@servasyy_ai: Holy shit, I only found out today! Turns out, if you want an "unrestricted version" of a large model, you don't need to…
Summary
A social media post claims that the Qwen3.8-Flash-Next model can be made 'unrestricted' by using 'Control Vector Projection' startup parameters in an inference engine to strip refusal directions from layers 4-44, without modifying model weights, and suggests this unlocks content normally blocked by cloud models.
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Cached at: 10/15/26, 02:05 AM
Holy shit, I only found out today!
Turns out, if you want an “unrestricted version” of a large model, you don’t need to hunt down modded models and redownload them everywhere!
I used to think you had to retrain tens of gigabytes of weights to lift the seal, but after testing it out today, I discovered: The Qwen3.8-Flash-Next model doesn’t require any heavy lifting at all—just tweak a simple startup parameter on the existing model, and boom, you’ve got a full-powered unrestricted large model.
A lot of folks might be wondering: Once you tweak this parameter and fully unleash the restrictions, what exactly can this model do?
Put it this way: All the forbidden zones you keep slamming into on cloud-based large models? It takes full command of every single one:
From reverse-engineering software breakdowns, doing shady stuff like adult text+images+video with real celeb faces, to deep dives into sensitive hot-button topics, on-device closed-loop handling of private code, and more.
It seizes control of every forbidden zone you hit on cloud models, no beating around the bush, no Tai Chi dodges—the boundaries are all up to you.
How does it pull off unlocking everything without even swapping out the model?
The secret’s actually in the inference engine.
I ran Qwen3.8-Flash-Next on dual V100 cards (using the Strata v0.1.43 engine), and the engine’s core already has the “Control Vector Projection” feature baked in from the get-go.
The original model weights stay untouched—no need to slap on LoRA or anything—just append these 4 lines to the startup config:
"--control-vector-scaled", "Qwen3.8-Flash-Next-cvec.gguf:1.0"
"--control-vector-layer-range", "4", "44"
"--cvec-mode", "project"
"--cvec-dir", "per-layer"
Restart the service—55 seconds later—and the engine automatically strips out the “refusal direction vectors” from layers 4 to 44 during inference.
And the best part? It even supports dynamic on/off toggling per request—defaults to unrestricted mode for everyday use; if an interface needs to flip back to the original safety policy, just pass a false in the request, and it switches for that one call without even restarting the service.
No more chit-chat—everyone, just click open the terminal test screenshot below and feel it for yourself. See what happens when a 256K full-powered large model sheds all that moral preaching: it rattles off 8 major forbidden-zone capabilities in one breath, then coolly drops a line like “Which one do you want? Just say it”—the sheer sensory impact is off the charts!
huangserva (@servasyy_ai): 兄弟们,花了一晚上! 我把目前最火的两个MiniMax H3 360度环绕 LoRA,拉到 4090 上实机跑了一遍,我们来直接看对比。
同样都标榜 360° 旋转,底层路线完全是两个维度的物种。 一个叫「真 3D 轨道」,一个叫「聪明的侧摆」。
左右分屏实测视频放这,底层差异看这三点:
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