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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...

Preços

Pagamento por uso

Sem custo inicial, pague apenas pelo que usar

Entrada$0.15 / M Tokens
Saída$0.80 / M Tokens
Cache Read$0.07 / M Tokens

Experimentar o modelo

qwen/qwen3-coder-next
Online
alibaba
Olá! Sou um assistente de IA útil. Em que posso ajudar?

Uso da API

Use os exemplos de código abaixo para integrar com nossa 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)

Introdução do modelo

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

Provedoralibaba
Tipollm

Funcionalidades suportadas

Entrada
Texto
Saída
Texto
Contexto262,144
Saída máx.65,536
Vision-
Function Calling✓ Suportado

Guia de acesso à API

Base URLhttps://llm.wavespeed.ai/v1
API Endpointchat/completions
ID do modeloqwen/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...

Entrada

$0.15 /M

Saída

$0.8 /M

Contexto

262K

Saída máx.

66K

Uso de ferramentas

Suportado

Experimente Qwen3 Coder Next no WaveSpeedAI

Acesse Qwen3 Coder Next através da nossa API unificada — compatível com OpenAI, sem inicializações a frio, preços transparentes.

Perguntas frequentes sobre Qwen3 Coder Next

Quanto custa Qwen3 Coder Next via API?+

Preços no WaveSpeedAI: $0.15 por milhão de tokens de entrada e $0.80 por milhão de tokens de saída. Prompt caching e batch processing são cobrados separadamente e reduzem o custo efetivo em cargas longas e repetitivas.

Qual é a janela de contexto do Qwen3 Coder Next?+

Qwen3 Coder Next suporta até 262K tokens de contexto e até 66K tokens de saída por requisição.

Qwen3 Coder Next é compatível com OpenAI?+

Sim. O WaveSpeedAI expõe o Qwen3 Coder Next através de um endpoint compatível com OpenAI em https://llm.wavespeed.ai/v1. Aponte o SDK oficial da OpenAI para esta base URL com sua chave API do WaveSpeedAI — sem outras alterações no código.

Como começo a usar o Qwen3 Coder Next?+

Entre no WaveSpeedAI, crie uma chave API em Access Keys, então envie uma requisição para https://llm.wavespeed.ai/v1/chat/completions com o model id mostrado acima. Contas novas recebem créditos grátis para avaliar o Qwen3 Coder Next.

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