Qwen 3.5's open-source 397B MoE model (17B active params) with hybrid linear attention. 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)
2.1K 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
32.7
Reasoning
GPQA Diamond
Graduate-level scientific reasoning
86.1%
Better than 84% of models compared
HLE
Humanity's Last Exam
19.8%
Better than 75% of models compared
IFBench
Instruction-following benchmark
51.6%
Better than 61% of models compared
T²-Bench Telecom
Conversational AI agents in dual-control scenarios
83.9%
Better than 75% of models compared
AA-LCR
Long context reasoning evaluation
62.0%
Better than 65% of models compared
CritPt
Research-level physics reasoning
0.9%
Coding
SciCode
Python programming for scientific computing
41.1%
Better than 75% of models compared
Terminal-Bench Hard
Agentic coding and terminal use
35.6%
Better than 82% of models compared
Knowledge
AA-Omniscience Accuracy
Proportion of correctly answered questions
24.5%
AA-Omniscience Hallucination Rate
Rate of incorrect answers among non-correct responses
82.7%
Last updated Aug 18, 2026
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