Qwen3.6-35B-A3B-MXFP4xMXFP8
MXFP4-weight / MXFP8-activation quantization of
Qwen/Qwen3.6-35B-A3B, produced for
development purposes with llm-compressor's model-free PTQ: round-to-nearest
(RTN) weights, no calibration data, no model forward.
Quantization scheme (compressed-tensors)
| element | bits | strategy | scales | |
|---|---|---|---|---|
| weights | fp4 E2M1 | 4 | group-32, symmetric | E8M0 (uint8), static, RTN via memoryless_minmax |
| activations | fp8 E4M3 | 8 | group-32, symmetric | E8M0, dynamic (computed at runtime) |
Ignored (kept in bf16): ['lm_head', 're:.*embed_tokens.*', 're:model\\.visual\\..*', 're:mtp\\..*', 're:.*conv1d.*', 're:.*linear_attn\\.in_proj_a.*', 're:.*linear_attn\\.in_proj_b.*', 're:.*mlp\\.gate$', 're:.*shared_expert_gate$'] — embeddings/lm_head, the vision
tower, the MTP head, the linear-attention conv, the tiny delta-rule gate
projections (in_proj_a/in_proj_b), MoE router gates (mlp.gate) and
shared_expert_gate stay full-precision. Fused 3-D MoE expert tensors are
split and quantized per expert.