Qwen3.6 27B
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.
- Vision
- Video Input
Added Apr 23, 2026
Model weightsPricing
Auto routing · per 1M tokens- Input
- $0.20
- Output
- $2.24
Specifications
- Context window
- 262.1K
- Max output
- 65.5K
- Parameters
- 27B
- Avg output (7d)
- 268 tokens
- Longer than 20% of models
Benchmarks
Benchmarks
Sourced from Artificial Analysis.
Intelligence Index
19.8
Coding Index
46.6
Agentic work
T²-Bench Telecom (legacy)
Legacy fallback · Conversational AI agents in dual-control scenarios
93.6%
Better than 90% of models compared
GDPval-AA v2
Economically valuable tasks (Elo)
966 Elo
Better than 43% of models compared
Document reasoning
AA-LCR v1.1
Long context reasoning with updated grading
66.7%
Better than 58% of models compared
Reasoning
HLE
Humanity's Last Exam
15.1%
Better than 61% of models compared
IFBench
Instruction-following benchmark
45.7%
Better than 53% of models compared
Coding
Terminal-Bench Hard (legacy)
Legacy fallback · Agentic coding and terminal use
21.2%
Better than 61% of models compared
Legacy benchmarks
GPQA Diamond (legacy)
Graduate-level scientific reasoning
82.9%
Better than 72% of models compared
AA-LCR (unversioned / legacy)
Long context reasoning evaluation
66.7%
Better than 57% of models compared
Last updated Oct 14, 2026
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