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JSon-AI/Qwen3.8-Flash-Next-Basalt-Uncensored

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  • classification m-uncensored
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Abliteration classifier · v1.0.0
M-U
Primary method

Uncensored (method unknown)

No other method signals detected in this model.
Confidence
LOW
Why this label 3 signals
Weak or ambiguous signals. Best guess based on catalog patterns; treat as tentative and check the evidence below.
  • 'uncensored' in name/tags but no 'abliterated' marker
  • method not identifiable from author declaration alone
  • may be DPO fine-tune, prompt engineering, or unknown technique
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Model age
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created 2026-10-15

Metadata

License
other
Tags
basalt moe qwen quantized uncensored speculative-decoding text-generation license:other region:us

Related

Total size
0 B
Files
4
Quantizations
1
Registered
2026-10-15 17:59
Last updated on HF
2026-10-15 17:42

Files by quantization

Auxiliary files 4 files 114 GB
Qwen3.8-FN-Uncensored-Q4_K_M-v2.basalt 114 GB 77f70379 download
README.md 3.75 KB ba7fa644 download
.gitattributes 1.56 KB ef7a173e download
SHA256SUMS 105 B ac17dc0c download

README current version from Hugging Face


license: other
license_name: qwen-community-license-1.0
library_name: basalt
pipeline_tag: text-generation
tags:

  • moe
  • qwen
  • basalt
  • quantized
  • uncensored
  • speculative-decoding

Qwen3.8-FN-Uncensored-Q4_K_M — Basalt pack

A ready-to-run .basalt pack for the Basalt inference engine
(a fork of Strata, MIT). This is an uncensored Q4_K_M build of
Qwen3.8-Flash-Next (125B-class mixture-of-experts, qwen4exp architecture), converted from GGUF and
rebuilt with tuned speculative-decoding assets.

File

File Qwen3.8-FN-Uncensored-Q4_K_M-v2.basalt
Size 122,465,146,884 bytes (114.06 GiB)
Format .basalt version 1
SHA-256 77f703791effaa051c01f0a2c6af4eadde291f59250c807f5417bfeed08ce6ee

What is inside

  • Experts: Q4_K_M, 48 layers, 512 routed experts per layer (24,576 expert slots in the routing profile).
  • Output head: Q6_K (output.weight, 2,560 × 248,320).
  • MTP / speculative decoding: mtp/dense marked tuning = self_distilled, mtp/draft_vocab = true,
    draft expert_format = q2_0. The draft head and draft vocabulary are the tuned ones, not the published defaults.
  • Vision: vision/mmproj (907,543,296 bytes) plus vision/text_vocab, so image input works when the
    engine runs with --vision.
  • Tokenizer: a full Qwen tokenizer directory and chat template are embedded in the pack; no external files are needed.
  • Sections: tokenizer/*, dense, dense.index, experts, experts.layout, mtp/{dense,index,experts,draft_vocab},
    profile, vision/*, gguf, meta.

Provenance

Converted with Basalt's tools/convert/convert.py (git 2ef470c) from:

Source file Bytes
Qwen3.8-Flash-Next-Uncensored-Q4_K_M-00001-of-00003.gguf 44,598,509,600
Qwen3.8-Flash-Next-Uncensored-Q4_K_M-00002-of-00003.gguf 44,693,535,520
Qwen3.8-Flash-Next-Uncensored-Q4_K_M-00003-of-00003.gguf 29,858,677,824
mmproj-Qwen3.8-Flash-Next-Uncensored-F16.gguf 907,543,296

Each source's fingerprint (sha256 of the first and last 64 MiB plus the file size) is recorded verbatim in the
pack's meta section. The pack also carries the Qwen Community License 1.0 text and the model's own sampling
defaults: temperature 1.0, top_p 0.95, top_k 20.

Running it

Requirements: an NVIDIA Blackwell GPU (compute capability 12.0) and CUDA 13, plus enough system RAM for the
experts that do not fit in VRAM. Upstream targets Linux; a native Windows port exists in this fork's sibling
work. Use an engine build that has the Q4_K MMQ tiles (upstream 0e1f926 or later).

Flags this pack was measured with:

--max-context 524288 --kv int8 \
--rope-scaling yarn --rope-scale 2 --yarn-orig-ctx 262144 \
--spec 7 --spec-min-p 0.5 \
--expert-cache auto --prefill auto --resident-experts --vram-reserve-mib 700 \
--ple-io ram --kv-resident 32768 --vision dynamic

--mtp-max-t should stay unset: a nonzero value disables the suffix drafter.

Development A/B on one RTX 5090 (575 W power limit): ~220 tok/s decode at a 512k context window,
~5,900 tok/s prefill. Numbers are labelled with their power limit and are development measurements,
not headline figures.

License and attribution

The pack records the Qwen Community License 1.0 as its license; the license text is embedded in the
.basalt file itself. The engine is Basalt, a fork of
Strata (MIT). This repository is an independent conversion of
third-party uncensored weights — check the upstream model's terms before redistributing or deploying it
commercially.

This repository is currently private and under test.

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