Qwen3.5 27B is a native vision-language dense model optimized for fast responses while balancing quality and inference speed.
Added Feb 24, 2026
Model weightsContext Window
260.1K
Max Output
65.5K
Input Price (Auto)
$0.28/1M
Output Price (Auto)
$2.27/1M
Cache Read (Auto)
$0.14/1M
Capabilities
Benchmarks
Benchmarks
Performance metrics and benchmarks
Sourced from Artificial Analysis.
Reasoning
GPQA Diamond
Graduate-level scientific reasoning
84.2%
Better than 85% of models compared
HLE
Humanity's Last Exam
13.9%
Better than 76% of models compared
IFBench
Instruction-following benchmark
46.9%
Better than 56% of models compared
T²-Bench Telecom
Conversational AI agents in dual-control scenarios
87.1%
Better than 80% of models compared
AA-LCR
Long context reasoning evaluation
61.0%
Better than 77% of models compared
CritPt
Research-level physics reasoning
0.3%
Coding
SciCode
Python programming for scientific computing
36.7%
Better than 64% of models compared
Terminal-Bench Hard
Agentic coding and terminal use
31.8%
Better than 76% of models compared
Knowledge
AA-Omniscience Accuracy
Proportion of correctly answered questions
15.7%
AA-Omniscience Hallucination Rate
Rate of incorrect answers among non-correct responses
75.1%
Last updated Aug 7, 2026, 12:00 AM
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