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Qwen: Qwen3.5 397B A17B Coding Benchmark

The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. It delivers...

Context262,144tokens
Max Output65,536tokens
Inputmodalities
Price$0.39/1M input
Ranks from Kilo Code LeaderboardPricing via OpenRouter

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Coding Performance

Coding benchmarks and performance metrics for development tasks

OpenClaw Benchmarks

PinchBench measures how Qwen: Qwen3.5 397B A17B performs on real OpenClaw agent tasks: multi-step execution, tool use, recovery, latency, and cost.

Explore OpenClaw PinchBench run

Average score

80.5%

#20 of 50 official models

Average time

18m 16s

10 runs · per OpenClaw task

Average cost

$1.006

Per benchmark run

Category breakdown

Best verified PinchBench v2 run by OpenClaw task family.

Basic100.0% · 1/1 cleared
Calendar100.0% · 1/1 cleared
Coding100.0% · 1/1 cleared
Data Analysis100.0% · 1/1 cleared

Top task results

Highest-scoring benchmark tasks from the same submission.

Calendar
Calendar Event Creation
100.0%
File Ops
Create Project Structure
100.0%
Data Analysis
CSV and Excel Data Summarization
100.0%
File Ops
File Structure Creation
100.0%
Basic
Sanity Check
100.0%
File Ops
Search and Replace in Files
100.0%

Autonomous task execution

Qwen: Qwen3.5 397B A17B 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

Real-World Usage

Real-world usage statistics from the Kilo Code community

No usage data available for this model yet.

No ranking data available for this model yet.

Real-world metrics from the Kilo Code Leaderboard

Pricing

Cost per 1 million tokens

Input Tokens
$0.39
per 1M tokens
Output Tokens
$2.34
per 1M tokens

Example Cost

Analyzing a 10,000 line codebase (≈40k input tokens, 10k output tokens) costs approximately $0.0390

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/qwen3.5-397b-a17b
Created
February 16, 2026
Tokenizer
Qwen3
Input Modalities
TextImageVideo
Context Window
262,144 tokens
Max Completion Tokens
65,536 tokens
Input Price
$0.39 per 1M tokens
Output Price
$2.34 per 1M tokens
Content Moderation
Disabled

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