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Qwen3.6 27B Thinking

alibaba/qwen3.6-27b:thinking
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Qwen3.6 27B Thinking

alibaba/qwen3.6-27b:thinking
BackTry Model

Qwen3.6 27B is a native vision-language dense model with stronger agentic coding and STEM reasoning than Qwen 3.5 27B. It also improves spatial intelligence (including object localization/detection), plus video understanding, document OCR, and visual-agent workflows.

Added Apr 23, 2026

Model weights

Context Window

260.1K

Max Output

65.5K

Avg output tokens (7d)

2.6K tokens

88%

Input Price (Auto)

$0.20/1M

Output Price (Auto)

$1.56/1M

Cache Read (Auto)

$0.098/1M

Capabilities

Benchmarks

Performance metrics and benchmarks

Sourced from Artificial Analysis.

Intelligence Index

37.7

Better than 81% of models compared

Coding Index

53.7

Better than 70% of models compared

Agentic Index

27.5

Better than 62% of models compared

Reasoning

GPQA Diamond

Graduate-level scientific reasoning

84.2%

Better than 78% of models compared

HLE

Humanity's Last Exam

23.1%

Better than 78% of models compared

IFBench

Instruction-following benchmark

67.6%

Better than 81% of models compared

T²-Bench Telecom

Conversational AI agents in dual-control scenarios

94.2%

Better than 92% of models compared

AA-LCR

Long context reasoning evaluation

73.3%

Better than 87% of models compared

Coding

SciCode

Python programming for scientific computing

39.8%

Better than 69% of models compared

Terminal-Bench Hard

Agentic coding and terminal use

34.8%

Better than 80% of models compared

Last updated Aug 18, 2026

Artificial Analysis

Providers

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