / regex / tool schemas). Support for that — so this drafter keeps its speedup on coding-CLI JSON (thin envelope around a large code/diff string) — is proposed upstream in sgl-project/sglang PR #28943.
Limitations
- Early preview (small data, single config); acceptance plateaus and is not yet tuned.
- Must be paired with the matching ablated Kimi-K2.7-Code target; not a standalone model.
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