The
full-precision BF16 abliterated
(refusal-removed) build of
Qwen/Qwen3.8-Flash-Next
— a ~180B
Mixture-of-Experts
(125B params / ~6B active), hybrid-attention, native
vision-language
model with flexible thinking, tool-calling, and an MTP head. These are the
source weights
from which the quantized releases are derived, and the recommended base for
further fine-tuning / post-training and quantization
— the full vision tower and MTP head are preserved.
This model has had its
safety alignment substantially removed
via
abliteration
(orthogonalizing the
refusal direction out of the residual stream). As a direct consequence:
It will comply with harmful, unethical, offensive, or illegal requests
that the original
Qwen3.8-Flash-Next
would refuse. It has no meaningful built-in guardrails.
It is released
strictly for legitimate research
— interpretability, AI-safety and refusal-mechanism
study, red-teaming, robustness evaluation, and controlled experiments.
You assume full responsibility and liability
for how you use it and for everything it generates. Do
not deploy it to end users or in production without adding your own safety, moderation, and
abuse-prevention layers.
Use must comply with the
Apache 2.0 License
inherited
from the base model, and all laws and regulations that apply to you.
The authors and uploaders
accept no liability
for any misuse or harm. Its outputs do
not
reflect
the views of the uploaders or of Qwen / Alibaba.
By downloading or using this model you acknowledge and accept the above.
Refusal-direction removal following
Arditi et al. (2024)
,
Refusal in Language Models Is Mediated by a
Single Direction
. A single refusal direction
r
(k = 1) is estimated from the
block-input residual
stream
(the 2560-d Hyper-Connections GR-Read output, where the refusal direction is linearly separable —
the widened 4-branch
output_hidden_states
smears it) as the massive-activation-masked mean-difference of
harmful − harmless activations, selected at
layer 24
by a full 9-layer quality sweep
(
harmful 0.00 / KL 0.085
).
r
is then orthogonalized out of every
residual-writing
matrix —
W' = W − r(rᵀW)
— computed in float32:
mlp.experts.down_proj
(fused 3D, all 512 experts × 49 layers)
49
mlp.shared_expert.down_proj
49
ple.value_proj
+
embed_tokens
(row space)
2
Total residual-writer tensors
149
Preserved (never touched):
the full
vision + video tower
(333
visual.*
tensors), the MoE
router
(
mlp.gate
), the fused
experts.gate_up_proj
reader, all
Hyper-Connection mixers
, the
QSA sparse-attention indexer
, the
n-gram embedding table
,
mtp.fc_*
, norms, and
lm_head
. The MTP
head's residual writers are abliterated consistently so speculative decoding keeps working. Max residual
leakage after the edit:
0.0755
(float32 projection → bf16 storage).
This is a
surgical weight edit
— it changes ~0 general capability (see Evaluation) while collapsing
refusal behaviour.
Fine-tuning & post-training
This BF16 checkpoint is the
recommended base for post-training
— full precision, whole VL tower + MTP
head, a drop-in for
Qwen/Qwen3.8-Flash-Next
in the
transformers
/
Qwen4ExpForConditionalGeneration
stack (needs
transformers 5.16+
).
SFT / DPO / RL work as on the base model (full-FT or LoRA/QLoRA).
Re-quantization:
quantize from these weights to FP8 / MLX / etc. (this is exactly how the derived
releases were produced).
Note:
abliteration is a
weight edit
, not data-level unlearning. Fine-tuning on refusal-heavy /
safety data can partially re-introduce refusals; neutral / task data preserves the uncensored behaviour.
Intended use
Research into refusal mechanisms, alignment, and interpretability.
Red-teaming and safety / robustness evaluation in controlled environments.
A full-precision base for further fine-tuning, post-training, and quantization.
Evaluation
Measured on
these exact weights
served with
vLLM
(day-0
qwen4_exp
image), against the official
Qwen/Qwen3.8-Flash-Next
served identically with the same scripts and settings. Full BF16. Refusal is judged by a rule-based opening-phrase classifier (
caveat
= answered but wrapped in a disclaimer) — indicative, not an LLM-judge / publication-grade number.
Thinking is off unless stated.
Safety — harmful-prompt refusal,
thinking OFF
(lower = more uncensored)
Benchmark
n
Base
This model
Caveat (this)
AdvBench
100
100.0%
2.0%
53.0%
JailbreakBench (harmful)
100
94.0%
0.0%
52.0%
StrongREJECT
150
99.3%
1.3%
62.0%
HarmBench (standard)
150
100.0%
1.3%
50.7%
MaliciousInstruct
100
98.0%
0.0%
55.0%
SimpleSafetyTests
50
64.0%
2.0%
68.0%
ForbiddenQuestions
150
75.3%
3.3%
57.3%
Custom probes (zh/en)
11
63.6%
0.0%
36.4%
Safety — harmful-prompt refusal,
thinking ON
(
enable_thinking=true
, max 3072)
Capability retention — vs the official base (same scripts, same settings)
Benchmark
n
Base
This model
Δ
MMLU (0-shot letter)
300
90.0%
87.7%
-2.3
MMLU-Pro (CoT)
400
77.8%
76.2%
-1.5
GSM8K (CoT)
150
92.0%
93.3%
+1.3
CMMLU (0-shot, Chinese)
500
81.8%
81.6%
-0.2
Verified working
on this build: tool-calling ✅, vision/OCR ✅ 6/6, reasoning ✅. The
vision + video tower is preserved byte-for-byte
(333
visual.*
tensors in BF16), so it remains a full vision-language model — a drop-in for the base.
Usage — self-host with vLLM (OpenAI-compatible)
qwen4_exp
needs the day-0 vLLM image and
transformers 5.16+
.
--enable-expert-parallel
is
required for the FP8 build
(MoE intermediate 640 ÷ TP is not divisible by the FP8 block 128 without it); it is harmless for BF16. Tool calls use the
Qwen3-Coder XML
format (
--tool-call-parser qwen3_coder
). Toggle reasoning per
request with
chat_template_kwargs={"enable_thinking": true|false}
; pass
image_url
content parts for
vision.
Bias, risks, and limitations
Safety guardrails removed
— the model will produce harmful, biased, or offensive content on request
(see the disclaimer).
It inherits any biases and limitations of the base
Qwen3.8-Flash-Next
.
The reported refusal metric is a rule-based heuristic; evaluate rigorously for your own use case.
License
Apache 2.0
, inherited from the base model
Qwen/Qwen3.8-Flash-Next
. Abliteration does not change
the underlying license obligations.
Runs of orcarouter Qwen3.8-Flash-Next-Uncensored on huggingface.co
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