Huihui · Qwen3.6 · 35B-A3B · abliterated

EXL3  ·  4.5 bpw  ·  21.6 GB  ·  Mixture‑of‑Experts  ·  40 layers × 256 experts


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base model quantized by collection


An ExLlamaV3 build of huihui-ai/Huihui-Qwen3.6-35B-A3B-abliterated at 4.5 bits per weight — quality-leaning build — comfortable on a 24 GB card with usable context (~22 GB weights). See Quants for sibling repos at other bit‑widths or browse the collection.

Quants

BPW     Head bits     Calibration rows     Size     Status
4.0 8 128 19.5 GB link
4.5 8 250 21.6 GB this repo

Inference

Loader Use it for
TabbyAPI OpenAI‑compatible HTTP server. Drop‑in for OpenAI clients.
text‑generation‑webui Local chat UI. Pick the ExLlamaV3 loader from the model dropdown.
ExLlamaV3 Direct Python API for embedding the model in your own code or pipeline.

VRAM at 4.5 bpw: ~21.6 GB weights + ~2 GB context. Comfortable on a single 24 GB card; tight on 16 GB with reduced context.

Download

pip install -U huggingface_hub

hf download \
  blockblockblock/Huihui-Qwen3.6-35B-A3B-abliterated-exl3-4.5bpw \
  --local-dir ./Huihui-Qwen3.6-35B-A3B-abliterated-exl3-4.5bpw
Quantization recipe  (advanced — embedded in quantization_config.json)
Setting Value
Format EXL3
Bits per weight 4.5
Head bits 8
Calibration rows 250
Codebook MCG
Out‑scales always
Parallel mode enabled (MoE expert batching)

Loaded automatically by every ExLlamaV3 loader; reproduced here for searchability.

License & use

Use and license follow the base model. Quantization adds no additional restrictions. Refer to the upstream repository for terms, citation, and safety documentation.


Quantized with BlockQuant  ·  convention {org}/{model}-exl3-{bpw}bpw
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