AI Stats is built around practical openness: broad model and provider access, explicit release/deprecation/retirement tracking, and clear observability so teams can run production workloads with low surprise.
Research models, execute through one API layer, stay current on lifecycle changes, and monitor behavior over time.
Browse and compare model capabilities and pricing across providers in one surface.
Route requests across providers with an OpenAI-compatible API layer.
Stay current on launches, deprecations, and retirements as they happen.
Get clear signal on request behavior, reliability, and provider performance.
Our goal is simple: keep access broad, interfaces stable, and operations understandable.
Decision-ready model data with benchmarks, pricing, and provider coverage.
OpenAI-compatible API surface to execute across many providers.
Track new releases, deprecations, and retirements in one feed.
Clear operational insight into requests, latency, errors, and behavior shifts.
Use AI Stats Pricing for our platform/service pricing, and use the Pricing Calculator for model-level estimation.
See platform pricing details, including credit purchase fee tiers and billing coverage.
Use model-level pricing references and cost estimation tools for scenario planning.
We prioritize transparent coverage and public documentation over vague claims. Compatibility, lifecycle updates, and observability are first-class.
Access should be broad and practical, with consistent naming and clear docs.
New releases, deprecations, and retirements are tracked so migration work is predictable.
Request-level observability keeps behavior auditable and easier to debug in production.
Everything company, product, and policy related in one place.