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Qwen3.8-27B-Uncensored-Heretic-exl3-4.00bpw-h4-vb4

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sjoe1244/Qwen3.8-27B-Uncensored-Heretic-exl3-4.00bpw-h4-vb4 is an uncensored open-source model hosted on Hugging Face.

Image-Text-to-TextsafetensorsLicense: apache-2.027Bexllamav3qwen3_5exl3tabbyapihereticuncensoredabliteratedmtpvisionconversationalquantized4-bit
README.md说明 / 使用方法

license: apache-2.0 license_link: https://huggingface.co/Qwen/Qwen3.8-27B/blob/main/LICENSE base_model: llmfan46/Qwen3.8-27B-Uncensored-Heretic-Native-MTP-Preserved base_model_relation: quantized quantized_by: sjoe1244 pipeline_tag: image-text-to-text library_name: exllamav3 tags:

  • exl3
  • exllamav3
  • tabbyapi
  • qwen3_5
  • heretic
  • uncensored
  • abliterated
  • mtp
  • vision
  • conversational
  • quantized inference: false

Qwen3.8 27B Uncensored Heretic · EXL3 4.00bpw-h4-vb4

An ExLlamaV3 quant of llmfan46/Qwen3.8-27B-Uncensored-Heretic-Native-MTP-Preserved. It is built for the full 262K context, with vision and MTP speculative decoding, on a single 24 GB card. Weights, head, vision tower and MTP head are all 4-bit.

It runs in TabbyAPI or ExLlamaV3 only. It does not run in Transformers, vLLM or llama.cpp.

At a glance (one RTX 4090, 24 GB)

This quant
Download16.1 GB
Contextthe full 262,144 tokens loads with vision and MTP on (4-bit KV cache)
VRAM after load21.0 GB
Writing speed with MTP155–167 tok/s without thinking, 142–144 tok/s with thinking

Quick start (TabbyAPI, 24 GB)

model:
  max_seq_len: 262144
  cache_size: 266240
  cache_mode: 4,4
  chunk_size: 1024
  max_batch_size: 2
  vision: true
  tool_format: auto
  prompt_template:

draft_model:
  draft_mode: mtp
  • Leave prompt_template empty. The model then uses its own chat template.
  • draft_mode: mtp drafts tokens with the model's own MTP head. No second model is needed.

Samplers

These are Qwen's recommended values.

Modetemperaturetop_ptop_k
Thinking1.00.9520
No thinking0.70.820
  • Keep min_p at 0, repetition penalty at 1.0 and DRY off.
  • Turn thinking off with chat_template_kwargs: {"enable_thinking": false}.
  • reasoning_effort defaults to xhigh, which can think for thousands of tokens. Use low or medium for everyday work.

Good to know

  • Made and tested with ExLlamaV3 1.6.0. It was not tried on older versions.
  • Only short tests were run on this quant. The longest prompt was 9K tokens. The full window loads, but it was not filled. For reference, turboderp's Huihui 4.00bpw quant of the same model family (6-bit head, 5-bit vision) peaked at 22.7 GB with a 232K-token prompt on this setup.
  • Quality against the BF16 source was not measured.
  • MTP is where the speed comes from. Without it, that Huihui quant wrote 54 tok/s on this setup. MTP off was not timed on this quant.
  • Vision loads and fits in the numbers above. No image test was run.
  • The "params" count in the Hugging Face sidebar is wrong for EXL3 files. This is the 27B model.

How it was made

SettingValue
MethodEXL3, ExLlamaV3 1.6.0
Weights4.00 bpw
Head (lm_head)4 bits
Vision tower4 bits
MTP head4 bits
EmbeddingsBF16 (unquantized)
Codebookmul1, out_scales auto
Calibration250 rows x 2048 cols (ExLlamaV3 default set)
Sourcellmfan46/Qwen3.8-27B-Uncensored-Heretic-Native-MTP-Preserved, BF16
python convert.py -i <source> -o <out> -w <work> -b 4.0 -hb 4 -vb 4 -mb 4

The source repo has no preprocessor_config.json, and ExLlamaV3 needs it for vision. This repo adds preprocessor_config.json and video_preprocessor_config.json from Qwen/Qwen3.8-27B. Their image settings are the same as in the source's processor_config.json.

FileBytes
model-00001-of-00002.safetensors8,471,336,006
model-00002-of-00002.safetensors7,605,654,924
Total16,076,990,930 (14.97 GiB)

Test run

The setup was TabbyAPI with ExLlamaV3 1.6.0 on one RTX 4090 (24,564 MiB), using the Quick start config above. VRAM is the whole-GPU nvidia-smi reading. Each test ran once.

CheckResult
Load35 s, 21,027 MiB after load
VRAM after all tests21,595 MiB
Short coding tasks, checked by hidden unit tests6 of 6 passed
Tool-call loops (read a file, fix it, write it, run the tests)2 of 2 finished, 4 calls each, no bad arguments
Lookups in 4K and 9K-token prompts (exact function copies, exact tool arguments)9 of 9 passed
Speed without thinking155–167 tok/s
Speed with thinking (reasoning_effort: low)142–144 tok/s
Speed on the 4K and 9K-token prompts173–193 tok/s
MTP drafts accepted81% (6,297 of 7,788 tokens)
  • The first request after loading ran at 48 tok/s.
  • One long-program test hit its 3,000-token output limit before finishing. It is not counted above.

Credit and license

Apache 2.0, the same as Qwen/Qwen3.8-27B and the source model. The uncensoring is llmfan46's work. This repo only adds the EXL3 export.

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来源与版本

作者
sjoe1244
最近更新
2026/10/10
最新创建
2026/10/10
HF 趋势
未知
数据快照
2026/10/10
版本
未知
许可证
apache-2.0