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EXL3 · 4.0 bpw · 19.5 GB · Mixture‑of‑Experts · 48 layers × 256 experts[!NOTE] An ExLlamaV3 build oflordx64/Qwen3.6-35B-A3B-Claude-4.7-Opus-Reasoning-Distilledat 4.0 bits per weight — the tight‑fit build, sized to leave generous context room on a 24 GB consumer GPU and to load on 16 GB cards at workable context lengths. See Quants for sibling repos at other bit‑widths or browse the collection.
| 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. |
[!TIP] VRAM at 4.0 bpw: weights on disk + ~2 GB context overhead. Comfortable on a single 24 GB card with room for ~24k tokens of context; fits a 16 GB card with a ~4–6k token window.
1pip install -U huggingface_hub
2
3hf download \
4 blockblockblock/Qwen3.6-35B-A3B-Claude-4.7-Opus-Reasoning-Distilled-exl3-4.0bpw \
5 --local-dir ./Qwen3.6-35B-A3B-Claude-4.7-Opus-Reasoning-Distilled-exl3-4.0bpwquantization_config.json)| Setting | Value |
|---|---|
| Format | EXL3 |
| Bits per weight | 4.0 |
| Head bits | 8 |
| Calibration rows | 128 |
| Codebook | MCG |
| Out‑scales | always |
| Parallel mode | enabled (MoE expert batching) |
[!IMPORTANT] Use and license follow the base model. Quantization adds no additional restrictions. Refer to the upstream repository for terms, citation, and safety documentation.
{org}/{model}-exl3-{bpw}bpw