Model pricing
Browse model input and output pricing references.
TackleKey
LLM API cost
LLM API cost is not just the listed token price
Real API cost includes failed retries, fallback behavior, model selection, cache behavior, and whether your team can trace spend by project key. TackleKey focuses on pricing visibility and request-level logs before scale.
Start with these checks
Cost candidates
Compare lower-cost public candidates with routing boundaries.
Cost calculator
Use the existing tools page for quick estimation.
Decision checklist
| Dimension | Why it matters | TackleKey entry |
|---|---|---|
| Compatibility | Start with an OpenAI-compatible base URL change before rewriting client code. | Base URL setup |
| Pricing clarity | Check input, output, cache, and capability-specific pricing before a larger batch. | Live pricing |
| Usage logs | Debug failures and spend by tracing requests, keys, models, and balance changes. | Resources |
| Project keys | Separate apps, environments, and tests so budgets and incidents are easier to isolate. | Docs |
| Successful cost | The useful number is successful-request cost, not only the listed token price. | Route candidates |
Why this page exists
Search terms like New API, API 中转站, OpenAI-compatible API, AI API gateway, and OpenRouter alternative often mix several different needs: model access, unified billing, cheaper testing, logs, and operational reliability. TackleKey should be evaluated by those practical needs, not by broad claims.
Use this as a search landing page and decision checklist. It does not claim universal lowest price, unlimited access, or guaranteed availability. Confirm live pricing and service boundaries before production use.
FAQ
Is TackleKey the same as New API?
TackleKey builds on the New API style of unified AI access, but its public positioning focuses on OpenAI-compatible setup, pricing visibility, project keys, usage logs, balance records, and cost-aware route operations.
Is an AI API gateway only about one endpoint?
No. A practical gateway should also expose pricing, logs, key-level usage, failure boundaries, and a way to reason about fallback and successful-request cost.
Can I test it with an OpenAI-compatible client?
For common chat completion workflows, start by changing the base URL, API key, and model name. Send a small request first, then inspect logs and live pricing before scaling.
Does TackleKey promise the lowest price?
No. Public pages show references and route candidates. Real cost depends on model choice, request shape, availability, failure handling, and current pricing.
Try TackleKey with one OpenAI-compatible change
Create an account, generate a project API key, then replace your client base URL with the TackleKey endpoint. Keep keys server-side and verify live pricing before scaling traffic.