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lordx64/Qwen3.6-35B-A3B-Claude-4.7-Opus-Reasoning-Distilled for
use with llama.cpp and
LM Studio.<think>...</think> blocks before producing the final answer.| File | Quant | Approx size | Use case |
|---|---|---|---|
*.IQ4_XS.gguf | IQ4_XS | ~18 GB | Smallest quant with good quality — default pick for LM Studio |
*.Q4_K_M.gguf | Q4_K_M | ~21 GB | Balanced quality / size |
*.Q5_K_M.gguf | Q5_K_M | ~25 GB | Higher quality |
*.Q8_0.gguf | Q8_0 | ~35 GB | Near-lossless |
1llama-server \
2 -m Qwen3.6-35B-A3B-Claude-4.7-Opus-Reasoning-Distilled.IQ4_XS.gguf \
3 --host 127.0.0.1 --port 18081 \
4 -c 32768 -fa on \
5 --cache-type-k q8_0 --cache-type-v turbo4lordx64/Qwen3.6-35B-A3B-Claude-4.7-Opus-Reasoning-Distilled-IQ4_XS-GGUF inside LM Studio's model browser and pick the quant
that fits your RAM/VRAM. The model should appear automatically once HF indexes
this repo.lordx64/Qwen3.6-35B-A3B-Claude-4.7-Opus-Reasoning-Distilled for training details,
evaluations, and intended use.