Qwen2.5-Open-Source

Will be retired on October 10, 2026View announcement

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Overview

The new multi-modal understanding and generation model trained based on Qwen2.5. It supports text, image, speech, video, and mixed input understanding and can simultaneously generate streams of text and speech, significantly improves the speed of multi-modal content understanding. It provides four natural tones.

Input

TextImageVideoAudio

Output

TextAudio

Features

Prefix Completion

Enable Partial Mode when calling the Qwen API to make the model continue strictly from your provided prefix text.View docs

Function Calling

Use function calling to connect large language models with external tools and systems.View docs

Cache

Context Cache stores shared prefixes for long-context requests to reduce repeated computation, improve latency, and lower cost.View docs

Structured Outputs

Structured Outputs help ensure the model returns a JSON string in the expected format.View docs

Batches

Asynchronously process requests in batches to reduce costs.View docs

Web Search

Enable web search so the model can answer with real-time retrieved data.View docs

Fine-tuning

Train models on sample data to better adapt them to specific tasks.View docs

Pricing

Input: Text
$0.1Per 1M tokens
Input: Audio
$6.76Per 1M tokens
Input: Vision
$0.28Per 1M tokens
Output: Text (When input contains only text)
$0.4Per 1M tokens
Output: Text (When input contains images/audio/video)
$0.84Per 1M tokens
Output: Text&Audio (Output text is not charged)
$13.51Per 1M tokens

Rate Limits & Context

Max Input
30K
Max Output
2K
Context
32K

API Reference

Call API

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import os
from openai import OpenAI

client = OpenAI(
    # The API keys for the Singapore and Beijing regions are different. To obtain an API key, see: https://www.alibabacloud.com/help/en/model-studio/get-api-key
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    base_url="https://maas.qwencloudapi.com/compatible-mode/v1",
)

completion = client.chat.completions.create(
    model="qwen2.5-omni-7b",
    messages=[{"role": "user", "content": "Who are you"}],
    # Set the modality for the output data. The following modalities are supported: ["text","audio"]、["text"]
    modalities=["text", "audio"],
    audio={"voice": "Ethan", "format": "wav"},
    # The stream parameter must be set to True. Otherwise, an error is reported
    stream=True,
    stream_options={"include_usage": True},
)

for chunk in completion:
    if chunk.choices:
        print(chunk.choices[0].delta)
    else:
        print(chunk.usage)