How Estimador de Latencia IA Works
An AI Latency Estimator is a performance-planning utility used to predict the "Wait Time" for an AI's response. This tool is essential for product designers, performance engineers, and developers optimizing UX for real-time apps, choosing the right model for low-latency chat, or determining if "Streaming" is required for a better user experience.\n\nThe processing engine handles time estimation through a rigorous three-stage performance pipeline:\n\n1. Model Bottleneck Profiling: The tool utilizes Latest Benchmark Data for various models (e.g., GPT-4o is fast, Claude 3.5 Sonnet is moderate, GPT-4 is slow).\n2. Network + Inference Summation: The engine calculates the total latency by adding:\n * TTFT (Time To First Token): The "Server Processing" delay plus network round-trip.\n * TBT (Tokens Per Second): The speed at which the AI "Types" its response.\n * Prompt Load: Higher input volume proportionally increases the initial delay.\n3. Statistical Distribution (P99): The tool provides not just an "Average," but a distribution of speeds to account for internet variability and server "Cold Starts."\n4. Reactive Real-time Rendering: Your "Response Timeline" and "Cumulative UX Score" update instantly as you adjust the output length or model type.\n\n## The History of Latency: From Telegraph to Instant Inference\nMeasuring "Response Time" has been the goal of digital engineering for a century.\n\n- The Morse Gap (1840s): The first "Latency" was the time it took for a telegraph operator to tap a key. Operators measured Words Per Minute (WPM). This tool Digitalizes that WPM.\n- The "Three Second Rule" (1990s): As the web grew, psychologists discovered that users begin to Lose interest in a webpage if it takes longer than 3 seconds to load.\n- The Intelligence "Wait" (2024): AI introduced a new kind of waiting—watching a model "Think." This tool Automates the trade-off between Quality (slow, reasoning models) and Quantity (fast, small models).\n\n## Technical Comparison: Speed Paradigms\nUnderstanding your "Intelligence Lag" is vital for AI UX and Product Satisfaction.\n\n| Model Class | Avg TTFT | Tokens / Sec | Feel |\n| :--- | :--- | :--- | :--- |\n| Edge / mini | < 200ms | 100+ | Instant |\n| Mid-range | 400 - 600ms | 60 - 80 | Natural Chat |\n| Reasoning (L)| 1s - 3s | 20 - 40 | "Thinking" |\n| Legacy / Heavy| 2s - 5s | 10 - 20 | Frustrating |\n| On-Device | < 50ms | 150+ | True Real-time |\n\nBy using this tool, you ensure your AI User Experience is smooth and responsive.\n\n## Security and Privacy Considerations\nYour performance planning is performed in a secure, local environment:\n\n- Local Logical Execution: All latency and token-per-second calculations are performed locally in your browser. Your sensitive UX targets—which define your product's competitive edge—never touch our servers.\n- Zero Log Policy: We do not store or track your inputs. Your Latency Profiles and Performance Targets remain entirely confidential.\n- W3C Security Compliance: The tool operates within the standard browser sandbox, ensuring no interaction with your local file system or Private Metadata.\n- Privacy First: To maintain absolute Data Privacy, the tool functions as an anonymous utility.\n