Qwen3.7 Max

qwen3.7-max

Qwen3.7 Max is positioned as the flagship model of the Qwen3.7 generation, with official messaging centered on the “agent frontier.” Model cards emphasize agent-centric work, coding, office/productivity tasks, and long-horizon autonomous execution. It should be described as a broad high-capability model for complex work rather than merely a larger chat model.

Context Window

1M tokens

Maximum Output

65.5K tokens

Release Date

May 21, 2026

Modalities

Qwen3.7 Max Pricing

Input Price	Output Price	Cache Read	Cache Create 5m	Cache Read 5m
$1.7143/M	$5.1429/M	$0.3429/M	$2.1429/M	$0.1714/M

Qwen3.7 Max API Capabilities

Reasoning

Supported

Tool calling

Supported

Temperature parameter

Supported

Attachments

Not supported

Knowledge Base

—

Endpoint Protocols

Completions APIMessages APIgemini

Qwen3.7 Max Model Highlights

Qwen3.7 Max combines agent-oriented reasoning, strong coding and productivity capabilities, and a one-million-token context for complex text workloads.

Agent-Level Reasoning

The model is designed to plan and sustain multi-step work, making it useful when tasks require repeated decisions and long-term execution.

Coding and Productivity

Its strengths cover programming, office work, and productivity tasks that require structured analysis and coordinated text generation.

Million-Token Context

A one-million-token context window supports large codebases, extensive documents, and long-running text interactions.

Qwen3.7 Max Use Cases

Qwen3.7 Max is suited to repository-scale development, long-running text agents, and analysis of extensive business or technical documents.

Repository-Scale Development

Examine dependencies across a large codebase, implement coordinated changes, and verify how modifications affect related components.

Long-Running Agents

Maintain goals and intermediate results while progressing through multi-step research, coding, or operational workflows.

Document-Intensive Analysis

Review extensive text collections, connect evidence across sections, and produce structured summaries, comparisons, or action plans.

How to Use Qwen3.7 Max via the TokenHub API

Create API key

import OpenAI from "openai"

const client = new OpenAI({
  apiKey: process.env.TOKENHUB_API_KEY,
  baseURL: "https://us-api.tokenhub.com/v1",
})

const result = await client.chat.completions.create({})
console.log(result.choices[0]?.message?.content)

Qwen3.7 Max Benchmarks

Qwen3.7 Max

Index score
Artificial Analysis Intelligence IndexArtificial Analysis Intelligence Index summarizes broad model capability across evaluation families.	Artificial Analysis broad capability aggregate	46
Artificial Analysis Coding IndexArtificial Analysis Coding Index summarizes model performance on coding and software engineering tasks.	Artificial Analysis software task aggregate	50.1
Knowledge & Reasoning
GPQAGPQA is a graduate-level science benchmark designed to test expert reasoning.	Advanced science problem solving	92.3%
HLEHLE is a broad, challenging benchmark for expert-level knowledge and reasoning across many domains.	Broad expert-level exam set	38.1%
Coding & Engineering
SciCodeSciCode evaluates Python programming for scientific computing, including algorithmic implementation from scientific context.	Scientific coding challenges	48.8%
Terminal-Bench HardTerminal-Bench Hard evaluates whether an AI agent can complete difficult tasks in a terminal environment.	Hard terminal task execution	50.8%
Instruction Following & Agent Tasks
IFBenchIFBench measures how reliably a model follows detailed instructions and constraints.	Prompt constraint adherence	80.5%
AA-LCRAA-LCR measures reasoning quality over extended context windows.	Long-context reasoning	69%
τ²-Benchτ²-Bench evaluates conversational agents in realistic workflows with tool and state constraints.	Agent workflow tasks	94.7%

Metrics sourced from Artificial Analysis

Qwen 3.7 Max FAQ

Qwen 3.7 Max: capabilities, use cases, limits, and TokenHub guidance.

How should teams view Qwen 3.7 Max?+

Qwen 3.7 Max is a Alibaba Qwen model for flagship coding, reasoning, and agent workflows.

What is Qwen 3.7 Max best for?+

Best for complex coding, agent workflows and tool-heavy automation, especially when maximum answer quality is the priority.

What is Qwen 3.7 Max's main strength?+

Key strength: broad agent capabilities across coding and tool-driven tasks and hybrid thinking that can switch between deliberate and direct responses.

Is Qwen 3.7 Max always the best choice?+

It uses more compute, so latency and cost can be higher. For multimodal input, consider Qwen 3.7 Plus.

What is the safest setup?+

Use the exact ID shown by TokenHub; follow your account docs and verify current features.

Ready to use Qwen3.7 Max?

Use one API key to access Qwen3.7 Max and more AI models through TokenHub.

Create API key

Qwen3.7 Max

Qwen3.7 Max Pricing

Qwen3.7 Max API Capabilities

Qwen3.7 Max Model Highlights

Agent-Level Reasoning

Coding and Productivity

Million-Token Context

Qwen3.7 Max Use Cases

Repository-Scale Development

Long-Running Agents

Document-Intensive Analysis

How to Use Qwen3.7 Max via the TokenHub API

Qwen3.7 Max Benchmarks

Models Similar to Qwen3.7 Max

Media and Discussions

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Qwen 3.7 Max FAQ

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