One API, every model
OpenAI-compatible endpoints. Automatic fallbacks. Per-key quotas. Drop-in replacement for the OpenAI SDK — works with LangChain, LlamaIndex, Vercel AI SDK and every framework that speaks OpenAI.
- OpenAI SDK compatible
- Streaming + tools
- Fallback chains built-in
Built by developers, for developers
Everything you need to put AI in production — without owning five contracts.
OpenAI-compatible endpoints
Swap the base URL, keep the SDK. Works with openai-python, openai-node, LangChain, LlamaIndex and every framework that speaks OpenAI.
Automatic fallback chains
Route traffic across providers. If one 5xx's or rate-limits, the next in the chain serves the request — your code never notices.
Per-key quotas
Give each service, user or environment its own budget. No one team can burn the whole cap in a runaway loop.
Streaming, tools, structured outputs
SSE streaming, tool calls, JSON mode, schema enforcement. Everything you expect from the OpenAI API, on every model.
One invoice, one balance
Stop reconciling bills from five vendors. One credit balance, one receipt, one number to watch.
Observability out of the box
Per-request traces, latency, tokens, cost. Filter by API key, model, customer. Export to your warehouse.
Built-in API for developers
Every plan includes OpenAI-compatible API access. Same models, same credits, same workspace. Drop-in replacement — just change the base URL.
from openai import OpenAI
client = OpenAI(
base_url="https://api.infery.ai/v1",
api_key="inf_live_..."
)
response = client.chat.completions.create(
model="gpt-5.5",
messages=[{"role": "user", "content": "Hello!"}],
stream=True
)
for chunk in response:
print(chunk.choices[0].delta.content, end="")Fallback chains that save your night
Define a list of models, ordered by preference. If the upstream provider 5xx's or rate-limits, we retry the next one before your request even returns an error. Your code stays simple; your service stays up.
- Automatic retry on 5xx / timeout / rate limit
- Transparent to the client SDK
- Per-key fallback policies
- Logged for post-incident review
Frequently asked questions
Which SDKs work out of the box?
Any OpenAI-compatible SDK: openai-python, openai-node, LangChain, LlamaIndex, Vercel AI SDK, Mastra, and anything that takes a base URL. Change one line and you're in.
What's the latency overhead?
Typically 5-15 ms over a direct provider call for the routing layer. Streaming starts as soon as the upstream starts — we don't buffer.
Do you support tool calls and structured outputs?
Yes. Tool calls, JSON mode, and strict schema enforcement work across every provider that supports them. For providers that don't, we emulate via prompt engineering.
How do fallback chains work?
Define an ordered list of models in your API key config. On 5xx, timeout, or rate limit, we retry against the next one. Single response to the client, transparent to your code.
Can I pin a model version for reproducibility?
Yes — every model has both a floating alias (e.g., claude-sonnet-latest) and pinned versions (e.g., claude-sonnet-4-6-20260115).
What are the rate limits?
Per-plan and per-key. Limits are visible in the dashboard and in response headers. Enterprise plans come with custom quotas.
Ship your AI feature this week
Free trial credits. OpenAI-compatible. No credit card required to start.