Qwen3-Coder-Flash-2025-07-28

Qwen3-Coder-Flash

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Text Generation

Overview

Text Generation

Based on Qwen3, this code generation model inherits the coding agent capabilities of Qwen3-Coder-Plus and supports multi-turn tool interaction. It features focused optimizations on repository-level understanding and enhanced tool-calling stability. This version is a snapshot dated July 28, 2025.

Input

Text

Output

Text

Features

Prefix Completion

Function Calling

Cache

Structured Outputs

Batches

Web Search

Pricing

Input
$0.3Per 1M tokens
Output
$1.5Per 1M tokens

Input
$0.3Per 1M tokens
Output
$1.5Per 1M tokens

Context

Max Input

997.95K

Max Output

65.53K

Rate Limits

RPMRequests Per Minute
600
TPMTokens Per Minute
5M

API Reference

Get API Key

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import os
from openai import OpenAI

client = OpenAI(
    # If the environment variable is not set, replace it with your Model Studio API key: api_key="sk-xxx",
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    base_url="https://[workspace-id].ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1",
)
completion = client.chat.completions.create(
    model="qwen3-coder-flash-2025-07-28",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Who are you?"},
    ],
    stream=True
)
for chunk in completion:
    print(chunk.choices[0].delta.content, end="", flush=True)

import os
from openai import OpenAI

client = OpenAI(
    # If the environment variable is not set, replace it with your Model Studio API key: api_key="sk-xxx",
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    base_url="https://[workspace-id].ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1",
)
completion = client.chat.completions.create(
    model="qwen3-coder-flash-2025-07-28",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Who are you?"},
    ],
    stream=True
)
for chunk in completion:
    print(chunk.choices[0].delta.content, end="", flush=True)