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qwen/qwen3-coder-next

qwen/qwen3-coder-next

262,144 context · $0.15/M input tokens · $0.80/M output tokens

Qwen3-Coder-Next is an open-weight causal language model optimized for coding agents and local development workflows. It uses a sparse MoE design with 80B total parameters and only 3B activated per...

Pricing

Pay-per-use

No upfront costs, pay only for what you use

Input$0.15 / M Tokens
Output$0.80 / M Tokens
Cache Read$0.07 / M Tokens

Try the model

qwen/qwen3-coder-next
Online
alibaba
Hi! I am a helpful AI assistant. What can I do for you?

API Usage

Use the following code examples to integrate with our API:

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://llm.wavespeed.ai/v1"
)

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

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

Model Introduction

Qwen qwen3-coder-next

Qwen3-Coder-Next is an open-weight causal language model optimized for coding agents and local development workflows

Qwen3-Coder-Next is an open-weight causal language model optimized for coding agents and local development workflows. It uses a sparse MoE design with 80B total parameters and only 3B activated per token, delivering performance comparable to models with 10 to 20x higher active compute, which makes it well suited for cost-sensitive, always-on agent deployment.

The model is trained with a strong agentic focus and performs reliably on long-horizon coding tasks, complex tool usage, and recovery from execution failures. With a native 256k context window, it integrates cleanly into real-world CLI and IDE environments and adapts well to common agent scaffolds used by modern coding tools. The model operates exclusively in non-thinking mode and does not emit <think> blocks, simplifying integration for production coding agents.


Why It Looks Great

  • Large Language Model architecture for efficient processing
  • 262144 context window for long document handling
  • Competitive pricing at $0.1/$0.3 per million tokens

Key Features

  • Context Window: 262144 tokens
  • Max Output: 65536 tokens
  • Vision: Supported
  • Function Calling: Supported

Specifications

SpecificationValue
ProviderQwen
Model TypeLarge Language Model (LLM)
ArchitectureN/A
Context Window262144 tokens
Max Output65536 tokens
InputText
OutputText
VisionSupported
Function CallingSupported

Pricing

Token TypeCost per Million Tokens
Input$0.1
Output$0.3

How to Use

  1. Write your prompt — describe the task, provide context, and specify desired output format.
  2. Submit — the model processes your request and returns the response.

API Integration

Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: qwen/qwen3-coder-next


API Usage

Python SDK

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://llm.wavespeed.ai/v1"
)

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

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

cURL

curl https://llm.wavespeed.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "qwen/qwen3-coder-next",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Notes

  • Model: qwen/qwen3-coder-next
  • Provider: Qwen

Info

Provideralibaba
Typellm

Supported Functionality

Input
Text
Output
Text
Context262,144
Max Output65,536
Vision-
Function Calling✓ Supported

API Access Guide

Base URLhttps://llm.wavespeed.ai/v1
API Endpointchat/completions
Model IDqwen/qwen3-coder-next

Qwen3 Coder Next API

qwen/qwen3-coder-next

Qwen3-Coder-Next is an open-weight causal language model optimized for coding agents and local development workflows. It uses a sparse MoE design with 80B total parameters and only 3B activated per...

Input

$0.15 /M

Output

$0.8 /M

Context

262K

Max Output

66K

Tool Use

Supported

Try Qwen3 Coder Next on WaveSpeedAI

Access Qwen3 Coder Next through our unified API — OpenAI-compatible, no cold starts, transparent pricing.

Frequently Asked Questions about Qwen3 Coder Next

How much does Qwen3 Coder Next cost via the API?+

Pricing on WaveSpeedAI: $0.15 per million input tokens and $0.80 per million output tokens. Prompt caching and batch processing are billed separately and reduce effective cost on long, repetitive workloads.

What is the context window of Qwen3 Coder Next?+

Qwen3 Coder Next supports up to 262K tokens of context with up to 66K tokens of output per request.

Is Qwen3 Coder Next OpenAI-compatible?+

Yes. WaveSpeedAI exposes Qwen3 Coder Next through an OpenAI-compatible endpoint at https://llm.wavespeed.ai/v1. Point the official OpenAI SDK at this base URL with your WaveSpeedAI API key — no other code changes required.

How do I get started with Qwen3 Coder Next?+

Sign in to WaveSpeedAI, create an API key in Access Keys, then send a request to https://llm.wavespeed.ai/v1/chat/completions with model id set to the value shown above. New accounts receive free credits to evaluate Qwen3 Coder Next before paying per token.

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