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OpenAI-compatible chat completions, completions, and responses, with streaming. Embeddings on their own page.

Last reviewed 2026-08-25

Create a chat completion

Use the OpenAI SDK with base_url set to https://api.mserve.ai/openai/v1.

from openai import OpenAI

client = OpenAI(base_url="https://api.mserve.ai/openai/v1", api_key="ms_live_your_key")

response = client.chat.completions.create(
    model="qwen3.8-27b",
    messages=[
        {"role": "system", "content": "Be brief."},
        {"role": "user", "content": "Write one sentence about GPUs."},
    ],
    temperature=0.2,
    max_tokens=64,
)
print(response.choices[0].message.content)

Stream tokens

Set stream to true. Chunks arrive as server-sent events. With stream_options.include_usage, the final chunk carries usage and an empty choices list.

stream = client.chat.completions.create(
    model="qwen3.8-27b",
    messages=[{"role": "user", "content": "Count to five."}],
    stream=True,
    stream_options={"include_usage": True},
)
for chunk in stream:
    if chunk.choices:
        print(chunk.choices[0].delta.content or "", end="")
    if chunk.usage:
        print("\ntokens:", chunk.usage.total_tokens)

Thinking

qwen3.8-27b thinks by default. Reasoning tokens are billed as output tokens. Turn thinking off for latency with reasoning_effort: "minimal", the same field the Realtime API uses.

response = client.chat.completions.create(model="qwen3.8-27b", messages=msgs, reasoning_effort="minimal")

Completions and responses

POST /openai/v1/completions and POST /openai/v1/responses work the same way. Responses covers text in, text out, and streaming. Stateful features return 400 (see Compatibility).

r = client.responses.create(model="qwen3.8-27b", input="Write one sentence about GPUs.")
print(r.output_text)

Models

GET /openai/v1/models lists the text and embedding models. With xi-api-key auth the same path returns the ElevenLabs models list.

Supported parameters

Rejected parameters per route are on Compatibility.

Prop

Type

Capacity errors

Pricing

ModelModel idInput per 1M tokensOutput per 1M tokens
Qwen3.8 27Bqwen3.8-27b$0.30$2.50

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