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alibaba
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...

Harga

Bayar sesuai pemakaian

Tanpa biaya di muka, bayar hanya sesuai penggunaan

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

Coba model

qwen/qwen3-coder-next
Online
alibaba
Hai! Saya asisten AI yang siap membantu. Ada yang bisa saya bantu?

Penggunaan API

Gunakan contoh kode berikut untuk integrasi dengan API kami:

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)

Pengenalan Model

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

Penyediaalibaba
Tipellm

Fitur yang Didukung

Input
Teks
Output
Teks
Konteks262,144
Output Maks65,536
Vision-
Function Calling✓ Didukung

Panduan Akses API

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

Konteks

262K

Output Maks.

66K

Penggunaan Tool

Didukung

Coba Qwen3 Coder Next di WaveSpeedAI

Akses Qwen3 Coder Next melalui API terpadu kami — kompatibel dengan OpenAI, tanpa cold start, harga transparan.

Pertanyaan Umum tentang Qwen3 Coder Next

Berapa biaya Qwen3 Coder Next melalui API?+

Harga di WaveSpeedAI: $0.15 per juta token input dan $0.80 per juta token output. Prompt caching dan batch processing ditagih terpisah dan mengurangi biaya efektif pada beban kerja yang panjang dan berulang.

Berapa context window Qwen3 Coder Next?+

Qwen3 Coder Next mendukung hingga 262K token konteks dengan hingga 66K token output per permintaan.

Apakah Qwen3 Coder Next kompatibel dengan OpenAI?+

Ya. WaveSpeedAI menyediakan Qwen3 Coder Next melalui endpoint yang kompatibel dengan OpenAI di https://llm.wavespeed.ai/v1. Arahkan OpenAI SDK resmi ke base URL ini dengan API key WaveSpeedAI Anda — tanpa perubahan kode lainnya.

Bagaimana memulai dengan Qwen3 Coder Next?+

Masuk ke WaveSpeedAI, buat API key di Access Keys, lalu kirim permintaan ke https://llm.wavespeed.ai/v1/chat/completions dengan model id seperti ditampilkan di atas. Akun baru menerima kredit gratis untuk menguji Qwen3 Coder Next.

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