LLMFly AI
One API for leading AI models, at lower cost.
LLMFly AI is a unified platform for accessing leading AI models including GPT, Claude, Gemini, and Grok through a single API. It provides OpenAI-compatible API endpoints and works with developer tools such as Codex, Claude Code, Cursor, and custom applications. Developers can manage separate API keys, compare model pricing, monitor usage, and switch between supported models without maintaining separate provider integrations.
Features
- One API for Leading AI Models — Access GPT, Claude, Gemini, Grok, and other leading models through a single platform.
- OpenAI & Anthropic Compatible — Connect existing applications and tools with minimal configuration changes.
- Flexible API Key Management — Create separate API keys for different apps, environments, team members, or AI tools.
- Usage & Cost Tracking — Monitor API usage, request history, model rates, and consumption from one place.
- Developer Tool Integrations — Works with Codex, Claude Code, Claude Desktop, Cursor, Cherry Studio, CC Switch, and custom backend applications.
- Easy Model Switching — Change models without maintaining separate integrations with multiple model providers.
Use Cases
- AI Coding & Development — Power code generation, code review, repository refactoring, and AI coding agents.
- Chatbots & RAG Applications — Build customer support bots, private-knowledge assistants, and multilingual chat experiences.
- AI Agents & Automation — Support function calling, browser agents, and multi-step workflow automation.
- Backend AI Applications — Integrate multiple LLMs into SaaS products, internal tools, and production services through one API.
- Document & Data Processing — Analyze documents, summarize long-form content, and extract structured data into validated formats.
- Multi-Model Testing & Optimization — Compare models and switch between them based on capability, cost, latency, or workload.
Comments
OpenAI-compatible is a lowest common denominator, and that is usually where these gateways leak. The things that do not map cleanly across providers: prompt caching, extended thinking, and the differences in tool-use and streaming event shapes. Do those pass through, say via a passthrough field, or are they dropped at the boundary? Prompt caching is the one I would put first, because you name Claude Code as a supported client. A long system prompt plus a growing conversation re-sent uncached on every turn is the difference between a sane bill and an absurd one. If caching does not survive the proxy, then "at lower cost" works against you on exactly the workload you are advertising. Second question: when a provider deprecates a model or changes a default, who absorbs it, you or the caller? A unified API is only worth the indirection if it is also a stability layer.
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Comments
OpenAI-compatible is a lowest common denominator, and that is usually where these gateways leak. The things that do not map cleanly across providers: prompt caching, extended thinking, and the differences in tool-use and streaming event shapes. Do those pass through, say via a passthrough field, or are they dropped at the boundary? Prompt caching is the one I would put first, because you name Claude Code as a supported client. A long system prompt plus a growing conversation re-sent uncached on every turn is the difference between a sane bill and an absurd one. If caching does not survive the proxy, then "at lower cost" works against you on exactly the workload you are advertising. Second question: when a provider deprecates a model or changes a default, who absorbs it, you or the caller? A unified API is only worth the indirection if it is also a stability layer.
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