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
Avg output tokens (7d)
2.6K tokens
Input Price (Auto)
$0.30/1M
Output Price (Auto)
$2.00/1M
Cache Read (Auto)
$0.030/1M
Capabilities
Benchmarks
Benchmarks
Performance metrics and benchmarks
Sourced from Artificial Analysis.
Intelligence Index
37.7
Coding Index
53.7
Agentic Index
27.5
Reasoning
GPQA Diamond
Graduate-level scientific reasoning
84.2%
Better than 79% 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 16, 2026
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