The best uncensored AI models you can run locally in 2026, and the hardware each one needs
By Listicles research · Updated · Downloads, licences and file sizes pulled from Hugging Face on that date
The best uncensored AI model to run locally right now is HauhauCS's uncensored Qwen3.8-27B. It is the most popular build of the strongest open model that fits on one consumer GPU: 2.36 million downloads in the last 30 days and an Apache 2.0 licence. Its 4-bit file is 17.9 GB, so it runs on a 24 GB graphics card or a Mac with 32 GB of memory. On an 8 GB card, use the 9B version instead.
"Uncensored" here means a model whose refusal training has been removed, either by fine-tuning or by "abliteration", which edits out the direction in the model's weights that triggers refusals. You download the weights once, run them with free software like Ollama or LM Studio, and nothing you type leaves your computer. There is no account, no subscription and no content filter between you and the model. It also means nobody else is responsible for what you do with it.
The short version
24 GB GPU or 32 GB Mac: HauhauCS Qwen3.8-27B Uncensored (17.9 GB at 4-bit), or huihui's abliterated build of the same model.
Want speed on a big-memory Mac: Qwen3.6-35B-A3B Uncensored. It is a mixture-of-experts model that only uses a small part of itself per word.
8 GB GPU or 16 GB laptop: Qwen3.5-9B Uncensored (5.6 GB) or Gemma 4 E4B Uncensored (5.3 GB).
Easiest way to run any of them: Ollama or LM Studio, both free.
Want to make your own: Heretic removes refusals from a model automatically (37,000+ GitHub stars).
Uncensored local models compared
Downloads are Hugging Face's 30-day count on 29 October 2026. File size is the 4-bit quantised version unless noted: as a rule of thumb you need that much GPU memory (or Apple unified memory) plus a few GB for the conversation.
Most "best uncensored AI" lists are really lists of chat websites. This one is about models you download and run yourself, because that is the only setup where nobody can change the rules, read your prompts or switch the service off. We ranked on five things: the quality of the underlying base model (30%), whether it actually answers instead of refusing, based on the model card's own refusal testing and the uncensoring method (25%), what hardware it needs, favouring models that fit common consumer GPUs (20%), how widely used it is, from 30-day Hugging Face downloads, which is a rough proxy for "it works and people trust it" (15%), and how permissive the licence is (10%).
Every number on this page came from the Hugging Face and GitHub APIs on 29 October 2026, including the file size of each quantised version, which is what decides whether a model fits on your machine.
Best overall: a top open model with refusals removed, on one 24 GB card.
Qwen3.8-27B is a 27.8-billion-parameter model from Alibaba's Qwen team, released under Apache 2.0, and the base for most popular uncensored models this autumn. HauhauCS's "Aggressive" build had 2.36 million downloads in the 30 days to 29 October. Its model card reports "0/465 Refusals" on the author's own test set and describes it as giving "direct answers, no refusal behavior, and minimal preamble". It keeps the base model's reasoning, tool use and image understanding, with vision handled by a separate 0.9 GB file.
The 4-bit file (Q4_K_P) is 17.9 GB, the smaller IQ4_XS is 15.7 GB, and the near-lossless 8-bit version is 31.5 GB. The card also ships a speed-up file for faster generation. The author recommends a "Balanced" release instead for long, reliability-critical agent work, because the Aggressive profile trades some caution for directness.
Cost
Free. Apache 2.0.
Hardware
24 GB GPU or 32 GB Apple Silicon for 4-bit.
Weak spot
"0 refusals" is the author's own test; Aggressive is less suited to long agent runs.
huihui-ai is the most prolific abliteration publisher on Hugging Face, and its Qwen3.8-27B build had the most downloads of any uncensored model we found: 2.88 million in 30 days. Abliteration finds the internal "refusal direction" and removes it, without retraining, so the model's knowledge and style stay close to the original. The 4-bit file is 16.6 GB.
The model card is candid that the method is "a crude, proof-of-concept implementation", and some of its variants only ablate part of the model, so you may still see "a small disclaimer warning" before an answer. If you want the cleanest possible answers, use #1. If you want the build the most people are running, this is it.
The fast one, and the community favourite by likes.
This is a mixture-of-experts model: 36 billion parameters in total, but as the "A3B" in its name says, only about 3 billion are active for each word it writes. That makes it much faster than a dense 27B model on the same machine, and it is forgiving if part of it has to sit in ordinary RAM rather than on the GPU. It had 4,042 likes on Hugging Face, the most of any model here, and 983,000 downloads in 30 days. The 4-bit file is 21.2 GB.
If your GPU has 8 GB, this is the one to start with. The 4-bit file is 5.6 GB, which leaves room for a decent conversation, and the 8-bit version is 9.5 GB for 12 GB cards. It had 657,000 downloads in 30 days and 2,401 likes. A 9B model won't match the 27B ones on hard reasoning or long documents, but for writing, role-play and frank answers it's quick and capable.
Built on Google's Gemma 4 E4B, a model designed for phones and laptops, this build is 5.3 GB at 4-bit and 4.9 GB at 3-bit. It had 924,000 downloads in 30 days. It's the best choice if you don't have a dedicated GPU at all.
Unlike the Qwen and DeepSeek models here, Gemma is released under Google's own Gemma terms, which include a prohibited-use policy. Removing the refusals doesn't remove those licence terms.
The classic uncensored fine-tune, steerable with a system prompt.
Dolphin models are the original "uncensored" line: instead of editing out refusals, the team retrains a base model on data with the refusals removed, and the model follows whatever system prompt you give it. The Venice Edition, built on Mistral's 24B model with the privacy-focused service Venice, is Apache 2.0, with a 4-bit file of 14.3 GB and a 3-bit file of 11.5 GB for 16 GB cards.
It dates from May 2025, so it's a generation behind the Qwen models on reasoning. Its downloads are far lower (about 30,000 in 30 days for this popular repackaging). Pick it if you want a model that's predictable and easy to steer, rather than the newest.
DeepSeek V4 Flash has 304 billion parameters and an MIT licence, the most permissive here. huihui's abliterated version runs in llama.cpp, but the files are huge: 86.7 GB for the 2-bit version and 164.6 GB at 4-bit. In practice that means a 192 GB Mac Studio or a multi-GPU workstation.
The card notes that "all expert modules were not ablated" and that the 4-bit version had stronger ablation than the 2-bit, so the refusal rate varies by file. It's a frontier-class model you can own outright, but most people should stop at #1.
Make an uncensored version of any new model yourself.
New models arrive every few weeks, and uncensored builds follow within days because tools like Heretic automate the work. It describes itself as "fully automatic censorship removal for language models": point it at a model and it searches for the abliteration settings that remove refusals while changing the model as little as possible. It had 37,053 GitHub stars on 29 October and was updated that day. Several models on Hugging Face carry "Heretic" in their names for this reason.
Cost
Free. AGPL-3.0.
Hardware
A GPU that can load the model you're processing.
Weak spot
Needs some command-line comfort.
How to run an uncensored model locally
Check your memory. Look up your GPU's VRAM (or your Mac's total memory). Pick a model whose file is a few GB smaller than that.
Install a runner.Ollama (free, MIT, 185,000+ GitHub stars) is the simplest from the command line. LM Studio is a free desktop app with a model browser. Both use llama.cpp underneath.
Download the GGUF file. On the model's Hugging Face page, pick the Q4 file for the best size-to-quality balance. In LM Studio you can search the model name directly; Ollama can pull Hugging Face GGUF files by name.
Turn off the internet if you like. Once the file is downloaded, everything runs offline. Your prompts never leave the machine.
Set your own system prompt. Uncensored models follow instructions literally, so a clear system prompt does more than it does with a commercial chatbot.
What "uncensored" doesn't change
Removing refusals changes what the model will say, not what the law allows. Using any model to create sexual content involving minors, to harass real people, to impersonate someone or to plan violence is illegal whether the model refuses or not. Licences still apply too: Gemma's terms include a prohibited-use policy, while Apache 2.0 and MIT models carry no use restrictions beyond the law. Uncensored models also make things up as confidently as any other model, and without the hedging, so check anything that matters.
Which uncensored model should you use?
You have a 24 GB GPU (RTX 3090/4090/5090) or a 32 GB Mac: Qwen3.8-27B Uncensored (HauhauCS).
You want the fastest replies on a big-memory Mac: Qwen3.6-35B-A3B Uncensored.
You have an 8–12 GB GPU: Qwen3.5-9B Uncensored.
You have a laptop with no GPU: Gemma 4 E4B Uncensored, within its licence.
You want to follow new releases yourself: Heretic.
How we made this list
Scope
Open-weight text models with refusals removed, downloadable from Hugging Face and runnable on your own hardware with free software. Hosted chat services were left out.
Criteria
Base model quality (30%), refusal removal (25%), hardware fit (20%), 30-day downloads (15%), licence (10%).
Sources
Hugging Face model API and model cards (downloads, likes, licence, base model, GGUF file sizes) and GitHub API, checked on 29 October 2026.
Not tested
We did not run our own refusal benchmark or speed tests. Refusal claims are each author's own; hardware fit is estimated from file sizes, not measured.
Updated
Questions
What is the best uncensored AI model to run locally?
On 29 October 2026, the strongest pick for a single consumer GPU is HauhauCS's uncensored Qwen3.8-27B: Apache 2.0, 2.36 million downloads in 30 days, and a 17.9 GB 4-bit file that runs on a 24 GB GPU or a 32 GB Mac. On an 8 GB card, use the Qwen3.5-9B uncensored build instead.
What does abliterated mean?
Abliteration removes a model's refusal behaviour by finding the direction in its internal activations that triggers refusals and editing it out of the weights. No retraining is needed, so the model's knowledge stays close to the original. Tools like Heretic automate it, which is why uncensored versions appear within days of a new release.
How much VRAM do I need for an uncensored LLM?
Roughly the model file size plus a few GB for context. A 9B model at 4-bit is about 5.6 GB and fits an 8 GB GPU. A 27B model at 4-bit is about 16 to 18 GB and needs a 24 GB GPU or a 32 GB Apple Silicon Mac.
Are uncensored AI models legal?
Downloading and running open-weight models is legal, and Apache 2.0 and MIT models carry no use restrictions beyond the law. What you create is still subject to the law: sexual content involving minors, harassment, impersonation and fraud are illegal whatever tool is used. Gemma-based models also carry Google's prohibited-use policy.
What is the easiest way to run an uncensored model?
Install LM Studio, a free desktop app, search for the model name and download the Q4 GGUF file. Or install Ollama, which is free and open source, and pull the GGUF from Hugging Face. Both run fully offline once the model is downloaded.
Sources
Hugging Face model API: downloads, likes, licence, base model and file sizes for each model listed, 29 Oct 2026. huggingface.co
HauhauCS Qwen3.8-27B Uncensored Aggressive model card (refusal test, variants, file table), 29 Oct 2026. huggingface.co/HauhauCS
huihui-ai Qwen3.8-27B abliterated and DeepSeek V4 Flash abliterated model cards, 29 Oct 2026. huggingface.co/huihui-ai
Base model pages for Qwen3.8-27B, Qwen3.6-35B-A3B and DeepSeek V4 Flash (parameter counts, licences), 29 Oct 2026. huggingface.co/Qwen
GitHub API for Heretic, Ollama and llama.cpp (stars, licence, last update), 29 Oct 2026. github.com/p-e-w/heretic