GGUF build of OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated. See the parent repo for the full pipeline: refusal ablation → constrained-LoRA Opus reasoning SFT → unconstrained chosen-completion SFT → Kimi K2.6 reasoning DPO (≈3,000 distilled samples + synthetic data, improving reasoning verbosity on ~12% of requests and removing looping on 2–6% of long-tail conversations).

This repo ships both the language model and the vision projector (mmproj), so it runs as a full multimodal (image + text) model in llama.cpp / LM Studio.

Files

File	Bits/weight	Size	Notes
`Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-Q4_K_M.gguf`	~4.6	~76 GB	Language model. Q4_K_M keeps `output.weight` at higher precision. MTP head included.
`mmproj-Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-F16.gguf`	F16	~0.9 GB	Vision projector (`qwen3vl_merger`, Qwen3.5 vision tower). Load alongside the model for image input.

Vision (mmproj)

Pass the mmproj file to enable image input. The vision tower is the standard Qwen3.5-122B-A10B Qwen3-VL encoder (carried over unchanged from the base model), F16.

bash

# llama.cpp multimodal CLI
llama-mtmd-cli \
  -m Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-Q4_K_M.gguf \
  --mmproj mmproj-Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-F16.gguf \
  --image path/to/image.jpg \
  -p "Describe this image." -ngl 99

In LM Studio: keep the mmproj-*.gguf in the same folder as the model — it is detected automatically and the image-attachment button becomes available.

MTP (multi-token prediction)

This build keeps the MTP head (blk.48.nextn.*, qwen35moe.nextn_predict_layers). Recent llama.cpp with qwen35moe MTP support (e.g. LM Studio's llama.cpp 2.15.0) can load it and expose "MTP Speculative Decoding" in the advanced load settings.

⚠️ Caveat: in our testing the MTP head gave no measurable performance gain on this checkpoint. It is shipped for completeness and would need to be retrained to be genuinely useful — happy to do so if there is interest in the model. The model runs fine with MTP speculative decoding off.

Usage (text-only)

Requires a recent llama.cpp build that supports the qwen35moe architecture (Gated DeltaNet linear-attn + MoE).

bash

llama-cli -m Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-Q4_K_M.gguf \
  -p "Explain why the sky is blue." -ngl 99 -c 8192

Hardware

Q4_K_M (~76 GB) + mmproj (~0.9 GB) fits on a single 96 GB GPU, an Apple Silicon machine with ≥ 96 GB unified memory, or CPU + RAM. Leave headroom for KV cache / context.

Notes

License: Other (inherits from the Qwen3.5 base license)
Parent (full weights): Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated
Modality: Text + Vision (via mmproj) + MTP head (see caveat)
Architecture: Qwen3 MoE (~10B active / 122B total) + Qwen3-VL vision tower

Disclaimer

Use is the responsibility of the user. Ensure your usage complies with applicable laws, platform rules, and deployment requirements.

Jonyses/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-GGUF

Support & Community

Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated — GGUF

Overview