Qwen3.6 35B A3B Thinking
Qwen3.6 35B A3B is a native vision-language MoE model with hybrid attention. Compared to Qwen3.5 35B A3B, Alibaba reports stronger agentic coding, mathematical and code reasoning, and better spatial understanding (including object localization and detection).
- Reasoning
- Vision
- Video Input
Added Apr 19, 2026
Model weightsPricing
Auto routing · per 1M tokens- Input
- $0.11
- Output
- $0.80
Specifications
- Context window
- 262.1K
- Max output
- 16.4K
- Parameters
- 35B / 3B
- Total / active
- Avg output (7d)
- 1.8K tokens
- Longer than 89% of models
Benchmarks
Benchmarks
Sourced from Artificial Analysis.
Intelligence Index
18.2
Coding Index
41.9
Agentic Index
13.1
Agentic work
AutomationBench-AA
Workflow automation with guardrail penalties
5.2%
Better than 29% of models compared
AA-Briefcase
Agentic knowledge work (Elo)
711 Elo
Better than 29% of models compared
GDPval-AA v2
Economically valuable tasks (Elo)
879 Elo
Better than 40% of models compared
Document reasoning
GDP.pdf
Professional PDF reasoning: all-pass rate
6.6%
Better than 32% of models compared
AA-LCR v1.1
Long context reasoning with updated grading
71.7%
Better than 66% of models compared
Reasoning
HLE
Humanity's Last Exam
22.2%
Better than 71% of models compared
IFBench
Instruction-following benchmark
64.4%
Better than 75% of models compared
CritPt
Research-level physics reasoning
0.3%
Coding
Terminal-Bench v4.0
Practical coding and terminal tasks
0.0%
Better than 16% of models compared
SciCode
Python programming for scientific computing
36.6%
Better than 17% of models compared
Knowledge
AA-Omniscience Accuracy
Proportion of correctly answered questions
18.8%
AA-Omniscience Hallucination Rate
Rate of incorrect answers among non-correct responses
50.5%
Legacy benchmarks
GPQA Diamond (legacy)
Graduate-level scientific reasoning
84.1%
Better than 75% of models compared
Terminal-Bench Hard (legacy)
Agentic coding and terminal use
34.8%
Better than 80% of models compared
T²-Bench Telecom (legacy)
Conversational AI agents in dual-control scenarios
95.3%
Better than 94% of models compared
AA-LCR (unversioned / legacy)
Long context reasoning evaluation
71.7%
Better than 66% of models compared
GDPval-AA (unversioned / legacy)
Economically valuable tasks
19.0%
Last updated Oct 1, 2026
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