Method Drift›Speculative decoding
Superseded baseline#34 of 151 most-superseded
DynaSpec
DynaSpec: Context-aware Dynamic Speculative Sampling for Large-Vocabulary Language ModelsSpeculative decoding · first seen Oct 11, 2025
superseded — cited as a baseline and beaten by newer methods
2 papers critique it · 1 beat it on benchmarks
What papers say
Verbatim critique sentences, each from a paper that cites DynaSpec as a baseline.
“still rely on statically pre-clustered vocabularies, resulting in non-negligible training overhead.”
— MicroSpec: Accelerating Speculative Decoding with Lightweight In-Context Vocabularies“The latter can become a noticeable bottleneck on GPUs because it involves such operations as global ranking, partial sorting, irregular indexing and gathering a context-dependent subset of weights, which are less efficient than dense matrix multiplication.”
— SlimSpec: Low-Rank Draft LM-Head for Accelerated Speculative Decoding
Beaten on benchmarks
Head-to-head results where a newer method reports beating DynaSpec. Values are copied from the source paper's tables — verify against the cited paper.
- MicroSpec: Accelerating Speculative Decoding with Lightweight In-Context Vocabularies
NanoSpec beats DynaSpec · Speed [Llama-3.1-8B-Instruct with EAGLE-2]
392.7 vs 367.7
Newer alternatives
Recent methods in the same sub-problem, not yet superseded in the knowledge base.
- May 11, 2026
- EvoSpecEvoSpec: Evolving Speculative Decoding via Real-Time Vocabulary and Parameter AdaptationTargetApr 17, 2026
- Apr 8, 2026