Qwen3.5 27B
Qwen3.5 27B is a native vision-language dense model optimized for fast responses while balancing quality and inference speed.
- Vision
- Video Input
Added Feb 24, 2026
Model weightsPricing
Auto routing · per 1M tokens- Input
- $0.25
- Output
- $2.00
Specifications
- Context window
- 260.1K
- Max output
- 65.5K
- Parameters
- 27B
- Avg output (7d)
- 730 tokens
- Longer than 61% of models
Benchmarks
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 55% of models compared
Reasoning
HLE
Humanity's Last Exam
13.9%
Better than 59% 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 54% of models compared
Last updated Oct 14, 2026
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