Important

If you downloaded the model before May 9, please re-download the model as some tensors were not in the right order

Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive-bf16

Bf16 safetensors conversion of original GGUF model + mmproj, in exact HuggingFace format matching Qwen/Qwen3.6-35B-A3B. Ready for vLLM speculators (DFlash/EAGLE-3) as a verifier/target model.

Original Model

Creator: HauhauCS
Source: Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive
Architecture: Qwen3_5MoeForConditionalGeneration (multimodal)
Base: Qwen 3.6 35B MoE (256 experts, 8 active, 3B active params)

Conversion

Text model: 733 GGUF Q8_K_P tensors → dequantized to bf16
Vision encoder: 334 GGUF F16 tensors → merged (patch_embd slices combined)
Full tokenizer extracted (248,320 vocab + 247,587 BPE merges + chat template)
1026 HF weights (693 text + 333 vision) across 17 shards, 70.2 GB total
All weight names match reference model exactly (e.g. model.language_model.*, model.visual.*)

Specs

Layers: 40 (30 linear attention/SSM + 10 full attention every 4th)
Hidden: 2048, Heads: 16 Q / 2 KV, Head dim: 256
Linear attention: key/value head dim 128, conv kernel 4
Experts: 256 routed + 1 shared per layer, 8 active
Vision: 27-layer encoder, Qwen3VL merger, patch 16, 768 image size
Vocab: 248,320, Context: 262,144

Conversion

Text model: 733 GGUF Q8_K_P tensors → dequantized to bf16

Vision encoder: 334 GGUF F16 tensors → merged (patch_embd slices combined)

Full tokenizer extracted (248,320 vocab + 247,587 BPE merges + chat template)

1026 HF weights (693 text + 333 vision) across 17 shards, 70.2 GB total

All weight names match reference model exactly (e.g. model.language_model.*, model.visual.*)

Specs

Layers: 40 (30 linear attention/SSM + 10 full attention every 4th)

Hidden: 2048, Heads: 16 Q / 2 KV, Head dim: 256

Linear attention: key/value head dim 128, conv kernel 4

Experts: 256 routed + 1 shared per layer, 8 active

Vision: 27-layer encoder, Qwen3VL merger, patch 16, 768 image size

Vocab: 248,320, Context: 262,144