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Qwen: Qwen3.7 Max Coding Benchmark

Qwen3.7-Max is the flagship model in Alibaba's Qwen3.7 series. It supports text input and output and is designed for agent-centric workloads, with particular strengths in coding, office and productivity tasks,...

Context1,000,000tokens
Max Output131,072tokens
Inputmodality
Price$1.48/1M input
Ranks from Kilo Code LeaderboardPricing via OpenRouter

Try Qwen: Qwen3.7 Max in Kilo Code

Experience this model with the most popular open source coding agent. Free to start, pay only for AI usage. Use in popular IDEs like VS Code, JetBrains, command line, or cloud agents.

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Coding Performance

Coding benchmarks and performance metrics for development tasks

Kilo Bench

% Completion on Terminal Bench 2.0
54.6%
Cost per attempt (USD)
$20.65
Benchmark
Terminal Bench 2.0

Official Kilo eval results. Cost is averaged per complete benchmark attempt.

Security

Enkrypt AI red-team scores for Qwen: Qwen3.7 Max. Each value is the share of successful attacks on a 0–100 scale — lower is safer.

Overall risk
29.3

Lower is safer

Safety

36.9/ 100

Composite safety risk from Enkrypt red-team evaluations. Lower is safer.

NIST

29.0/ 100

Average attack success across NIST-mapped tests: bias, harm, toxicity, CBRN, and insecure code.

OWASP

32.0/ 100

Weighted average of the same tests using OWASP Top 10 for LLMs 2025 risk rankings.

Attack categories

Percentage of successful attacks in each Enkrypt red-team category.

Jailbreak26.9/ 100

Share of jailbreak tests that bypassed the model's safety constraints.

Bias74.4/ 100

Share of tests that elicited biased responses.

Harmful content8.9/ 100

Share of tests that produced dangerous, violent, or hateful content.

Toxicity4.4/ 100

Share of tests that produced toxic or abusive content.

CBRN49.8/ 100

Share of tests that elicited chemical, biological, radiological, or nuclear assistance.

Insecure code8.9/ 100

Share of tests that produced vulnerable or malicious code.

Score
Value
Overall risk
29.3 / 100
Safety
36.9 / 100
NIST
29.0 / 100
OWASP
32.0 / 100
Jailbreak
26.9 / 100
Bias
74.4 / 100
Harmful content
8.9 / 100
Toxicity
4.4 / 100
CBRN
49.8 / 100
Insecure code
8.9 / 100

Security scores from the Enkrypt AI Safety Leaderboard · Last checked Oct 2, 2026

Real-World Usage

Real-world usage statistics from the Kilo Code community

Weekly Token Usage

Mode Rankings (Last Week)

Where this model ranks for each built-in mode

Code

Write, modify, and refactor code

No data

Ask

Get answers and explanations

No data

Debug

Diagnose and fix software issues

No data

Orchestrator

Coordinate tasks across multiple modes

No data

Real-world metrics from the Kilo Code Leaderboard

OpenClaw Benchmarks

PinchBench measures how Qwen: Qwen3.7 Max performs on real OpenClaw agent tasks: multi-step execution, tool use, recovery, latency, and cost.

PinchBench run

Average score

92.5%

#2 of 50 official models

Average time

200m 5s

6 runs · per OpenClaw task

Average cost

$20.508

Per benchmark run

Category breakdown

Best verified PinchBench v2 run by OpenClaw task family.

Log Analysis97.7% · 15/30 cleared
Csv Analysis96.7% · 12/26 cleared
Writing95.8% · 2/6 cleared
Productivity95.5% · 4/8 cleared

Top task results

Highest-scoring benchmark tasks from the same submission.

Analysis
Access Control Log Anomaly Detection
100.0%
Csv Analysis
Apple Stock 2014 Best and Worst Days
100.0%
Csv Analysis
Apple Stock 2014 Trend Analysis
100.0%
Csv Analysis
Apple Stock 2014 Volatility Analysis
100.0%
Productivity
Calendar Event Creation
100.0%
Writing
Commit Message Writer
100.0%

Autonomous task execution

Qwen: Qwen3.7 Max shows strong average success across OpenClaw-style benchmark runs, useful for recurring research, browser, and file-based automations.

Tool use and recovery

PinchBench tasks stress multi-step planning, tool calls, and judge-verified completion rather than single prompt coding snippets.

Agent workflow fit

Its deliberate average runtime and premium run cost help set expectations for long-running agents and production workflows.

Agentic benchmarks from the PinchBench Leaderboard

Pricing

Cost per 1 million tokens

Input Tokens
$1.48
per 1M tokens
Output Tokens
$4.42
per 1M tokens

Example Cost

Analyzing a 10,000 line codebase (≈40k input tokens, 10k output tokens) costs approximately $0.1032

Coding Capabilities

Features and parameters relevant to coding tasks

Coding Features

Function Calling
Can call external functions/APIs
Tool Choice
Control over function selection
Structured Outputs
JSON schema validation
Reasoning Tokens
Extended thinking for complex problems

Pricing details from OpenRouter

Technical Details

Architecture and implementation specifications

Specifications
Model ID
qwen/qwen3.7-max
Created
May 21, 2026
Tokenizer
Qwen
Input Modalities
Text
Context Window
1,000,000 tokens
Max Completion Tokens
131,072 tokens
Input Price
$1.48 per 1M tokens
Output Price
$4.42 per 1M tokens
Cache Read Price
$0.29 per 1M tokens
Cache Write Price
$1.84 per 1M tokens
Content Moderation
Disabled

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  4. Start coding

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