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).
Added Apr 19, 2026
Model weightsContext Window
262.1K
Max Output
16.4K
Avg output tokens (7d)
2K tokens
Input Price (Auto)
$0.11/1M
Output Price (Auto)
$0.80/1M
Capabilities
Benchmarks
Benchmarks
Performance metrics and 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 30% of models compared
GDPval-AA v2
Economically valuable tasks (Elo)
879 Elo
Better than 43% 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 67% of models compared
Reasoning
HLE
Humanity's Last Exam
22.2%
Better than 72% 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 18% 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 67% of models compared
GDPval-AA (unversioned / legacy)
Economically valuable tasks
19.0%
Last updated Sep 29, 2026
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