Your session has been flagged for unusual activity.
Please confirm you're human to continue.
An inference-speedup technique where a small fast model drafts several tokens and a large model verifies them in parallel — faster output with identical results.
Leviathan et al. (2023) introduced speculative decoding: a small, cheap "draft" model proposes several tokens, and the large target model checks them all in a single parallel pass, accepting the longest correct prefix. Because verification is parallel, this yields 2–3× faster generation with provably the same output distribution as the large model alone.
It is a now-standard way to cut latency for large-model serving without changing the responses users see.
Primary, peer-reviewed and archival sources for this definition.
Run the same prompt across ChatGPT, Claude, Gemini and Grok — grounded in your own sources, cross-checked against each other.
Try MultipleChat FreeContinue learning
See the AI subscription that replaces separate ChatGPT, Claude, Gemini and Grok accounts.
Multi-model AIRun the same prompt through ChatGPT, Claude, Gemini and Grok before trusting one answer.
GuideChoose the best model for writing, research, coding, documents, images and business work.
Buyer intentOne app for several frontier AI models, side-by-side comparison and model collaboration.
PlatformA professional workspace for using several AI models, comparing answers and creating deliverables.
Core conceptUse several frontier models together for stronger answers and fewer blind spots.
ComparisonCompare several AI answers side by side when the output matters.
WorkflowBuild a professional AI stack for documents, research, writing, images and automation.
Free toolsStart with free tools, then upgrade when multi-model workflows save real time.
