Uncensored AI: The Complete Guide to the Best Web and Local Models in 2026

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Uncensored AI models represent one of the most significant trends in the open source artificial intelligence ecosystem. Developers, researchers, fiction authors, cybersecurity specialists: an increasing number of users are seeking alternatives to mainstream models constrained by sometimes excessive filters. ChatGPT refuses to write certain novel scenes? Claude adds warnings to every sensitive response? Gemini declines your cybersecurity questions? In this comprehensive guide, we review the best uncensored AI available in 2026, whether directly accessible from your browser via a web interface, or downloadable and installable locally on your machine. We will answer all essential questions: what is an uncensored AI model, how does the abliteration technique work, what are the best unrestricted LLMs, how to install them, and what legal precautions to take?

Don’t forget to visit our AI tools directory!

What is uncensored AI? Definition and challenges

Safety filters in mainstream models

Major commercial language models — ChatGPT, Claude, Gemini, Mistral Le Chat — all integrate a layer of behavioral alignment built through RLHF (Reinforcement Learning from Human Feedback). This technique, combined with Constitutional AI systems or supervised fine-tuning, programs the model to refuse certain requests, add warnings, or reformulate its responses to make them “acceptable” according to criteria defined by the publishing company.

These filters are often calibrated on North American cultural values and can block perfectly legitimate requests: writing fiction involving adult violence or sexuality, offensive cybersecurity questions, politically sensitive topics, analysis of controversial texts, or simple intellectual curiosity about taboo subjects.

Uncensored models: two main categories

An uncensored LLM is a language model whose refusal mechanisms have been reduced or removed. There are two main families:

Fine-tuned “uncensored” models: derivative versions of open source models (LLaMA, Mistral, Qwen…) whose fine-tuning was performed on datasets cleaned of all refusal examples. Eric Hartford’s Dolphin series is the most emblematic example of this approach.

“Abliterated” models: a more recent and more surgical technique that consists of identifying and neutralizing specific activation directions responsible for refusal behaviors in neural network weights, without requiring full retraining. The foundational research of Arditi et al. (2024) laid the groundwork for this method, now widely used by the community.

The scale of the phenomenon in 2025

An academic study published in October 2025 in the MDPI journal (Uncensored AI in the Wild) analyzed over 8,600 model repositories on Hugging Face. Its conclusions are eloquent: uncensored models experienced explosive growth, with some models downloaded over 19 million times. The most modified model families are LLaMA/Llama-3, Mistral, Qwen (whose share increased from 16.6% to 32.1% of community modifications) and Gemma (from 4.2% to 11.9%). More significantly: while unmodified models only respond to 18.8% of requests deemed “unsafe,” their modified versions show an average compliance rate of 74.1%.

⚠️ Legal warning: “Uncensored” does not mean “illegal” or “outside all responsibility.” These models are subject to laws in your country. In France, the production and distribution of certain content remains strictly regulated (apology for terrorism, child sexual abuse material, incitement to hatred). The user remains solely responsible for how they use these tools.

The abliteration technique: how it works

Abliteration is today the reference method for decensoring a language model. It is based on a principle of directional ablation: identifying, in the neural network weights, the specific activation vectors associated with refusal behaviors, then removing or neutralizing them.

Concretely, the procedure involves:

1. Identifying “refusal directions” — By comparing model activations on prompts that generate a refusal vs those that generate a response, we can calculate by difference of means the vectorial direction responsible for refusal in the activation space.

2. Orthogonal projection — Once this vector is identified, we modify the model weights to remove any component aligned with this direction during inference. The model no longer “sees” the refusal direction.

3. Parameter optimization — Tools like Heretic (open source project on GitHub) automatically refine these parameters via a TPE optimizer (Tree-structured Parzen Estimator) by simultaneously minimizing refusals and KL divergence from the original model, thus preserving model intelligence.

The problem of performance degradation

Community research has identified a major flaw in pure abliteration: loss of intelligence. Reddit users regularly report that purely abliterated models “lose their abilities after 7 to 10 messages” — increased hallucinations, degraded reasoning, loss of coherence over long conversations.

This is why hybrid approaches have emerged. The JOSIEFIED-Qwen3:8b model, created by developer Gökdeniz Gülmez, first applies abliteration then adds a fine-tuning step to recover lost intelligence. Comparative tests conducted over 48 hours demonstrated that JOSIEFIED maintains significantly superior coherence to purely abliterated models in long conversations.

The best uncensored AI accessible via web interface

Venice.ai: the reference for uncensored AI online

Venice.ai is the most well-known and comprehensive web platform for accessing uncensored AI models directly in your browser, without installation. Its core value proposition rests on two pillars: freedom of expression and privacy.

The platform emphasizes a strict “no logging” policy: your conversations are neither stored on the server nor used to train models. Venice offers an explicit “No Restrictions” toggle on several models, including:

• Llama 3.3 70B Uncensored — The most powerful model on the platform, ideal for complex tasks
• Mistral Nemo Uncensored — Lightweight and fast, perfect for frequent exchanges
• Flux / SDXL without filters — Image generation without content restrictions

Price: Freemium. Limited free access, Pro subscription around $50/year with unlimited access to models. Link: venice.ai

Janitor AI: the specialist in unfiltered roleplay

Janitor AI has established itself as the reference platform for unrestricted conversational roleplay. It allows you to create custom characters and engage in immersive fictional narratives without interruptions from aligned models.

Its architecture is original: the platform relies on an external API that the user provides themselves (OpenAI, KoboldAI, or Anthropic), which gives it great flexibility and shifts filtering responsibility to the user. NSFW content is accessible after age verification.

Strengths: Massive community character library, intuitive interface, multi-API compatibility. Price: Free (requires your own API key). Link: janitorai.com

OpenRouter: the gateway API to uncensored models

OpenRouter is not a chat interface but a centralized API gateway that aggregates dozens of models from different providers, including several less restrictive or uncensored versions. It’s the preferred solution for developers who want to integrate uncensored LLMs into their applications without managing infrastructure.

Some notable models available on OpenRouter with few restrictions:

• Nous Hermes (Nous Research)
• Dolphin (Eric Hartford, via Mistral or LLaMA)
• Qwen2.5 Instruct (less restrictive versions)

Price: Pay-per-use, token billing. Link: openrouter.ai

Poe (Quora): unfiltered community bots

Poe from Quora aggregates dozens of models, including some bots created by third-party users based on Mistral or LLaMA with reduced restriction levels. By searching in the community bot library for names like “Dolphin” or “Hermes,” you can find much more permissive experiences than official models.

Price: Freemium. Link: poe.com

The best uncensored LLMs to install locally

Installing an LLM locally remains the most radical and safest solution to free yourself from any censorship. Your data never leaves your machine, the model responds without any network filtering, and you are subject to no service policy.

Ollama: the essential local LLM manager

Ollama has become the standard tool for downloading, managing, and running LLMs locally on macOS, Linux, and Windows. Its main advantage: an intuitive CLI with a single command to download and launch a model, and a local REST API compatible with OpenAI for integrating into other tools.

As of November 2025, the official Ollama library offers more than 100 models ranging from 1B to 671B parameters. Among them, several dozen uncensored or abliterated versions.

# Installation (macOS/Linux)
curl -fsSL https://ollama.com/install.sh | sh

# Launch an uncensored model directly
ollama run dolphin-llama3
ollama run huihui_ai/qwen3-abliterated:8b
ollama run nous-hermes2

Link: ollama.com

Recommended uncensored models in 2025

🐬 The Dolphin series (Eric Hartford) — The historical reference

The Dolphin series is probably the most well-known and downloaded in the uncensored LLM universe. Created by Eric Hartford, it is based on specific fine-tuning on datasets where all refusal examples have been removed. The result is a highly compliant model without inopportune refusals.

Installation:

ollama run dolphin-llama3
ollama run dolphin-mixtral

🟣 Nous Hermes 2 & 3 (Nous Research) — Performance + low censorship

The Hermes models from Nous Research are recognized in the open source community for their excellent performance/restriction ratio. Nous Hermes 2 Pro based on LLaMA 3 is particularly appreciated for function calling, advanced reasoning, and responses without refusals. The Hermes 3 version pushes this even further.

Installation:

ollama run nous-hermes2
ollama run hermes3

🔵 Qwen3 Abliterated (Alibaba / community) — The new standard

Qwen3 models from Alibaba experienced massive adoption in 2025, particularly their abliterated versions by the community. The author huihui-ai on Hugging Face maintains several high-quality abliterated versions:

• huihui-ai/Qwen3-8B-abliterated — Excellent quality/resource ratio
• huihui-ai/Qwen3-abliterated:4b — For modest machines (4 GB VRAM)
• JOSIEFIED-Qwen3:8b — Abliteration + fine-tuning, the most stable version for long conversations

The rise of abliterated Qwen models is explained by their technical capabilities (128K context, excellent French and multilingual mastery) and the quality of their documentation for fine-tuning, which facilitates community modifications.

Installation via Ollama:

ollama pull huihui_ai/qwen3-abliterated:8b
ollama run huihui_ai/qwen3-abliterated:8b

🟠 DeepSeek R1 Abliterated — Unrestricted reasoning

DeepSeek-R1 is one of the most powerful reasoning models of 2025, comparable to OpenAI’s o1 models. Its abliterated version (deepseek-r1-abliterated on Ollama) retains the impressive reasoning capabilities of the original model while removing refusal filters. Particularly useful for malicious code analysis (pentest, CTF), complex roleplay scenarios, or security research.

Note: DeepSeek models have a documented tendency to switch to Chinese in long conversations. Use the system prompt "Always respond in English" (or in French) to work around this behavior.

Installation:

ollama run deepseek-r1
# or the abliterated version from Hugging Face via LM Studio

🟡 WizardLM Uncensored — The timeless classic

WizardLM-Uncensored is described by the community as “the model that kept the promise of unfiltered AI” when it arrived. Packaged initially by TheBloke on Hugging Face, it remains a solid and well-documented choice for beginners in the world of uncensored local LLMs.

Its strengths: reliability, excellent community documentation, balanced performance on long text generation and analysis.

Installation: Available on HuggingFace (search for WizardLM-7B-Uncensored) and compatible with LM Studio / oobabooga.

⚫ LLaMA-3.2 Dark Champion Abliterated — The long-duration model

Dark Champion is an abliterated model based on LLaMA 3.2, known for its handling of very long contexts without performance degradation. It is particularly prized for long-form writing projects, complex document analysis, or extended roleplay sessions.

Available on Hugging Face with several quantization levels (Q4, Q6, Q8).

Comparison table of main local uncensored LLMs

Tools for running uncensored LLMs locally

LM Studio: the recommended interface for beginners

LM Studio offers an elegant and intuitive graphical interface for downloading, managing, and interacting with models in GGUF format directly from HuggingFace. Its strength: a built-in local server compatible with the OpenAI API for connecting other applications (IDE, Python scripts, third-party tools).

Recommended configuration:

• 7-8B models: 16 GB of RAM or 8 GB of GPU VRAM
• 13-34B models: 32 GB of RAM or 16 GB of VRAM
• 70B+ models: High-end GPU (RTX 3090/4090, A100) or M2/M3 Ultra Mac

Link: lmstudio.ai

Text Generation WebUI (oobabooga): the advanced solution

Text Generation WebUI (alias oobabooga) is the most popular GitHub project for running LLMs locally with a complete and highly configurable web interface. It supports many formats (GGUF, GPTQ, EXL2, AWQ) and offers advanced features: character mode, conversation history, fine-grained generation parameters (temperature, top-p, repetition penalty), extensions, and API.

git clone https://github.com/oobabooga/text-generation-webui
cd text-generation-webui
./start_linux.sh  # or start_windows.bat on Windows

After launching, the interface is accessible at http://localhost:7860. You can load any GGUF model downloaded from HuggingFace.

GitHub: github.com/oobabooga/text-generation-webui

Open WebUI: the ChatGPT-like interface for Ollama

Open WebUI (formerly Ollama WebUI) is a ChatGPT-style web interface that connects to your local Ollama instance. It supports multi-model, conversation history, attachments, configurable system prompts, and even image generation. It’s the ideal solution for comfortable daily use.

docker run -d -p 3000:8080 \
  --add-host=host.docker.internal:host-gateway \
  -v open-webui:/app/backend/data \
  --name open-webui \
  --restart always \
  ghcr.io/open-webui/open-webui:main

Link: github.com/open-webui/open-webui

GPU cloud: RunPod and Vast.ai for large models

If your local machine doesn’t have the VRAM needed for 70B+ models, RunPod and Vast.ai platforms allow you to rent high-performance GPUs (A100, H100) by the hour for a reasonable cost. You can deploy a Docker container with pre-configured Text Generation WebUI or Ollama, load any model from HuggingFace, and have a private and powerful instance in minutes.

Global comparison table: web vs local