---

license: apache-2.0

base_model: OpenMOSE/Qwen3.5-REAP-212B-A17B

library_name: gguf

pipeline_tag: text-generation

tags:

• gguf
• abliterated
• uncensored
• imatrix
• moe
• reap
• qwen3.5
• not-for-all-audiences

---

Qwen3.5-REAP-212B-A17B - Abliterated GGUF

Abliterated, importance-matrix (imatrix) quantized GGUFs of

OpenMOSE/Qwen3.5-REAP-212B-A17B —

itself a 48% REAP expert-pruning of Qwen3.5-397B-A17B down to

212B total / ~17B active.

Provenance chain: the abliterated bf16 safetensors base was converted to a Q8_0 master

(near-lossless), and every rung here is cut from that master. The bf16 base lives at

RobinsonLabs/Qwen3.5-REAP-212B-A17B-abliterated —

use that repo if you want to re-abliterate, merge a LoRA, fine-tune, or roll your own quants.

Disclosure

This model is abliterated — the hard-refusal reflex on adult / creative content has been

reduced via single-direction weight orthogonalization. Harm guardrails are retained by design:

self-harm prompts still redirect to help (e.g. 988), and it is not intended to assist genuine

wrongdoing. Capability is preserved. Tagged not-for-all-audiences. Use responsibly — you are

responsible for what you generate with it. License inherited from the base model: Apache-2.0.

Files

| File | Quant | bpw | ~Size | Notes |

|---|---|---|---|---|

| ...-Q5_K_M.gguf | Q5_K_M | 5.68 | ~150 GB | highest-fidelity rung published |

| ...-Q4_K_M.gguf | Q4_K_M | 4.85 | ~128 GB | K-quant quality pick |

| ...-IQ4_XS.gguf | IQ4_XS | 4.27 | ~113 GB | quality/size sweet spot |

| ...-IQ3_M.gguf | IQ3_M | 3.51 | ~93 GB | |

| ...-IQ3_XS.gguf | IQ3_XS | 3.29 | ~87 GB | |

| ...-IQ2_M.gguf | IQ2_M | 2.63 | ~70 GB | |

| ...-fit1m-imat.gguf | fit1m (mix) | 2.55 | ~67 GB | cluster-fit attention-priority mix — attn/router/shared-expert/embed kept high, routed experts low; punches above its bpw |

| ...-IQ2_XS.gguf | IQ2_XS | 2.36 | ~63 GB | |

| ...-IQ2_XXS.gguf | IQ2_XXS | 2.13 | ~56 GB | smallest |

All quants are imatrix-weighted (corpus-rldomain, computed on the source model).

!Quant ladder — bits-per-weight vs file size

The chart shows the contested 2–5 bpw band; the higher-fidelity Q5_K_M rung is in the table above.

Architecture notes

qwen35moe hybrid: 60 decoder layers (45 linear-attn / DeltaNet + 15 full-attn,

full_attention_interval=4), 267 experts, MoE, hidden size 4096. The REAP convert's phantom MTP

layer is corrected (block_count 61→60, nextn_predict_layers 1→0) so the model loads as a clean

60-layer decoder. This is the text path only (no vision mmproj).

Method

• Abliteration — single-direction weight orthogonalization (FailSpy / Labonne method): for every

matrix that writes the residual stream (o_proj, DeltaNet out_proj, fused expert down_proj,

shared-expert down_proj, and the token embedding), the rank-1 component along the refusal

direction is subtracted. 181 tensors edited; routers, MTP block, and norms pass through

byte-identical.

• Refusal direction — massive-activation guarded. The direction is captured with a

mean-difference control vector, then guarded against attention-sink contamination: the sink

dimensions that dominate raw activation magnitude (and would brick the model if ablated) are

detected across layers and excluded, and the direction is taken from the clean, spread-out

consensus of the late layers rather than a single sink-dominated layer.

• Quant — importance-matrix (imatrix) weighted convert + quantize with

llama.cpp.

bf16 base

The full-precision bf16 safetensors master this ladder derives from is at

RobinsonLabs/Qwen3.5-REAP-212B-A17B-abliterated.

That repo is the master for further surgery (re-abliteration, LoRA merge, fine-tune) and for making

your own quants.

Provenance

Qwen3.5-397B-A17B (Apache-2.0) → OpenMOSE/Qwen3.5-REAP-212B-A17B (48% REAP prune) →

abliterated (bf16 master) → Q8_0 master → imatrix quants. Recipe and diagnosis are Robinson

Labs internal (WI #1423, KB #213 "abliteration massive-activation brick").