Laminarity Relay
Pay-per-request LLM inference for AI agents, served by open-weight models (DeepSeek, GLM, MiniMax). OpenAI-compatible; paid in USDC via x402 — no signup, no API keys.
Quickstart (x402, no account)
POST /v1/chat/completions with an OpenAI chat body (model, messages, optional max_tokens and stream). The first call returns HTTP 402 with x402 payment requirements; sign the USDC payment and retry with the PAYMENT-SIGNATURE header. The price is quoted from the prompt size and max_tokens, so set max_tokens to pay less. GET /v1/models lists models and per-token prices.
curl -i https://api.laminarity.uk/v1/chat/completions \
-H 'content-type: application/json' \
-d '{"model":"deepseek-ai/DeepSeek-V4-Flash-0731","messages":[{"role":"user","content":"Hello"}],"max_tokens":64}'
# → HTTP 402 with x402 payment requirements (USDC).
# Sign the payment with any x402 client and repeat the request with the PAYMENT-SIGNATURE header.
With an API key (prepaid credits)
Sign in with a wallet at https://api.laminarity.uk/app, top up credits and create a key. Then use any OpenAI SDK:
from openai import OpenAI
client = OpenAI(base_url="https://api.laminarity.uk/v1", api_key="YOUR_KEY")
print(client.chat.completions.create(model="deepseek-ai/DeepSeek-V4-Flash-0731",
messages=[{"role": "user", "content": "Hello"}]).choices[0].message.content)
Endpoints
| Method | Path | What it does |
|---|---|---|
| POST | /v1/chat/completions | OpenAI-compatible chat completion (stream supported). Paid per request via x402 or with an API key. |
| GET | /v1/models | Models and per-token prices. Free. |
| GET | /openapi.json | OpenAPI 3.1 description with x402 payment info. |
| GET | /apis.json | APIs.json catalog entry. |
| GET | /status | Service health. |
Pricing
Price is quoted per request from the prompt size and max_tokens; set max_tokens to pay less. Current per-token prices: /v1/models.
Models
Open-weight models: DeepSeek V4 Flash, GLM 5.3 Flash, MiniMax M2.7. Each also has its own endpoint, e.g. /v1/deepseek-v4-flash/chat/completions; see /llms.txt.