01Turn your Azure OpenAI usage into a LLMFly estimate
The comparison above shows input and output rates for the same model on Azure OpenAI and LLMFly, plus the difference for identical usage. LLMFly totals already include the group multiplier. Change usage or model to see the resulting budget.
- See original cost, LLMFly cost and savings together.
- Check both per-million-token rates and linked price sources.
- Use the matching model and group, then verify billing with a small request sample.
02What else does LLMFly simplify?
Compare GPT, Claude, Gemini and other catalog models and groups in one place, without rebuilding separate price sheets for every budget check. Keep a familiar supported client, with one-to-one technical assistance for model selection and setup. Keys separated by app and environment, together with usage records, simplify daily operation, cost reviews and troubleshooting.
03Start moving from Azure OpenAI with one working request
- Choose a LLMFly group supporting your model and client in Model Plaza.
- Get a LLMFly API key and configure the endpoint and model ID using the quickstart.
- Send a small set of equivalent requests; check streaming, tool calls and usage records.
- Increase usage after validation and use the comparison above to budget ongoing costs.
04Which workloads does this comparison cover?
The comparison estimates ordinary text input and output inference. Add the applicable charges for cache-heavy, tool-based or long-context requests. Codex / Claude Code groups retain their supported-client requirements; the original provider's cloud services, identity and private networking do not transfer with model inference.
Sources: Azure OpenAI pricing ↗