CrossModel
Qwen3.7 Max
qwen/qwen3.7-max
Back to model catalog

Qwen · Model guide

Qwen3.7 Max

Compare
qwen/qwen3.7-max20% off

Qwen3.7's largest public flagship is a text-only 1M-context reasoning model for complex programming, multilingual knowledge work, office productivity and long-running autonomous agents.

Modalities
TextText
Context
1M
Max output
66K
Price / 1M tokens
$ 1.88$ 1.50in$ 4.50out
StreamingTool callingJSON outputImage inputThinking mode · can be turned off

What this model is good at

What the vendor positions it for, and which of our models to reach for instead.

VendorThe largest and most capable Qwen3.7 model, focused on programming, productivity and long autonomous execution.source

Best for

  • Complex reasoning · Qwen recommends Max when the strongest reasoning in the hosted family is required.(vendor claim)source

  • Long-running coding agents · Positioned for programming and sustained autonomous execution over large contexts.(vendor claim)source

Neighbouring models
Compare them side by side →

Pricing and billing

Billed per token. Cached input is charged at the cache-read rate.

Price / 1M tokensYou pay
Input$ 1.88$ 1.50
Output$ 5.63$ 4.50
Cache read$ 0.38$ 0.30
Cache write$ 2.35$ 1.88
Estimate a request
$ 0.0240
Estimated cost per request
10.0K × $ 1.50
+ 2.0K × $ 4.50
≈ $ 24.05 per 1,000 requests

Capabilities and limits

What CrossModel guarantees across every route this model can take right now.

Context window
1.0M tokens
Max output
65.5K tokens
Input / output modalities
Text → Text
Streaming
Supported
Tool calling
Supported
Structured output (JSON)
Supported
Image input
Not supported
Thinking mode
Supported· can be turned off
Available endpoints
/v1/chat/completions · /v1/responses · /v1/messages
First-party sources:Specsqwencloud.comCapabilitiesqwencloud.com 1help.aliyun.com 2

Published benchmarks

Scores the vendor reported, with the evaluation setup each one came from.

Agentic coding
  • Terminal-Bench 2.0
    pass_rate·Qwen Team · 2026-05-21Terminussetup not fully disclosed
    69.7%
Coding
  • SWE-Bench Pro
    resolved_rate·Qwen Team · 2026-05-21setup not fully disclosed
    60.6%
  • SWE-Bench Verified
    resolved_rate·Qwen Team · 2026-05-21setup not fully disclosed
    80.4%
Instruction following
  • IFBench
    score·Qwen Team · 2026-05-21setup not fully disclosed
    79.1%
Long context
  • MRCR v2 128K
    score·Qwen Team · 2026-05-21setup not fully disclosed
    90.4%
Reasoning
  • Humanity's Last Exam
    accuracy·Qwen Team · 2026-05-21setup not fully disclosed
    41.4%
  • Humanity's Last Exam (with tools)
    accuracy·Qwen Team · 2026-05-21setup not fully disclosed

    Tool set was not disclosed.

    53.5%
Scientific reasoning
  • GPQA Diamond
    accuracy·Qwen Team · 2026-05-21setup not fully disclosed
    92.4%
Tool use
  • MCPMark
    score·Qwen Team · 2026-05-21setup not fully disclosed
    60.8%

Vendor-reported numbers, not CrossModel measurements. Scores are only comparable when the benchmark version, metric and evaluation setup match, so nothing here is averaged or ranked.

Use it in your tools

Point the base URL at CrossModel and paste this model ID — every tool below has a setup guide.

Claude Code
Anthropic's official command-line coding assistant
Cursor
AI-first code editor
Cline
Open-source AI coding agent for VS Code
Codex
OpenAI's coding agent for ChatGPT desktop and the terminal
OpenCode
Open-source terminal coding assistant
Zed
High-performance, AI-native code editor
Open WebUI
Open-source, self-hosted AI chat interface
Continue
Open-source AI coding assistant for VS Code & JetBrains
See all integration guides →

Frequently asked questions

What is Qwen3.7 Max?
Qwen3.7 Max is available on CrossModel as qwen/qwen3.7-max. It has a 1M-token context window and can return up to 66K tokens per request.
How much does Qwen3.7 Max cost?
Currently $ 1.50 per 1M input tokens and $ 4.50 per 1M output tokens. Cached input is billed at $ 0.30 per 1M.
Does Qwen3.7 Max support tool calling and structured output?
Tool calling: Supported · Structured output (JSON): Supported · Image input: Not supported · Streaming: Supported · Thinking mode: Supported
Which endpoint do I call?
For text models, OpenAI Chat Completions (/v1/chat/completions), OpenAI Responses (/v1/responses) and Anthropic Messages (/v1/messages) all work — pick whichever your SDK already speaks.
Can I try it without writing code?
Yes. Sign in and open the Playground on this page to chat with the model directly — no API key needed. Usage is billed from your wallet at the normal rate.

Chat first, integrate later

Chat first, then wire it in once you like the answers.