DFlash2

This repository contains the promoted DFlash2 draft head used with Qwen/Qwen3.8-27B. It is not a fine-tune of the full Qwen target and must not be loaded as a standalone language model. It has no tokenizer and no target weights: a compatible DFlash2 runtime loads this head alongside the Qwen verifier.

The Hub base-model tree is intentionally omitted. A conventional "Qwen finetune" label would misrepresent the artifact: only the small speculative draft head is changed, while target-controlled output remains the authority.

The head descends from the public Qwen3.8-27B DFlash2 draft model. It was adapted with target-verified cycles from the incumbent legacy corpus and a session-grouped Fable agentic corpus. The final checkpoint combines a generation-2 Fable adaptation at strength 0.0625 with a generation-3 combined-domain adaptation at strength 0.1875.

No trace dataset, prompt file, capture cycle, selector tensor, or W&B log is included in this repository. Only the final draft checkpoint, configuration, blend metadata, and evaluation summary are published.

Acceptance results

All acceptance runs used greedy target-controlled generation on one Apple M4 Max through DFlash MLX. The target was the calibrated Qwen3.8-27B MXFP4 runtime. Draft quantization was disabled for this head.

Paired gate Incumbent This head Mean delta Wins / ties / losses
Legacy 24-prompt corpus 0.6712239583 0.6718750000 +0.0006510417 5 / 14 / 5
Fable 25-prompt held-out 0.6471875000 0.6492187500 +0.0020312500 11 / 5 / 9

The Fable live-gate prompts were excluded from the generation-2 and combined training splits. The legacy corpus had already been used to train the incumbent, so it remained in the combined training capture for a paired comparison.

Exact parity

The exact 256-token baseline-versus-DFlash smoke gate passed:

  • token_match: true
  • smoke acceptance: 0.7109375
  • diagnostic baseline throughput: 21.9615 tok/s
  • diagnostic DFlash throughput: 33.5111 tok/s

Throughput is diagnostic only. Thermal pressure and co-tenant machine load were not controlled.

Training summary

  • combined capture: 11,273 target-verified cycles
  • prompt groups: 127
  • legacy contribution: 1,981 cycles from 24 prompts
  • Fable contribution: 9,292 cycles from 103 training prompts
  • excluded Fable live gate: 25 prompts
  • teacher signal: target top-64 logits and greedy target tokens
  • final full-run held-out prefix accuracy: 0.7932212528
  • final full-run held-out top-1 accuracy: 0.8714877986

The capture teacher was the calibrated MXFP4 Qwen3.8-27B target runtime, not the pinned BF16 Qwen3.8-27B checkpoint. This precision choice is part of the training provenance.

Checkpoint integrity

  • model.safetensors SHA-256: c90e0fc65dddbe4107b1b417d771c3be188c87197e89cf4b14415f56abc866f0
  • config.json SHA-256: 873e3556509b0da06e29654ba00d4944888d4b5e8a33afde25f7eb27d321e980
  • blend.json SHA-256: e53a6bb5e890d7e3368053302189766c3ef68d2eb7887152ece1ea9eac4f64d5

Intended use and limits

This artifact is for lossless speculative decoding research with a compatible DFlash2 implementation. Acceptance metrics do not establish broad task quality, natural-EOS behavior, multilingual performance, long-context performance, or a controlled thermal throughput win. The Fable held-out prompts come from the same eval shard as the Fable training prompts, so that gate does not prove out-of-domain generalization.

Downloads last month
42
Safetensors
Model size
2B params
Tensor type
BF16
ยท
MLX
Hardware compatibility
Log In to add your hardware

Quantized

Inference Providers NEW
This model isn't deployed by any Inference Provider. ๐Ÿ™‹ Ask for provider support