Sign up

wang-yang/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive-MTP-GGUF

🤗 Hugging Face sourcetext-generationapache-2.031 GBGGUF✓ HF checksums availableupdated today
No torrent yet →

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's draft-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 sets block_count = 41, nextn_predict_layers = 1.

  • Architecture: qwen35moe (35B total, ~3B active, 256 experts / 8 used)
  • Quant: Q6_K (MTP eh_proj is 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 nextn head.
  • 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.