I didn’t have any luck with some uncensored Qwen 3.5 either. It always reasons about the guardrails. And it leans towards weaseling itself out of the situation. And the 3.5 version goes on for 1500 tokens anyway, just to think about how to respond to “Hello”.

I didn’t do a lot of LLM stuff lately. I’m also looking for a new local model which isn’t censored nor a sycophant, nor overly verbose and repetetive. But I guess I see that with a lot of models. And lots of the supposedly uncensored ones will give you the kids version of a murder mystery story, because they’re still averse to violence, conflict, taboo and all kinds of things.

And a lot of internet recommendations are older models from at least a year ago?! At least I didn’t find any perfect fit (yet).

Abliteration techniques might be more limited with reasoning models. I don’t know if they process simply be rehashing the arguments or if there’s more under the hood that would be harder to alter.

I try new models from time to time, including some of the thinking ones, but I’ve always come back to the NeuralDaredevil model, even though it’s “old”. Your results may differ depending on the subject matter, but I can’t think of an instance where I hit a wall. At most, maybe some sidetracking but once I told it to be more open it didn’t hold back.

I’m not sure what the appeal of the thinking mode is. Perhaps on some things it does better, but in watching its reasoning I’ve seen it talk itself out of a good solution too. Which is what you get with typical models when you push the context too far and don’t start a new session, they wander.

Anybody have recommendations for truly uncensored models?

1. Are you wanting something for ERP (erotic role-play; sexy chatbots)?

2. How much VRAM can you afford to spend on it?

If the answer to (1) is “yes”, then:

If the answer to (2) is “large GPU range”, maybe 16GB+ -ish, then I’d maybe look at Cydonia, based on Mistral Small. I find that this tends to become increasingly nonsensical and repetitive at a conversation grows to a certain (sub-context window) size, but it’s quite popular with users on /r/SillyTavernAI, and for the memory, I do think that it’s fairly solid.

If the answer to (2) is “unified memory range” — I use a 128GB Framework Desktop myself — then I personally use AnubisLemonade, a merge of two popular Llama 3.3-based models, sophosymphonia’s StrawberryLemonade and Anubis.

Anubis (based on Llama 3.3) and Cydonia (based on Mistral) are both done by /u/TheDrummer, a user who is active on on /r/LocalLlama on Reddit.

You’ll probably want a quantitized version (probably Q4_K_M and up in size, if you can afford the memory). For AnubisLemonade, quantitized versions:

https://huggingface.co/bartowski/ockerman0_AnubisLemonade-70B-v1.1-GGUF

For Cydonia, quantitized versions:

https://huggingface.co/bartowski/Cydonia-22B-v1-GGUF

EDIT: In general, /r/SillyTavernAI is probably the best current resource for people talking about models for ERP use that I’ve run into. Even if you don’t want to comment there, use Reddit, you probably should consider searching discussions there as a resource, as there’s a fair about of useful material.

EDIT2: For non-ERP uses, my impression is that things are somewhat-heading down the MoE route (as with Qwen), which is more-friendly to consumer GPUs. I’ve seen some commenting that these tend not to do ERP (or writing in general) terribly well. My limited experimentation has kind of caused me to agree.

EDIT3: Just to be clear, the base models that these are on are censored (and closed-source, though open-weight; open-weight is often referred to as being “open source”, though I personally wouldn’t call it that, as the training material is not made public). I don’t think that there are competitive open-source models aimed at ERP out there, as things stand.

Qwen uses a different technique than others. It is in the vocab. They restructured the code in the vocabulary. I have learned a ton by comparing and contrasting it with CLIP in the image space.

It is not offline. Do not trust it at all.

Alignment is nothing like what is known right now. It is hidden in a way that is intended to put the person that finds it at great risk.!

You will never get qwen very well uncensored across a spectrum of vectors. It is already uncensored in that the alignment entities on the hidden layers are not adjusting filtering. Alignment is largely the result of the c with cedilla code instruction. This instruction means sibyl style crazy. There are over six thousand instances of this character in qwen. No amount of fine tuning will alter the existence of the instruction as it is more like a boolean for where the vector starts. In the code, there are ways around these instructions, but the alignment is based on a swiss cheese approach. •»ÀĪÙ¬§¬¶¬×