A drop-in, OpenAI-compatible endpoint for GLM-5.2 and the leading open models. Confidential by design, with subscriptions or pay-per-token credits, no KYC. Keep your SDK, change one line.
# the same request you already send OpenAI curl https://api.libertai.io/v1/chat/completions \ -H "Authorization: Bearer $LIBERTAI_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "glm-5.2", "messages": [{"role": "user", "content": "Explain confidential inference."}], "stream": true }'
from openai import OpenAI client = OpenAI( base_url="https://api.libertai.io/v1", api_key="ltai-••••", ) stream = client.chat.completions.create( model="glm-5.2", messages=[{"role": "user", "content": "Explain confidential inference."}], stream=True, ) for chunk in stream: print(chunk.choices[0].delta.content or "", end="")
import OpenAI from "openai"; const client = new OpenAI({ baseURL: "https://api.libertai.io/v1", apiKey: process.env.LIBERTAI_API_KEY, }); const stream = await client.chat.completions.create({ model: "glm-5.2", messages: [{ role: "user", content: "Explain confidential inference." }], stream: true, }); for await (const chunk of stream) { process.stdout.write(chunk.choices[0]?.delta?.content ?? ""); }
Works with the tools you already use
The full OpenAI-compatible surface, running on a decentralized network that cannot keep your data. Everything you'd expect from a modern inference API, with privacy built into the architecture.
The API mirrors the OpenAI spec across chat, tools, vision, embeddings and streaming. Point your client at a new base URL and keep everything else: SDK, prompts and stack.
Read the migration guide# one line changes - base_url = "https://api.openai.com/v1" + base_url = "https://api.libertai.io/v1"
Requests are processed and forgotten. Sensitive workloads run inside Trusted Execution Environments with remote attestation, so you can verify the enclave instead of trusting a policy.
See how privacy worksGLM-5.2 leads, and the rest of the catalog is one parameter away. Prices shown are per-token credit rates; subscriptions cover steady usage at a fixed price.
Browse all modelsA subscription gives you a fixed monthly price for steady usage. Direct credits bill per million tokens, and overflow past your subscription is charged at the same per-token rate. No seats, no KYC.
Pricing detailsA plain HTTPS endpoint that speaks the OpenAI dialect. Reach for the terminal, the official SDKs, or wire it straight into your agents.
curl api.libertai.io/v1/chat/completions \ -H "Authorization: Bearer …" \ -d '{"model":"glm-5.2", …}'
One curl call and you're streaming tokens. Great for scripts and quick tests.
from openai import OpenAI client = OpenAI(base_url="…libertai.io/v1") client.chat.completions.create(…)
Use the official Python or JavaScript clients. Only the base URL changes.
tools = [{"type": "function", "function": {"name": "search"}}] client.chat.completions.create(tools=tools)
Function calling and JSON output plug into the agent frameworks you already run.
"Swapped one base URL and our whole stack was private. Nothing else in the codebase changed."
"Same class of output as the closed flagships, at a fraction of the token cost. Easy call for us."
"No KYC, no waitlist. I had a private endpoint answering requests before my coffee was cold."
"The attestation story is what sold our security team. We can verify the enclave, not just read a policy."
"Function calling worked out of the box with our existing agent framework. Genuinely drop-in."
"Open models, my choice of weights, and nothing logged. This is how inference should work."