What TempMTP changes
The native one-layer MTP proposal was initialized from the base checkpoint and
trained with a frozen target. Its objective combines:
- hard-label cross-entropy;
- teacher-to-draft KL at temperatures 0.7, 1.0; and
- total-variation distance at those temperatures.
For a single speculative token, 1 - TV(target, draft) is the ideal acceptance
probability before implementation overhead. That makes the TV term directly
connected to the intended speed mechanism. The training objective uses full
vocabulary distributions, not a top-k distillation shortcut.
The best checkpoint was selected on held-out conversations. The training report
is stored at tempmtp/training-report.json, and the standalone native head is at
tempmtp/mtp-head.safetensors.
Serving
Use the same native Qwen3.5 MTP path as the base release:
qwen-superfast plan \
--variant bf16 \
--method mtp \
--model ProCreations/Qwen-3.8-SuperFast-TempMTP
The target verifier is still the unchanged BF16 model. This checkpoint is a
speed experiment, not a claim that speculative execution is bitwise identical
to serial execution. Use target-only serial decoding when bitwise execution is
required.
Measured boundary
The training-time held-out acceptance estimate improved. End-to-end SGLang throughput is pending until the matched benchmark artifact is published.
Temperature-specific throughput must be measured on the same GPU, engine build,
prompts, sampling parameters, and output length as the native-MTP baseline.
Training provenance
- Frozen base:
ProCreations/Qwen-3.8-SuperFast@196d97c3c5533e3e36e442ca8a1cfaa987692d81
- Dataset:
HuggingFaceH4/ultrachat_200k (train_sft)
- Best optimizer step: 16
- Estimated held-out acceptance delta: +0.141250
- Trainable tensors: exactly 15
mtp.* tensors
- Target-model trainable parameters: 0
This model inherits the base model's Apache-2.0 license and usage limitations.