license: apache-2.0
base_model:
- Qwen/Qwen3.6-35B-A3B
tags: - gguf
- llama.cpp
- mtp
- speculative-decoding
- qwen3
- moe
- not-for-all-audiences
language: - en
- zh
pipeline_tag: text-generation
Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive — MTP-grafted GGUF
⚠️ Not-for-all-audiences. This is an uncensored fine-tune of Qwen3 with reduced
refusal behaviour. Use responsibly and in accordance with applicable law and the
upstream licenses. The maintainers of the source models are not responsible for outputs.
A Q6_K GGUF of the Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive model, with a
Multi-Token-Prediction (MTP / nextn) head grafted on so that llama.cpp'sdraft-mtp speculative decoding can be exercised.
What this is
The original Uncensored Q6_K_P GGUF shipped without the MTP head (the nextn
tensors were dropped during quantization). This file restores a single MTP layer by
transplanting blk.40 (20 tensors, including nextn.eh_proj / enorm / hnorm / shared_head_norm) from a matching Qwen3.6-35B-A3B GGUF that retained it, and setsblock_count = 41, nextn_predict_layers = 1.
- Architecture:
qwen35moe(35B total, ~3B active, 256 experts / 8 used) - Quant: Q6_K (MTP
eh_projis Q8_0, norms F32) - The transplant is byte-exact — no requantization of the base weights.
Performance — MTP gives ~+27% generation speedup
Measured with llama-bench on an Apple M3 Max (Metal), tg128, real prompt:
| Setting | Throughput | Draft acceptance | Mean accepted len |
|---|---|---|---|
| Baseline (no speculation) | 65.6 t/s | — | — |
draft-mtp n_max=1 |
83.6 t/s | 90.2% | 1.90 tok/step |
draft-mtp n_max=2 |
83.7 t/s | 83.8% | 2.68 tok/step |
draft-mtp n_max=3 |
80.8 t/s | 76.5% | 3.29 tok/step |
draft-mtp n_max=4 |
81.7 t/s | 75.2% | 4.01 tok/step |
The grafted MTP head reaches ~90% acceptance despite the backbone being an
uncensored fine-tune — i.e. the fine-tune diverges little from the base the MTP head was
trained on. Best operating point: --spec-draft-n-max 1 or 2, for roughly a +27%
generation throughput gain over plain autoregressive decoding.
Note: acceptance rate is highly sensitive to having a real prompt/context. With an
empty prompt the draft head has nothing to condition on and acceptance collapses (~31%);
always benchmark with representative input.
Usage
# Plain generation
llama-cli -m Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive-Q6_K_P-MTP.gguf -ngl 99 -c 8192
# MTP speculative decoding (requires a llama.cpp build with draft-mtp support)
llama-bench -m <file>.gguf -ngl 99 -n 64 --spec-type draft-mtp --spec-draft-n-max 2
Provenance & licenses
- Backbone: Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive (uncensored fine-tune of Qwen3).
- MTP layer: transplanted from a Qwen3.6-35B-A3B GGUF that retained the
nextnhead. - Both derive from Qwen3 (Apache-2.0). Please honor the original Qwen license and the
respective fine-tuners'/quantizers' terms. If you are a rights holder and want
attribution corrected or content removed, open a discussion on this repo.