Speculative decoding
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A small model proposes several tokens ahead and the large model checks them together. Google's Multi-Token Prediction drafters for Gemma 4 use it to speed up generation by up to 3x.
vLLM's built-in DSpark drafter gives 1.92 to 2.23x output throughput for Mistral Large 4.
Drafts tokens that the target model verifies. TextSeal2 keeps tokens that replace rejected drafts watermarked with the same keys, without changing the acceptance rate.
A drafter proposes several future tokens and the target model verifies them in a single forward pass that reuses the same weight read, making an individual user faster.
Faster inference that MTP heads enable; the KL self-distillation term improves it.
Lossless method that predicts draft tokens and verifies them in a single pass, amortizing weight loading. DSpark drafting is much faster than the verification step.
DFlash2 drafter with Reflection Beam and LiLiCorr/DFlash with Nemotron Bolt to raise throughput.
SD
DSpark
DSpark
Used for speed with two draft sources, the model's own draft head and the request's own text (prompt lookup). At temperature 0 output is byte-identical to serial greedy decode, verified on every release.
MTP/EAGLE3/DFlash/DSpark
inverted
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