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Glossary2
Open the full glossary- Local vs cloud (run it yourself or call an API)Whether the model runs on your own machine (local) or you call someone else's over the network (cloud API). The real difference is not "free vs paid" but several axes: privacy, cost at volume, latency, capability ceiling and maintenance burden.
- Batching (serving many requests together)Running several requests together to amortize the cost of hauling weights into the compute units. It raises the machine's total throughput but can lengthen any single request's latency.
Found 4 articles
After You Press Enter: From 0.03 s to 0.85 s, What Your Question Goes Through
One real API call dissects the full chain of a question: 35 ms to establish the connection, microseconds to tokenize, 474 ms for the model to read your whole question, 380 ms generating it token by token — 854 ms in total. Includes the complete reproducible measurement method, and one counterintuitive conclusion: 96% of the time is not in the network but inside the model.
A Multi-Agent Investment-Research Pipeline: Collect, Analyze, Report in Three Stages
A single Agent cannot finish an investment-research task: the context blows up, attention scatters, and errors cross-contaminate. This article gives the complete design for a three-stage collect / analyze / report division of labor — each stage's responsibilities and negative list, the structured JSON contract between stages, the write-scope partition, failure isolation and contamination detection, where to place the verification gates, and the cost-and-latency trade-off framework, with an architecture diagram and a failure-mode list.
The "Non-Text-Generating Model": Jev and the New System One Category, and How Agent Architecture Changes When AI Only Answers Multiple Choice
TypeSafe AI emerges from stealth with a $40M seed and releases Jev, a System One model that generates no text and only answers typed questions (choice / score / noul). It answers multiple questions in parallel in a single forward pass, returns calibrated probabilities, with ~100ms latency, priced at $0.042/MTok.
Complete Comparison of 15 Native Search Engines: In-Depth Analysis from Indexing Mechanisms to Application Scenarios
A comprehensive review of 15 native search engines supported by OpenClaw: indexing sources, API pricing, latency, Chinese language support, stability, and the best choice for each scenario.