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⚠️ 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.
nextn) head grafted on so that llama.cpp's
draft-mtp speculative decoding can be exercised.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.qwen35moe (35B total, ~3B active, 256 experts / 8 used)eh_proj is Q8_0, norms F32)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 |
--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.
1# Plain generation
2llama-cli -m Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive-Q6_K_P-MTP.gguf -ngl 99 -c 8192
3
4# MTP speculative decoding (requires a llama.cpp build with draft-mtp support)
5llama-bench -m <file>.gguf -ngl 99 -n 64 --spec-type draft-mtp --spec-draft-n-max 2nextn head.