Your session has been flagged for unusual activity.
Please confirm you're human to continue.
The delay between sending a prompt and receiving a response. Larger models and longer contexts increase latency — the main speed trade-off in AI products.
Latency in an LLM system is usually split into time-to-first-token and time-per-output-token. Both grow with model size and sequence length, because attention cost scales with the amount of context; the survey by Tay et al. (2022) catalogues the efficiency techniques developed to mitigate this.
Approaches that reduce latency include sparsity (Mixture of Experts), quantization, caching and streaming — each trading some accuracy, memory or complexity for speed.
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.
