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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...

가격

사용량 기반 과금

선결제 없이 사용한 만큼만 지불

입력$0.15 / M Tokens
출력$0.80 / M Tokens
Cache Read$0.07 / M Tokens

모델 사용해 보기

qwen/qwen3-coder-next
온라인
alibaba
안녕하세요! 도움이 되는 AI 어시스턴트입니다. 무엇을 도와드릴까요?

API 사용법

다음 코드 예시를 사용해 API와 연동하세요:

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)

모델 소개

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

정보

제공자alibaba
유형llm

지원 기능

입력
텍스트
출력
텍스트
컨텍스트262,144
최대 출력65,536
Vision-
Function Calling✓ 지원

API 접근 가이드

Base URLhttps://llm.wavespeed.ai/v1
API 엔드포인트chat/completions
모델 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...

입력

$0.15 /M

출력

$0.8 /M

컨텍스트

262K

최대 출력

66K

도구 사용

지원

WaveSpeedAI에서 Qwen3 Coder Next 체험

통합 API를 통해 Qwen3 Coder Next 액세스 — OpenAI 호환, 콜드 스타트 없음, 투명한 가격.

Qwen3 Coder Next에 대해 자주 묻는 질문

Qwen3 Coder Next API 비용은 얼마인가요?+

WaveSpeedAI 가격: 입력 토큰 100만 개당 $0.15, 출력 토큰 100만 개당 $0.80. 프롬프트 캐싱과 배치 처리는 별도로 청구되며 긴 반복 작업에서 실질 비용을 줄여 줍니다.

Qwen3 Coder Next의 컨텍스트 윈도우는 얼마나 되나요?+

Qwen3 Coder Next은 요청당 최대 262K 컨텍스트 토큰과 최대 66K 출력 토큰을 지원합니다.

Qwen3 Coder Next은 OpenAI 호환인가요?+

네. WaveSpeedAI는 OpenAI 호환 엔드포인트 https://llm.wavespeed.ai/v1을 통해 Qwen3 Coder Next을 제공합니다. 공식 OpenAI SDK의 base URL을 이 주소로 변경하고 WaveSpeedAI API 키를 사용하면 코드 변경 없이 사용할 수 있습니다.

Qwen3 Coder Next을 어떻게 시작하나요?+

WaveSpeedAI에 로그인하고 Access Keys에서 API 키를 만든 다음, 위에 표시된 모델 ID로 https://llm.wavespeed.ai/v1/chat/completions에 요청을 보내세요. 신규 계정은 Qwen3 Coder Next을 평가할 수 있는 무료 크레딧을 받습니다.

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