request
OpenAI-compatible ingress
Keep your OpenAI-compatible SDK. Point baseURL at KiteRouter and send the same chat completion payload.
AI gateway for builders who read the bill
One unified gateway for the models you already use.
Route requests to GPT, Claude, Gemini, Mistral, Meta, and more through one API. Keep provider choice open, keep integration small, and keep token costs visible.
100+ modelsone catalog
OpenAI-compatiblesame request shape
Pay per tokenno subscription
Keys + usageproduction control
POST https://kiterouter.com/api/v1/chat/completionsmodel
openai/gpt-5.6-sol
1const client = new OpenAI({)2 baseURL: 'https://kiterouter.com/api/v1',3 apiKey: process.env.KITEROUTER_API_KEY,4})OpenAI
Anthropic
Google
Mistral
Meta
OpenAI
Anthropic
Google
Mistral
Meta
Supported models
Popular frontier models, one gateway.
OpenAI
gpt-5.6-solgpt-5.6-terra
Anthropic
claude-fable-5claude-opus-5claude-sonnet-5
Google
gemini-3.7-flashgemini-3.5-flash-lite
DeepSeek
deepseek-v4-prodeepseek-v4-flash
Meta
llama-4-maverickllama-4-scout
and more...
How it works
KiteRouter sits between your app and every model vendor.
Your app keeps the OpenAI-compatible SDK it already trusts. KiteRouter checks keys and credits, forwards the request body transparently to a compatible upstream provider, then returns the response without turning integration work into platform work.
Codex
OpenCode
OpenClaw
Cherry Studio
gateway
KiteRouter
authcreditsroute
OpenAI
GPT 5.6 Sol
Claude
Claude Fable 5
Grok
Grok 4.5
Gemini
Gemini 3.7 Flash
DeepSeek
DeepSeek V4 Pro
ModelsOpenAI, Anthropic, Google, Mistral, Meta
ControlsAPI keys, credits, usage, status
FormatOpenAI-compatible request format
same body, status-only tracking
One request shape, one operational surface.
01Chat completions
/chat/completions02Streaming
stream: true03Models
/modelsSend OpenAI-compatible requests. KiteRouter tracks request status only; request bodies pass through transparently to compatible upstream providers.
route
Provider and model routing
Route OpenAI-compatible requests to OpenAI, Anthropic, Google, Mistral, Meta, and other compatible upstreams.
control
Keys, credits, and budgets
Issue scoped API keys, fund prepaid credits, and track cost without surprise platform subscriptions.
observe
Usage and status visibility
See tokens, spend, models, and status-only request history in analytics — without storing request bodies.
Integrate in minutes
Change the base URL. Keep the rest of your app.
KiteRouter accepts the OpenAI-compatible format your SDK already sends. That keeps migration small and makes model/provider changes an operations decision, not a rewrite.
1import OpenAI from 'openai'2 3const client = new OpenAI({)4 baseURL: 'https://kiterouter.com/api/v1',5 apiKey: process.env.KITEROUTER_API_KEY,6})7 8const response = await client.chat.completions.create({)9 model: 'openai/gpt-5.6-sol',10 messages: [{ role: 'user', content: 'Route this request.' }],11})Operate
Production signals without enterprise platform ceremony.
See the basics every multi-model app needs before traffic grows: which keys are active, which models spend money, which requests completed or failed, and how many credits remain.
Usage by model
model spend visible
GPT, Claude, Gemini, Mistral
Key controls
scoped key inventory
expiration, spend tracking, revoke flow
Credit balance
prepaid balance
transparent, per token, no subscription
request.completemodel routelatency
key.usagescoped keycost
credit.debitprovider calltokens
route.readyfallback poolhealthy
Privacy posture
We are not interested in your request bodies.
KiteRouter is a routing and billing gateway, not a data-harvesting layer. We keep status, token, cost, latency, key, model, and routing metadata needed to operate the service. Prompt and message bodies pass through to the selected upstream provider (for example: OpenAI, Anthropic, Google, Mistral, Meta, DeepSeek).
No prompt-body logging
We do not store prompts, messages, or request body content in request logs. That reduces database load and reduces sensitive data surface area.
Check upstream provider policies
Your main data-use concern should be the upstream model provider you choose, such as OpenAI, Anthropic, Google, Mistral, Meta, DeepSeek, or other model vendors. Providers have their own retention, abuse-monitoring, and AI-training policies, so review them before sending sensitive traffic.
Storing bodies costs us too
Keeping customer prompt data would mean more database storage, security work, retention tooling, and compliance burden. We do not have a product reason, budget, or appetite to do that.
Positioning
Lighter than full LLMOps. Easier than provider sprawl.
Full LLMOps platforms are broad. Direct providers are fragmented. KiteRouter is the practical middle path for teams that need multi-model access and cost control first.
Decision
Direct providers
KiteRouter
Full LLMOps suite
Integration path
One account and SDK per provider
One base URL, OpenAI-compatible request
Platform SDK or proxy layer
Cost posture
Provider list price and separate bills
Pay-per-token credits with low gateway pricing
Enterprise platform pricing
Best fit
Single-provider prototypes
Teams needing cheap multi-model access fast
Large orgs needing full governance suites