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 weightsContext Window
260.1K
Max Output
65.5K
Input Price (Auto)
$0.20/1M
Output Price (Auto)
$1.56/1M
Cache Read (Auto)
$0.098/1M
Capabilities
Benchmarks
Benchmarks
Performance metrics and benchmarks
Sourced from Artificial Analysis.
Intelligence Index
31.3
Coding Index
46.6
Reasoning
GPQA Diamond
Graduate-level scientific reasoning
82.9%
Better than 75% of models compared
HLE
Humanity's Last Exam
15.1%
Better than 69% of models compared
IFBench
Instruction-following benchmark
45.7%
Better than 53% of models compared
T²-Bench Telecom
Conversational AI agents in dual-control scenarios
93.6%
Better than 90% of models compared
AA-LCR
Long context reasoning evaluation
64.3%
Better than 68% of models compared
Coding
SciCode
Python programming for scientific computing
37.3%
Better than 60% of models compared
Terminal-Bench Hard
Agentic coding and terminal use
21.2%
Better than 61% of models compared
Last updated Aug 18, 2026
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