Inference API (OpenAI-compatible)

Green Compute serves open models behind an OpenAI-compatible API. Any OpenAI SDK or tool works once you change the base URL and key.

• Base URL: https://api.green-compute.com/v1
• Auth: Authorization: Bearer <your API key>

List models

curl -s https://api.green-compute.com/v1/models -H "Authorization: Bearer $GC_KEY"

Use an id from this list verbatim as model. Per-token prices for each listed model are in GET https://api.green-compute.com/platform/pricing (public).

Chat completions

curl -s https://api.green-compute.com/v1/chat/completions \
  -H "Authorization: Bearer $GC_KEY" -H "Content-Type: application/json" \
  -d '{
    "model": "<id from /v1/models>",
    "messages": [{"role": "user", "content": "Say hello in five words."}],
    "max_tokens": 200
  }'

Python

from openai import OpenAI

client = OpenAI(base_url="https://api.green-compute.com/v1", api_key="YOUR_KEY")
resp = client.chat.completions.create(
    model="<id from /v1/models>",
    messages=[{"role": "user", "content": "Say hello in five words."}],
    max_tokens=200,
)
print(resp.choices[0].message.content)

Streaming

Set "stream": true. Responses are standard server-sent events, ending with data: [DONE]. The final chunk carries usage. If you disconnect mid-stream, you are billed only for the tokens actually generated.

Tool calling

Standard OpenAI tools / tool_choice are passed through. tool_calls come back in the usual place on the message.

Reasoning models

Some models think before answering. For those:

• the thinking arrives in message.reasoning_content (not reasoning) and the answer in message.content;
• thinking counts against max_tokens, so budget generously (2000+). If content comes back empty, the model ran out of budget while thinking; raise max_tokens and retry.

Using it from coding tools

Any tool that accepts a custom OpenAI base URL works:

Billing

Per token, input and output priced separately, with a small minimum charge per request. See GET /platform/pricing for the live figures.