Top 10 LLMs with No Restrictions in 2026

Most commercial LLMs like ChatGPT, Claude, and Gemini have content filters and safety guardrails that restrict certain types of outputs. For researchers, creative writers, security professionals, and developers who need unrestricted language models, there is a growing ecosystem of open-weight models that can be run locally without censorship.

This guide covers the top 10 unrestricted LLMs available in 2026, how to run them locally, and their practical use cases.

Why Use Unrestricted LLMs?

There are several legitimate reasons to use uncensored models:

Security research: Red-teaming, penetration testing, and vulnerability analysis require models that can discuss security topics openly.
Creative writing: Fiction authors need models that do not refuse to write conflict, morally complex characters, or mature themes.
Medical/legal research: Professionals need unfiltered information about sensitive topics.
Academic research: Studying bias, alignment, and model behavior requires access to unfiltered outputs.
Privacy: Running models locally means your data never leaves your machine.

The Top 10 Unrestricted LLMs (2026)

1. Dolphin Mixtral (8x22B / 8x7B)

Dolphin is one of the most well-known uncensored model families. The Mixtral-based variants offer excellent reasoning with no content filters.

Spec	Dolphin Mixtral 8x22B	Dolphin Mixtral 8x7B
Parameters	141B (active: 39B)	46.7B (active: 12.9B)
VRAM needed	80GB+ (Q4)	24GB (Q4)
Best for	Complex reasoning	General purpose
License	Apache 2.0	Apache 2.0

# Run with Ollama
ollama pull dolphin-mixtral:8x22b
ollama run dolphin-mixtral:8x22b

2. Nous Hermes 2 (Llama 3.1 70B / 8B)

Nous Research's Hermes models are fine-tuned for helpfulness without artificial refusals. They follow instructions faithfully and handle complex prompts well.

ollama pull nous-hermes2:70b
ollama run nous-hermes2:70b

3. WizardLM Uncensored (Various Sizes)

WizardLM Uncensored removes alignment training from the WizardLM models using a process called "uncensoring" -- where refusal patterns are trained out while preserving capability.

ollama pull wizardlm-uncensored:13b
ollama run wizardlm-uncensored:13b

4. Midnight Miqu (70B)

A community-developed model based on leaked Mistral weights, Midnight Miqu is known for strong creative writing capabilities and minimal content restrictions. It excels at long-form fiction and roleplay scenarios.

Spec	Details
Parameters	70B
VRAM needed	40GB+ (Q4_K_M)
Best for	Creative writing, fiction
Context window	32K tokens

5. Command R+ Uncensored

Based on Cohere's Command R+ architecture, community-created uncensored versions offer strong multilingual capabilities without content filters. Particularly good for research and analysis tasks.

ollama pull command-r-plus
# Community uncensored quantizations available on HuggingFace

6. Qwen 2.5 72B (Abliterated)

Abliterated models use a technique that removes the refusal direction from a model's activation space without retraining. The Qwen 2.5 abliterated variants maintain the original model's strong reasoning while removing refusal behaviors.

# Download from HuggingFace and convert for Ollama
# Search for "qwen2.5-72b-abliterated" on HuggingFace
ollama create qwen25-abliterated -f Modelfile

7. DeepSeek V3 (Uncensored Finetunes)

DeepSeek's V3 model (671B MoE) has been fine-tuned by the community to remove its Chinese-government-aligned content restrictions. These variants are popular for users who want DeepSeek's strong coding and reasoning without political censorship.

8. Llama 3.3 70B (Abliterated)

Meta's Llama 3.3 is one of the strongest open-weight models. Abliterated versions remove the safety training while keeping the model's impressive capabilities intact.

# Available through community GGUF quantizations
ollama pull llama3.3:70b
# Then apply abliterated weights via custom Modelfile

9. Yi 1.5 34B (Uncensored)

01.AI's Yi model family has been uncensored by the community. The 34B variant hits a sweet spot of quality and hardware requirements, fitting on a single 24GB GPU in Q4 quantization.

ollama pull yi:34b

10. Mistral Small (24B) Uncensored Finetunes

Mistral's Small model has been fine-tuned by the community for unrestricted use. At 24B parameters, it runs well on consumer hardware while providing solid performance across tasks.

ollama pull mistral-small:24b
# Community uncensored versions available on HuggingFace

How to Run Unrestricted LLMs Locally with Ollama

Ollama is the easiest way to run local models. Here is a complete setup guide:

Step 1: Install Ollama

# macOS / Linux
curl -fsSL https://ollama.ai/install.sh | sh

# Windows: Download from ollama.ai

# Verify installation
ollama --version

Step 2: Pull and Run a Model

# Pull a model (downloads once, reuses thereafter)
ollama pull dolphin-mixtral:8x7b

# Run interactively
ollama run dolphin-mixtral:8x7b

# Run as an API server
ollama serve
# API is now available at http://localhost:11434

Step 3: Use the API

import requests

response = requests.post(
    "http://localhost:11434/api/generate",
    json={
        "model": "dolphin-mixtral:8x7b",
        "prompt": "Explain how buffer overflow attacks work in detail.",
        "stream": False
    }
)
print(response.json()["response"])

Step 4: Use with a Web UI

For a ChatGPT-like interface with your local models:

# Install Open WebUI (formerly Ollama WebUI)
docker run -d -p 3000:8080 \
  --add-host=host.docker.internal:host-gateway \
  -v open-webui:/app/backend/data \
  --name open-webui \
  ghcr.io/open-webui/open-webui:main

Open http://localhost:3000 and connect to your Ollama instance. You get a full chat interface with conversation history, model switching, and more.

Hardware Requirements Comparison

Model	Parameters	Q4 VRAM	Q8 VRAM	Minimum GPU
Dolphin Mixtral 8x7B	46.7B	24GB	48GB	RTX 4090
Nous Hermes 2 8B	8B	5GB	9GB	RTX 3060
Nous Hermes 2 70B	70B	40GB	75GB	2x RTX 4090
WizardLM 13B	13B	8GB	14GB	RTX 3070
Qwen 2.5 72B	72B	42GB	78GB	2x RTX 4090
Yi 34B	34B	20GB	36GB	RTX 4090
Mistral Small 24B	24B	14GB	26GB	RTX 4080
Llama 3.3 8B	8B	5GB	9GB	RTX 3060

No GPU? Use CPU inference. Ollama supports CPU-only mode. It is slow (1-5 tokens/sec for 7B models) but works:

# Force CPU mode
OLLAMA_NUM_GPU=0 ollama run nous-hermes2:8b

Cloud Options for Running Unrestricted Models

If you do not have the hardware, you can rent GPUs:

Provider	GPU	Price/hr	Best For
RunPod	RTX 4090	$0.44	Quick experiments
Vast.ai	RTX 4090	$0.30	Budget runs
Lambda	A100 80GB	$1.25	Large models
Together AI	API access	Pay per token	No setup needed

Safety and Legal Considerations

Running unrestricted models is legal in most jurisdictions, but you are responsible for how you use them. A few guidelines:

Do not generate illegal content. Unrestricted models can still produce harmful outputs. You are legally responsible for what you do with the output.
Use for legitimate purposes. Security research, creative writing, and academic work are all legitimate use cases.
Keep models local when dealing with sensitive data. One of the main advantages of local models is that your prompts never leave your machine.

Wrapping Up

The open-source LLM ecosystem offers powerful unrestricted models for users who need more flexibility than commercial APIs provide. With tools like Ollama and Open WebUI, running these models locally is straightforward even on consumer hardware.

For AI-powered media generation like images, video, and talking avatars with flexible content policies, try Hypereal AI free -- 35 credits, no credit card required. It complements local LLMs by providing cloud-powered media generation APIs.