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alibaba
qwen/qwen3.7-max

qwen/qwen3.7-max

1,000,000 context · $2.50/M input tokens · $7.50/M output tokens

Qwen3.7-Max is Alibaba’s flagship model in the Qwen3.7 series, built for agent-centric text workflows. It is optimized for coding, debugging, office automation, productivity tasks, tool use, and long-horizon autonomous execution. With a 1M-token context window and up to 64K output tokens, it is well suited for large documents, repository-scale coding, multi-step planning, structured generation, and workflows that require sustained reasoning across hundreds or thousands of steps.

Preise

Pay-per-Use

Keine Vorabkosten, zahlen Sie nur, was Sie nutzen

Eingabe$2.50 / M Tokens
Ausgabe$7.50 / M Tokens
Cache Read$0.25 / M Tokens
Cache Write$3.13 / M Tokens

Modell ausprobieren

qwen/qwen3.7-max
Online
alibaba
Hallo! Ich bin ein hilfreicher KI-Assistent. Womit kann ich helfen?

API-Nutzung

Verwenden Sie die folgenden Codebeispiele zur Integration mit unserer 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/qwen3.7-max",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

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

Modelleinführung

Qwen: Qwen3.7 Max

Qwen3.7-Max is Alibaba’s flagship model in the Qwen3.7 series, designed for agent-centric text workflows. It is optimized for coding, debugging, office automation, productivity tasks, tool use, and long-horizon autonomous execution.


Why It Looks Great

  • Flagship Qwen3.7 model built for agentic workloads
  • Strong fit for coding, debugging, office automation, productivity tasks, and tool use
  • 1M-token context window for long prompts, large documents, codebases, and multi-turn workflows
  • Up to 64K output tokens for extended reasoning, coding, and structured generation
  • Designed for long-horizon autonomous execution across complex multi-step tasks
  • Function calling and tool-use support for agentic application workflows
  • Structured output support for JSON responses and schema-constrained generation
  • Reasoning controls for tuning latency, quality, and cost per request

Key Features

  • Context Window: 1,000,000 tokens
  • Max Input: 934,464 tokens
  • Max Output: 65,536 tokens
  • Input: Text
  • Output: Text
  • Vision: Not listed
  • Function Calling: Supported
  • Structured Outputs: Supported
  • Thinking Mode: Supported
  • Image Generation: Not listed
  • Audio Input: Not listed
  • Supported Parameters: include_reasoning, logprobs, max_tokens, presence_penalty, reasoning, response_format, seed, structured_outputs, temperature, tool_choice, tools, top_logprobs, top_p

Specifications

SpecificationValue
Provideralibaba
Model TypeChat Completions model
Architecturetext->text
Context Window1,000,000 tokens
Max Input934,464 tokens
Max Output65,536 tokens
InputText
OutputText
VisionNot listed
Function CallingSupported
Structured OutputsSupported
Thinking ModeSupported
Primary Use CasesCoding, office automation, productivity workflows, long-horizon agents, tool use
ReleaseMay 2026

Pricing

Token TypeCost
Input$2.50 per million tokens
Output$7.50 per million tokens
Cache Write$3.125 per million tokens

How to Use

  1. Write your prompt - describe the task, provide context, and specify the 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/qwen3.7-max


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/qwen3.7-max",
    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/qwen3.7-max",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Notes

  • Model: qwen/qwen3.7-max
  • Provider: alibaba
  • Best suited for coding agents, office automation, long-context text workflows, multi-step productivity tasks, tool use, and structured output generation

Info

Anbieteralibaba
Typllm

Unterstützte Funktionen

Eingabe
Text
Ausgabe
Text
Kontext1,000,000
Max. Ausgabe65,536
Vision-
Function Calling✓ Unterstützt

API-Zugriffsanleitung

Base URLhttps://llm.wavespeed.ai/v1
API-Endpunktchat/completions
Modell-IDqwen/qwen3.7-max

Qwen3.7 Max API

qwen/qwen3.7-max

Qwen3.7-Max is Alibaba’s flagship model in the Qwen3.7 series, built for agent-centric text workflows. It is optimized for coding, debugging, office automation, productivity tasks, tool use, and long-horizon autonomous execution. With a 1M-token context window and up to 64K output tokens, it is well suited for large documents, repository-scale coding, multi-step planning, structured generation, and workflows that require sustained reasoning across hundreds or thousands of steps.

Eingabe

$2.5 /M

Ausgabe

$7.5 /M

Kontext

1000K

Max. Ausgabe

66K

Tool-Nutzung

Unterstützt

Qwen3.7 Max auf WaveSpeedAI testen

Zugriff auf Qwen3.7 Max über unsere einheitliche API — OpenAI-kompatibel, keine Kaltstarts, transparente Preise.

Häufige Fragen zu Qwen3.7 Max

Wie viel kostet die Qwen3.7 Max-API?+

Preise auf WaveSpeedAI: $2.50 pro Million Input-Tokens und $7.50 pro Million Output-Tokens. Prompt-Caching und Batch-Verarbeitung werden separat berechnet und reduzieren die effektiven Kosten bei langen, sich wiederholenden Workloads.

Wie groß ist das Kontextfenster von Qwen3.7 Max?+

Qwen3.7 Max unterstützt bis zu 1000K Kontext-Tokens und bis zu 66K Output-Tokens pro Anfrage.

Ist Qwen3.7 Max OpenAI-kompatibel?+

Ja. WaveSpeedAI stellt Qwen3.7 Max über einen OpenAI-kompatiblen Endpunkt unter https://llm.wavespeed.ai/v1 bereit. Richten Sie das offizielle OpenAI SDK mit Ihrem WaveSpeedAI-API-Schlüssel auf diese Base-URL — keine weiteren Codeänderungen erforderlich.

Wie starte ich mit Qwen3.7 Max?+

Bei WaveSpeedAI anmelden, in Access Keys einen API-Schlüssel erstellen und eine Anfrage an https://llm.wavespeed.ai/v1/chat/completions mit der oben angezeigten Model-ID senden. Neue Konten erhalten kostenlose Credits, um Qwen3.7 Max zu testen.

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