Streaming

Set "stream": true in the request body. Streaming works in both inference formats and does not change pricing.

Anthropic emits events such as message_start, content_block_delta, and message_stop. OpenAI emits data: {...} chunks and finishes with data: [DONE].

from openai import OpenAI
client = OpenAI(api_key="mg_live_...", base_url="https://api.model-gate.com/v1")
stream = client.chat.completions.create(model="claude-opus-4.8", messages=[{"role":"user","content":"Hello"}], stream=True)
for chunk in stream:
    text = chunk.choices[0].delta.content
    if text:
        print(text, end="", flush=True)

Keep the connection open and disable reverse-proxy buffering. Closing the client connection cancels upstream generation; already generated usage remains billable. See Errors for retry guidance.

Completion and missing usage

HTTP 200 confirms the stream began, not that inference finished. A provider error or interrupted/truncated stream is shown as failed or incomplete in Usage. Chat Completions completion is a finish reason for every requested choice or [DONE]; Responses uses response.completed; Anthropic uses message_stop. Keep the request ID and treat already received text/tool arguments as partial. The gateway does not silently repeat this request.

Provider-reported usage, including zero or partial counters, is authoritative. A confirmed successful text stream without usage may receive an explicitly labelled estimate based on decoded text/reasoning/tool-argument delta bytes, excluding SSE/JSON framing; explicit output limits cap estimates only. Failed or unsupported streams without usage show Usage unknown · review required and do not receive an automatic byte-estimated charge. Unknown is not proof that the provider execution was free. See Errors.