Qwen 3.5's open-source 397B MoE model (17B active params) with hybrid linear attention and extended reasoning. Supports text, image, and video input with a 256K context window.
Added Feb 16, 2026
Model weightsContext Window
258.0K
Max Output
65.5K
Avg output tokens (7d)
3.5K tokens
Input Price (Auto)
$0.39/1M
Output Price (Auto)
$2.34/1M
Cache Read (Auto)
$0.20/1M
Capabilities
Benchmarks
Benchmarks
Performance metrics and benchmarks
Sourced from Artificial Analysis.
Intelligence Index
26.1
Coding Index
48.2
Agentic Index
10.6
Reasoning
GPQA Diamond
Graduate-level scientific reasoning
89.3%
Better than 87% of models compared
HLE
Humanity's Last Exam
29.0%
Better than 81% of models compared
IFBench
Instruction-following benchmark
78.8%
Better than 97% of models compared
T²-Bench Telecom
Conversational AI agents in dual-control scenarios
95.6%
Better than 95% of models compared
AA-LCR
Long context reasoning evaluation
77.3%
Better than 82% of models compared
GDPval-AA
Economically valuable tasks
20.4%
CritPt
Research-level physics reasoning
1.7%
Coding
Terminal-Bench Hard
Agentic coding and terminal use
40.9%
Better than 87% of models compared
Knowledge
AA-Omniscience Accuracy
Proportion of correctly answered questions
30.8%
AA-Omniscience Hallucination Rate
Rate of incorrect answers among non-correct responses
88.9%
Last updated Sep 7, 2026
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