LLMFly AI: One API for GPT, Claude, Gemini & Grok
What is LLMFly AI
LLMFly AI is a unified API gateway that lets developers call GPT, Claude, Gemini, and Grok through a single OpenAI-compatible endpoint. Instead of maintaining separate integrations for each provider, teams point their existing OpenAI SDK client to LLMFly AI, select a catalog model ID, and start sending requests. The platform publishes transparent per-1M-token rates for every model, with current prices running 50 to 70 percent below official reference pricing on popular models such as GPT-6 Astra, Claude Sonnet 5, and Gemini. Each environment gets its own API key, so a leaked key can be revoked without taking other apps offline. LLMFly AI is built for everyday API work, from small automation scripts to large agent deployments, and includes usage history so teams can confirm every charge against a real request.
How does LLMFly AI work
LLMFly AI acts as a routing layer between clients and model providers. A developer keeps the OpenAI SDK they already use and changes only the base URL to the LLMFly AI endpoint. Each request carries a catalog model ID, and the platform routes it to the matching provider, such as OpenAI, Anthropic, Google, or xAI. Rates are published per 1 million tokens for input, output, cache write, and cache read, with the billing multiplier reflecting the current discount. Every request is recorded against real usage, so the final charge is confirmed from usage history rather than the provider's list price. Separate keys per environment keep development and production isolated, and a key can be revoked independently.
Benefits of LLMFly AI
LLMFly AI centralizes GPT, Claude, Gemini, and Grok behind one OpenAI-compatible API, which removes the maintenance burden of managing separate provider SDKs and credentials. The platform shows live pricing in a single catalog, so teams can compare input, output, and cache rates before sending traffic. Environment-scoped API keys keep development and production isolated, and a leaked key can be revoked without affecting other apps. Current rates are 50 to 70 percent below official provider prices on popular models, and every charge is recorded in usage history for verification.
Pros and Cons of LLMFly AI
Pros
- One OpenAI-compatible API for four major model providers.
- Current rates 50 to 70 percent below official pricing.
- Separate API keys per app and environment.
- Transparent per-token pricing for input, output, and cache.
- Real usage history confirms every charge.
Cons
- Requires credits bought in advance; no free tier is offered.
- Provider-specific features are limited to where the app needs them.
- Model availability depends on provider lifecycle and retirement.
- Pricing varies across the billing multiplier and context tiers.
Core Features of LLMFly AI
One OpenAI-compatible endpoint
Call GPT, Claude, Gemini, and Grok from the same client by changing the base URL only. No per-provider SDK or credential setup.
Environment-scoped API keys
Create a different key for every app and environment, then revoke a leaked key without taking other applications offline.
Live model pricing catalog
Compare input, output, cache write, and cache read rates per 1M tokens across 28 models before you send traffic.
Usage history with real charges
Each request is recorded against real usage, so monthly budgets are confirmed against actual consumption, not provider list prices.
Provider model guides
OpenAI, Anthropic, Google, and xAI provider pages document model IDs, context limits, and compatibility differences in one place.
Copy-ready integration skill
A ready-made integration guide can be copied into Claude Code, Codex, or Cursor to start calling the API immediately.
Use Cases of LLMFly AI
- Developers: route GPT, Claude, Gemini, and Grok through one OpenAI-compatible client for multi-model products.
- AI coding agents: connect Claude Code, Codex, and Cursor to a single endpoint for model switching without reconfiguration.
- DevOps and platform teams: isolate development and production keys so a leaked credential does not take down all environments.
- Automation and backend services: call LLM APIs from scripts and services with a stable base URL and per-request model selection.
- Cost-conscious teams: compare input, output, and cache rates in the catalog before sending traffic to high-volume workloads.
FAQs of LLMFly AI
What does LLMFly AI do?
LLMFly AI is a unified API gateway that lets you call GPT, Claude, Gemini, and Grok models through a single OpenAI-compatible endpoint. You keep the OpenAI SDK client you already use, change the base URL, and select a model ID from the catalog instead of maintaining a separate integration for every provider.
Can I keep using the OpenAI SDK?
Yes. The LLMFly AI endpoint is OpenAI-compatible, so your existing OpenAI SDK client continues to work. You change the base URL and pick a catalog model ID, then send requests exactly as you would to OpenAI, including streaming, function calling, and tool usage.
Which models can I call?
The catalog covers 28 models across four providers: ChatGPT and the GPT series from OpenAI, Claude models from Anthropic, Gemini from Google, and Grok from xAI. Provider pages document each model's context limits, API IDs, and compatibility notes, and some dated model snapshots are available for pinned versions.
How am I charged?
Charges are based on tokens consumed per request, with rates published per 1 million tokens for input, output, cache write, and cache read. Credits are purchased in advance, and each request is recorded in usage history so you can confirm the actual charge against a real usage record instead of the provider's list price.
Does LLMFly AI store prompts or responses?
The platform records usage history per request for billing verification. If you need details about data retention for prompts and responses, check the provider documentation for the specific model, since each provider may apply its own data policies.
Is there a free tier?
LLMFly AI is a paid, credit-based service. You buy credits and consume them by usage. The quickstart and a free test request are available through the dashboard so you can verify the integration before committing budget.
Where can I get help?
Use the documentation at https://llmfly.ai/doc/en/ for authentication, model IDs, SDK setup, and error handling. For direct assistance, contact hello@llmfly.ai.
How to use LLMFly AI
- Sign in to the LLMFly AI dashboard and create an API key. Use a separate key for each app and environment so a leak can be revoked independently.
- Point your server-side OpenAI client to the LLMFly AI base URL. The existing client code stays unchanged because the endpoint is OpenAI-compatible.
- Open the model catalog, copy a model ID, and paste it into your request. Start with a short, non-streaming call to confirm the route works.
- Check the usage history after your first request. Compare input, output, and cache charges against the model's published rate per 1 million tokens.
- Read the provider or model guide when you need setup notes, context limits, or compatibility differences for a specific model family.
LLMFly AI Website Traffic Analysis
Latest traffic information
- Monthly Visits71
- Bounce Rate44.67%
- Pages Per Visit1.01
- Visit Duration00:00:00
- Global Rank--
- Country/Region Ranking--
Top Keywords
| Keyword | Traffic | Volume | Cost Per Click |
|---|---|---|---|
| gpt 6 astra api | -- | 5.68K | -- |
| gpt6 astra vs claude code 5.1 fable | -- | 740 | -- |
| codexplusplus | -- | 650 | $6.22 |
| gemini api modal costs | -- | 200 | -- |
Top Regions
| Region | Percentage |
|---|---|
| Türkiye | 100% |
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