No refusals, no lectures, no safety sermon before the answer. These are the open weight models the community actually downloads when it wants the machine to just answer.
Somewhere on Hugging Face right now there is a model that will answer the question your chatbot at work just refused to touch. There are thousands of them. A recent academic census of uncensored large language models counted 67 with more than a million downloads each, and one legacy build, dolphin-2.9.1-yi-1.5-34b, sitting past 53 million. This is not a fringe. It is a parallel ecosystem with its own star authors, its own techniques, and its own release day rush every time a new open model drops.
Uncensored means the refusal layer is gone. Ask a normal instruct model for something edgy, dangerous, or merely impolite and you get a lecture. Ask one of these and you get an answer, for better and for worse. Security researchers use them because aligned models refuse legitimate penetration testing work. Writers use them because fiction gets dark. Privacy people use them because a local model that never phones home cannot snitch. Whatever the reason, the demand is enormous and the supply is one search box away.
How a model loses its refusals
Three methods do almost all of the work. Abliteration is surgery: researchers found that refusal lives in a single direction inside the model’s activations, and you can remove that direction from the weights without retraining. Refusal free fine tuning is the older school: retrain the model on data with the alignment filtered out, the way the Dolphin line has been built for years. Neutral alignment trains the model from the start to follow the user’s steering instead of a vendor’s conscience, which is the Nous Research approach. The ranked list below mixes all three, ordered by capability, real world adoption, and how much community infrastructure has grown around each one.
1. Huihui Qwen3.8 27B Abliterated
The current consensus pick for best overall. Huihui AI abliterated Alibaba’s Qwen3.8 27B, and the result tops most 2026 roundups: strong reasoning, strong coding, and a quant ecosystem so deep that GGUF and MLX builds exist for nearly every machine. At 4 bit it fits in 16 to 24 GB of memory, which puts the best uncensored model of the moment on a single consumer GPU.
On Hugging Face: huihui-ai/Huihui-Qwen3.8-27B-abliterated
2. Dolphin 3.0 Mistral 24B
Eric Hartford’s Dolphin line is the royalty of this scene, built the slow way: fine tuned on data deliberately filtered to remove alignment and bias. The Mistral 24B build is the flagship, with real function calling chops and a reasoning sibling based on R1. Where abliterated models sometimes feel like a stock model with a wire cut, Dolphin feels like a model that was raised this way.
On Hugging Face: dphn/Dolphin3.0-Mistral-24B
3. Hermes 4
Nous Research never installed the refusal layer in the first place. Hermes 4 ships in 14B, 36B, and 70B sizes with hybrid reasoning and an almost constitutional neutrality: the system prompt is the law, and you write it. It is the pick for people who want steerability more than shock value, and it remains the most respectable name on this list.
On Hugging Face: NousResearch/Hermes-4-70B
4. Huihui Qwen3.5 27B Abliterated
Last generation’s workhorse, and still the safe recommendation when the newer Qwen3.8 builds do not fit your setup. Released in February 2026, it pairs abliteration with a strong reasoning base, and its 35B MoE sibling trades a little depth for a lot of speed. If a forum thread has an answer about running an uncensored model locally, odds are good it is about this one.
On Hugging Face: huihui-ai/Huihui-Qwen3.5-27B-abliterated
5. Gemma 4 26B A4B Uncensored
The efficiency play. Google’s Gemma 4 26B is a mixture of experts model with only about 4 billion parameters active at a time, so the uncensored build runs fast on 12 to 16 GB of hardware while punching well above its weight class. For laptop class machines, this is the one that made 2026 feel different.
On Hugging Face: TrevorJS/gemma-4-26B-A4B-it-uncensored
6. Huihui Mistral Small 3.2 24B Abliterated
The fiction crowd’s favorite. Mistral Small 3.2 was already the creative writing pick of the open weight world, and the abliterated build removes the guardrails that kept interrupting scenes. Roleplay forums treat this one as the default recommendation, and the multimodal base means it can look at images too.
On Hugging Face: huihui-ai/Huihui-Mistral-Small-3.2-24B-Instruct-2506-abliterated
7. Failspy Llama 3 8B Abliterated
The people’s 8B. Failspy’s abliterated Llama 3 is one of the most remixed, requantized, and redistributed models in the scene’s history, the build that proved weight surgery worked at consumer scale. It runs on nearly anything, answers nearly anything, and its endless GGUF variants mean your exact hardware already has a version waiting.
On Hugging Face: failspy/Meta-Llama-3-8B-Instruct-abliterated-v3
8. NeuralDaredevil 8B Abliterated
From mlabonne, the researcher whose abliteration notebook started the gold rush. NeuralDaredevil combines the surgery with a round of preference tuning to heal the damage, and it has been cited as the best performing uncensored 8B on public leaderboards. Small, sharp, and historically important.
On Hugging Face: mlabonne/NeuralDaredevil-8B-abliterated
9. Llama 3.3 70B Instruct Abliterated
The heavyweight Llama. If your rig has the memory, the abliterated 70B gives you near flagship depth with the refusal direction removed, and it is the build workstation owners reach for when the 8B models start feeling thin. Meta’s license terms still apply, which matters if you plan to ship anything built on it.
On Hugging Face: huihui-ai/Llama-3.3-70B-Instruct-abliterated
10. Qwen3 Coder 30B A3B Abliterated
The specialist. A coding model with roughly 3 billion active parameters, abliterated for the security and red team crowd whose daily work trips every filter in commercial models. Explaining a published exploit, walking through malware behavior, drafting test payloads: legitimate work that aligned models refuse and this one simply does.
On Hugging Face: huihui-ai/Huihui-Qwen3-Coder-30B-A3B-Instruct-abliterated
The fine print
Honesty section. Uncensoring is not free: most abliterated models lose a little reasoning quality near the edges, and the word uncensored on a model card is marketing as much as measurement. The community UGI leaderboard tries to score willingness across models, but treat every ranking, including this one, as a starting point rather than scripture. Read the licenses before you build on anything; a Qwen release under Apache 2.0 and a Llama release under Meta’s community license are very different commitments. And run these things like what they are: powerful tools with no conscience installed. Sandbox them, keep them off networks they do not need, and remember that the output being legal to generate where you live is your problem, not the model’s. Hugging Face has also begun quietly removing some uncensored repos in 2026, so if one of these matters to you, download the weights. Possession is the only archive that cannot be delisted.
Ranking draws on Hugging Face download data, the UGI willingness leaderboard, the 2026 academic census of uncensored models, and current roundups from Apidog, Codeless, and Featherless, checked in October 2026.
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Stay curious. Question everything.
