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
Avg output tokens (7d)
807 tokens
Input Price (Auto)
$0.27/1M
Output Price (Auto)
$2.16/1M
Cache Read (Auto)
$0.14/1M
Capabilities
Benchmarks
Benchmarks
Performance metrics and benchmarks
Sourced from Artificial Analysis.
Intelligence Index
19.4
Agentic work
T²-Bench Telecom (legacy)
Legacy fallback · Conversational AI agents in dual-control scenarios
87.1%
Better than 81% of models compared
Document reasoning
AA-LCR v1.1
Long context reasoning with updated grading
64.0%
Better than 58% of models compared
Reasoning
HLE
Humanity's Last Exam
13.9%
Better than 64% of models compared
IFBench
Instruction-following benchmark
46.9%
Better than 55% of models compared
CritPt
Research-level physics reasoning
0.3%
Coding
Terminal-Bench Hard (legacy)
Legacy fallback · Agentic coding and terminal use
31.8%
Better than 75% 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%
Legacy benchmarks
GPQA Diamond (legacy)
Graduate-level scientific reasoning
84.2%
Better than 75% of models compared
AA-LCR (unversioned / legacy)
Long context reasoning evaluation
64.0%
Better than 58% of models compared
Last updated Sep 11, 2026
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