Purpose-built for code

Qwen3-Coder

Name: Qwen3-Coder
Author: Alibaba

by Alibaba

Chat Tools

Qwen3-Coder is tuned for software engineering and agentic coding, with tool calling and a 256K-token context for whole-repository work.

Publisher: Alibaba
Context window: 256K tokens
Sizes: 30B, 480B
Licence: Apache 2.0

Model card on Hugging Face

Run Qwen3-Coder

Install it on a Pendra worker, then call it through the OpenAI-compatible API with a pdr_sk_ key.

from pendra import Pendra

client = Pendra(api_key="pdr_sk_...")

response = client.chat.completions.create(
    model="qwen3-coder:30b",
    messages=[{"role": "user", "content": "Hello!"}],
)

print(response.choices[0].message.content)

import { Pendra } from "pendra";

const client = new Pendra({ apiKey: "pdr_sk_..." });

const response = await client.chat.completions.create({
  model: "qwen3-coder:30b",
  messages: [{ role: "user", content: "Hello!" }],
});

console.log(response.choices[0].message.content);

Run Qwen3-Coder on your own UK infrastructure

Deploy a worker, install Qwen3-Coder, and start serving it through one sovereign API endpoint.

Get started free Read the quickstart

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