dylanneve1/Qwen3.5-0.8B_int4_sym_group-1_dyn_stateful
06
Qwen3.5-0.8B — INT4 Symmetric Channel-wise (OpenVINO)
OpenVINO stateful model exported from Qwen/Qwen3.5-0.8B with INT4 symmetric channel-wise weight compression.
Model Details
Architecture
Qwen3.5 is a hybrid model with 24 layers: 18 linear-attention (GatedDeltaNet) + 6 full-attention layers in a 3:1 repeating pattern. Linear-attention layers use fixed-size conv and recurrent states (cache_params.past.{conv,ssm}.N).
Conversion
pip install git+https://github.com/rkazants/optimum-intel.git@support_qwen3_5
pip install --pre -U openvino openvino-tokenizers nncf --extra-index-url https://storage.openvinotoolkit.org/simple/wheels/nightly
pip install transformers==5.2.0
optimum-cli export openvino \
--model Qwen/Qwen3.5-0.8B \
--weight-format int4 \
--group-size -1 \
--sym \
Qwen3.5-0.8B_int4_sym_group-1_dyn_stateful