Qwen2.5 32B Instruct

Alibaba Qwen chatcode Free

API ID: qwen/qwen2.5-32b-instruct

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Input Price
Free
/1M tokens
Output Price
Free
/1M tokens

About Qwen2.5 32B Instruct

Qwen2.5 32B Instruct is the instruction-tuned variant of the latest Qwen large language model series. It provides enhanced instruction-following capabilities, improved proficiency in coding and mathematical reasoning, and robust handling of structured data and outputs such as JSON. It supports long-context processing up to 128K tokens and multilingual tasks across 29+ languages. The model has 32.5 billion parameters, 64 layers, and utilizes an advanced transformer architecture with RoPE, SwiGLU, RMSNorm, and Attention QKV bias. For more details, please refer to the [Qwen2.5 Blog](https://qwenlm.github.io/blog/qwen2.5/) .

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Price Ranking
#6 lowest price among 1240 Chat models — Top 20% cheapest!

Model Specifications

Context Length
131k
Max Output
—
Release Date
2025-03-03
Capabilities
chat code
Input Modalities
text
Output Modalities
text

Best For

  • Code generation, debugging, code review, refactoring
  • Conversations, content writing, general assistance

Consider Alternatives For

  • Image understanding (needs vision capability)
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This model is completely free!

No token costs - use it without worrying about API bills.

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Alibaba Qwen Model Lineup

Compare all models from Alibaba Qwen to find the best fit

Model Input Output Context Capabilities
Qwen2.5 32B Instruct Current Free Free 131k chat code
Qwen2.5-VL 7B Instruct Free Free 33k chat vision tool_use
Qwen3 Embedding 0.6B Free Free 8k chat code
Qwen3 Embedding 0.6B Free Free 8k chat code
Qwen2.5 VL 3B Instruct Free Free 64k chat vision code
Qwen2.5 VL 3B Instruct Free Free 64k chat vision code
View All Alibaba Qwen Models →

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🚀 Quick Start

Get started with Qwen2.5 32B Instruct API

OpenAI-compatible SDK 
from openai import OpenAI

client = OpenAI(
    base_url="https://api.provider.com/v1",
    api_key="YOUR_API_KEY"
)

response = client.chat.completions.create(
    model="qwen/qwen2.5-32b-instruct",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)
print(response.choices[0].message.content)

Resources

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