---
title: Chat Completion with Qwen3.8 Flash 27B
slug: chat-completion-with-qwen3-8-flash-27b
url: https://apyhub.com/flonno/service/chat-completion-with-qwen3-8-flash-27b
provider: Flonno
tags: [llm-chat, chat-completions, model-listing, generative-ai, text-generation]
auth: bearer
version: 2026-10-12
service_type: sync
endpoints: 1
atoms: 1
mcp: true
---

# Chat Completion with Qwen3.8 Flash 27B

Generate text with Qwen3.8 Flash 27B. JSON chat completions, model discovery, and usage-based metering for coding and text workflows.

## Endpoints

| Method | URL | Description | Atoms |
| --- | --- | --- | --- |
| POST | `https://api.eu.apyhub.com/flonno/chat-completion-with-qwen3-8-flash-27b/chat/completions` | What it does Generates a text chat completion from the messages you provide. You send a model name… | 1 |

## Endpoint reference

### Generate a Qwen text chat completion

`POST https://api.eu.apyhub.com/flonno/chat-completion-with-qwen3-8-flash-27b/chat/completions` · 1 atoms · accepts `application/json` · returns `application/json`

| Parameter | In | Type | Required | Description |
| --- | --- | --- | --- | --- |
| `model` | body | string | yes | One of: qwen3.8-27b. Default: `qwen3.8-27b`. |
| `top_p` | body | number | no |  |
| `stream` | body | boolean | no | One of: false. Default: `false`. |
| `messages` | body | array of object | yes |  |
| `messages[].role` | body | string | yes | One of: system, user, assistant. |
| `messages[].content` | body | string | yes |  |
| `max_tokens` | body | integer | no | Default: `1024`. |
| `temperature` | body | number | no |  |
| `reasoning_effort` | body | string | no | One of: none, low, medium, high. Default: `none`. |

#### Quickstart

Create a chat completion with the required `model` and `messages`.

```bash
curl -X POST "https://api.eu.apyhub.com/flonno/chat-completion-with-qwen3-8-flash-27b/chat/completions" \
  -H "apy-token: $APY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen3.8-27b",
    "messages": [
      {
        "role": "user",
        "content": "Hello, how are you?"
      }
    ],
    "max_tokens": 256
  }'
```

#### What you'll get back

A JSON object. The generated text is in `choices[0].message.content`.

```json
{
  "id": "chatcmpl-3e13a3a3f428b2a7",
  "object": "chat.completion",
  "created": 1791873923,
  "model": "qwen3.8-27b",
  "choices": [
    {
      "finish_reason": "stop",
      "index": 0,
      "logprobs": null,
      "message": {
        "content": "I'm doing well, thank you for asking! How are you doing today? Is there anything specific I can help you with?",
        "refusal": null,
        "role": "assistant"
      }
    }
  ],
  "usage": {
    "completion_tokens": 27,
    "completion_tokens_details": {
      "reasoning_tokens": 0
    },
    "prompt_tokens": 15,
    "prompt_tokens_details": {
      "cached_tokens": 0
    },
    "total_tokens": 42
  }
}
```

## About

## What it does
Chat Completion generates a text response from a chat-style message list. Send a `model` and a `messages` array with one or more entries, each with a `role` of `system`, `user`, or `assistant` and a `content` string. You can also set `stream` to `true` for streamed output, and `max_tokens` to control the length of the reply.

Use Chat Completion when you need a conversational LLM endpoint for assistants, drafting, classification, or controlled text generation inside your app. The request format is simple and keeps the conversation history explicit, so you can build prompts from your own application state and send exactly the context you want the model to use.

The response schema is open-ended, so the exact payload depends on the model and runtime. In practice, you should treat the result as the completion object returned by the model call and parse it according to your integration requirements. This makes Chat Completion suitable for workflows where you want to route user input to an LLM and handle the generated text in your own code.

## Usage

Base URL: `https://api.eu.apyhub.com` (default region — see
`GET https://apyhub.com/api/public/regions` for the rest).

Authenticate with an ApyHub API key in the `apy-token` header.
Full docs and a live playground: https://apyhub.com/flonno/service/chat-completion-with-qwen3-8-flash-27b