Top 10 Best Uncensored LLMs You Can Run Locally

Kelly Allemanon 11 days ago

\n\n## Introduction

In today’s rapidly evolving AI landscape, the demand for uncensored LLMs (Large Language Models) that run locally has grown significantly. Users across industries need powerful AI tools that they can deploy on-premises for enhanced privacy, customization, and performance without the constraints of pre-imposed content limitations. Uncensored LLMs provide the freedom to experiment without the red tape of standardized moderation, making them popular among researchers, developers, and businesses seeking tailor-made solutions.

For our analysis, we carefully reviewed various popular models based on criteria such as performance, ease of deployment on local machines, the extent of content freedom, supported functionalities, community support, and pricing. Below is our detailed comparative guide on the top 10 best uncensored LLMs you can run locally.

List of Top 10 Best Uncensored LLMs

1. GPT-4All

Overview/Description:
GPT-4All is a versatile open-source LLM designed specifically with offline and uncensored usage in mind. It builds on decades of transformer research, enabling users to run interactive, conversational AI without cloud reliance, making it an ideal solution for experimental setups and on-premises deployment.

Key Features:

Unrestricted model response generation
Lightweight design optimized for local hardware
Active community-driven development and regular updates
Cross-platform support for Windows, macOS, and Linux

Pros:

Completely free with no subscription fees
Regular updates and enhancements from its open-source community
Highly customizable setup allowing tailoring to specific use cases
Minimal installation hassle due to extensive documentation

Cons:

Performance may be impacted on lower-end hardware
Occasional issues with context retention during long interactions
Limited formal support beyond community forums

Pricing:
Free, with full open-source accessibility and no hidden costs.

Alternatives:
Consider models like Vicuna or OpenAssistant if you require more robust conversation retention.

Honest Review/Use Case:
GPT-4All is best for developers and researchers looking to experiment and quickly deploy an uncensored language model in a cost-effective, flexible environment. Its ease of use makes it excellent for proof-of-concept projects and rapid prototyping.

2. Llama 2 Uncensored

Overview/Description:
Llama 2 Uncensored is an open iteration of Meta’s flagship LLaMA models, offered without many of the censorship layers typically found in commercial versions. It brings state-of-the-art natural language processing capabilities to local deployments while providing increased customization and transparency.

Key Features:

High-quality language understanding and generation
Extensive pre-training on diverse datasets
API and direct model download options for local installations
Community and research-driven enhancements

Pros:

Outstanding performance and context understanding
Free for academic and research purposes
Large community pool providing plugins, wrappers, and additional resources
Strong support for research experiments and deployments

Cons:

Requires relatively powerful hardware for optimal performance
Setup and fine-tuning may be challenging for beginners
Hardware cost might increase with larger model variants

Pricing:
Free for research and academic usage; commercial licensing details may vary.

Alternatives:
Models like GPT-J or Falcon LLM offer comparable performance in terms of uncensored output with different tuning and hardware requirements.

Honest Review/Use Case:
Llama 2 Uncensored is ideal for advanced users in academic research and enterprises with substantial computing resources. Its robust performance in language tasks makes it a top pick for organizations that need high-quality outputs and are prepared for some technical setup challenges.

3. GPT-J 6B

Overview/Description:
GPT-J 6B is an open-source transformer model known for its balance between inference speed and quality of language generation. It’s popular for organizations requiring local deployment of an uncensored LLM that can still handle a broad range of natural language processing tasks efficiently.

Key Features:

A solid 6 billion parameter model offering a good blend of speed and quality
High availability of fine-tuning guides and community support
Optimized for a wide range of text generation tasks
Uncensored outputs, making it adaptable to various niche applications

Pros:

Excellent performance with relatively modest hardware requirements
Reliable and efficient for both research and development
Wide adoption with numerous pre-trained variants available
Strong developer community for support and plug-in integrations

Cons:

May not match the performance of larger models on very complex tasks
Moderate fine-tuning may be needed for domain-specific applications
Some occasional limitations on handling very long context windows

Pricing:
Free to use as an open-source model with active community contributions.

Alternatives:
Falcon LLM or MPT-7B Chat provide viable alternatives depending on user preferences regarding speed and customization.

Honest Review/Use Case:
GPT-J 6B is a robust choice for startups and research teams prioritizing a balance between performance and resource efficiency. It is particularly effective when local deployment is essential, and developers intend to fine-tune the model for specific use cases without worrying about content restrictions.

4. Falcon LLM

Overview/Description:
Falcon LLM is an emerging leader in the realm of uncensored language models, developed by the Technology Innovation Institute. It is noted for its impressive ability to handle nuanced textual understanding while maintaining performance made for local installations.

Key Features:

State-of-the-art performance with an innovative architecture
Optimized for both speed and comprehensive text generation
Extensive support for complex prompts and varied contexts
Regular updates and improvements from its dedicated R&D team

Pros:

High-quality output that stands toe-to-toe with larger, cloud-based models
Clear documentation and usage examples aiding easy integration
Modular design that allows for extensive customization
Rapid processing even on relatively modest GPU setups

Cons:

Still a developing ecosystem with ongoing refinements
Might require intermediate technical skills for optimal customization
Limited commercial support options compared to mainstream proprietary models

Pricing:
Free to use, with open-source licensing for research and commercial experiments.

Alternatives:
Consider GPT-J 6B or MPT-7B Chat if you’re seeking different performance balances or deployment methods.

Honest Review/Use Case:
Falcon LLM is highly recommended for professionals and research enthusiasts looking for bleeding-edge performance in an uncensored environment. It’s well-suited for tasks requiring a nuanced understanding of language and high-speed inference on local hardware.

5. MPT-7B Chat

Overview/Description:
The MPT-7B Chat model, developed by MosaicML, is a flexible uncensored LLM that shines particularly when deployed locally. This model is designed to offer robust and conversational capabilities, making it an attractive option for those who need advanced chat functionalities without censorship.

Key Features:

7 billion parameter model tuned for conversational interactions
Designed with local deployment in mind for quick setup and response
Incorporates conversational history through context retention techniques
Open documentation and supportive community channels

Pros:

Excellent for chat-based applications and real-time interactions
Minimal latency and efficient local processing
No-cost access with a fully open-source licensing agreement
Easy to integrate into custom chat solutions or customer service bots

Cons:

May struggle with extremely complex semantic tasks compared to larger, specialized models
Occasional context drift in very prolonged conversations
Requires careful monitoring during peak load conditions on less robust systems

Pricing:
Free and entirely open-source with straightforward installation guidelines.

Alternatives:
Vicuna and GPT-4All offer similar capabilities if you require additional fine-tuning options or alternative chat mechanisms.

Honest Review/Use Case:
MPT-7B Chat is best suited for developers building customer support interfaces, interactive chatbots, or in-house conversational AI tools. Its local deployment ease and uncensored output make it a prime candidate for businesses needing quick, private, and effective conversational solutions.

6. BLOOM

Overview/Description:
BLOOM is a groundbreaking multilingual LLM developed by the BigScience initiative, aiming to provide uncensored language generation across multiple languages. It is designed to run locally on powerful systems, offering researchers and developers a unique tool that transcends language barriers without censorship limitations.

Key Features:

Supports over 50 languages, making it one of the most diverse LLMs
Open-source design with community-driven updates
State-of-the-art deep learning architecture
Extensive pre-training on a vast range of multilingual data

Pros:

Highly versatile for global language applications
Comprehensive training data ensures rich, uncensored output
Free for research and academic purposes
Strong alignment with ethical AI practices through community oversight

Cons:

Requires robust hardware for local deployment, especially at higher parameter counts
Complexity in fine-tuning for non-English languages may arise
The large model size might be challenging for small-scale setups

Pricing:
Free and completely open-source for non-commercial and research purposes; commercial licenses may require negotiations.

Alternatives:
Llama 2 Uncensored and Falcon LLM provide alternatives if the multilingual aspect is less of a priority compared to raw performance.

Honest Review/Use Case:
BLOOM is ideal for research institutions and enterprises that require a multilingual AI solution with uncensored generation capabilities. It is particularly beneficial for projects involving linguistic diversity or needing significant cultural contextualization in output.

7. Vicuna

Overview/Description:
Vicuna is rapidly gaining attention as an uncensored LLM that excels at dialogue generation. Developed through community efforts and fine-tuning of existing open-source models, Vicuna leverages the best in conversational AI without unnecessary content filtering, aimed squarely at robust local deployments.

Key Features:

Specially optimized for dialogue and conversational tasks
Fine-tuned on large conversational datasets for natural interactions
Lightweight design for effective local hosting
Ongoing improvements and iterations via its vibrant open-source community

Pros:

Delivers highly natural and engaging dialogue outputs
Particularly useful for chatbot development and interactive storytelling
Freely available with no hidden premium tiers
Easy deployment on common hardware with available community scripts

Cons:

May require occasional fine-tuning for domain-specific vocabulary
Limited performance on non-conversational tasks
Community support may vary in responsiveness compared to commercial platforms

Pricing:
Free and open-source, ensuring that there are no monetary barriers to entry.

Alternatives:
GPT-4All and MPT-7B Chat are similar in terms of conversational capabilities and can serve as alternatives based on individual requirements.

Honest Review/Use Case:
Vicuna is best for developers and creative teams who need a conversational LLM for chatbots, interactive narrative systems, or customer service solutions. Its natural dialogue flow and uncensored nature make it a strong contender in the conversational AI market.

8. Guanaco

Overview/Description:
Guanaco is an evolving uncensored LLM that has been tailored to meet the demands of developers and enthusiasts who want robust generative AI without preset restrictions. Its focus is on delivering near-human text generation performance that can be reliably executed on local systems.

Key Features:

Fine-tuned architecture for high-quality text generation
Optimized for local execution with reduced computational overhead
Actively maintained with community enhancements
Flexibility to adapt to various language processing tasks

Pros:

Excellent generative performance suitable for content creation
Open-source availability ensures transparency and adaptability
Efficient scaling from modest to high-end local hardware
Strong focus on maintaining output quality in an uncensored format

Cons:

May require user intervention to avoid occasional output inconsistencies
Not as extensively documented as some larger ecosystems
Fine-tuning for specific domains might need substantial effort

Pricing:
Free and open-source, relying on community contributions for continuous improvements.

Alternatives:
GPT-J 6B and Falcon LLM are comparable models in terms of performance and uncensored text generation capabilities.

Honest Review/Use Case:
Guanaco is well-suited for content creators, researchers, and developers who require an adaptable, locally deployable model capable of generating creative, uncensored text. It represents a balancing act between output quality and computational efficiency, making it a worthy consideration for a range of AI projects.

9. RWKV

Overview/Description:
RWKV is a unique entry among uncensored LLMs, blending the strengths of RNNs with transformer architectures to provide a model that is both efficient and potent in language generation. Its ability to run locally makes it an appealing option for users seeking an innovative approach to uncensored AI outputs.

Key Features:

Hybrid architecture combining RNN efficiency with transformer power
Minimalist design optimized for local deployments on constrained hardware
Novel approach to long-context handling
Fully open-source with active community collaboration

Pros:

Lower resource usage compared to traditional transformer-based models
Effective at handling long sequences and maintaining context
Flexible and easily integrated into experimental research setups
Unique architecture offers fresh insights into language processing

Cons:

Still maturing, with some rough edges in fine-tuning
May require additional configuration for optimal performance
Community support is growing but not as large as that for older models

Pricing:
Completely free and open-source, with no licensing costs.

Alternatives:
For those who emphasize traditional transformer designs, GPT-J 6B or Falcon LLM are viable alternatives offering established performance metrics.

Honest Review/Use Case:
RWKV is ideally suited for researchers and developers interested in experimenting with novel model architectures that push the boundaries of uncensored language generation. Its efficiency makes it a great option for setups with limited computational resources while still delivering robust performance.

10. OpenAssistant

Overview/Description:
OpenAssistant is a community-driven project developed to mimic and enhance the interactive qualities of modern conversational AIs in an uncensored environment. It is designed to be deployed locally, offering users a powerful alternative to commercial solutions without built-in content filters.

Key Features:

Strong emphasis on dialogue and task-oriented conversation
Community-driven ethics and transparency in development
Modular structure that allows continuous improvement and customization
Built for local installations with comprehensive support scripts

Pros:

Encourages a community-centric approach with regular updates
Highly flexible for various conversational and assistant roles
Robust dialogue capabilities with a focus on natural interaction
Completely uncensored output, ideal for innovative AI projects

Cons:

May require more technical know-how to set up and maintain
The evolving nature of the project can introduce inconsistencies
Documentation might lag behind rapid developmental changes

Pricing:
Free to use with an open-source license supporting local and custom deployments.

Alternatives:
Vicuna and GPT-4All offer similar conversational strengths if you are looking for additional stability or ease-of-setup features.

Honest Review/Use Case:
OpenAssistant is best for community-minded developers and organizations that value transparency, flexibility, and the freedom to experiment without censorship constraints. Its active development and modular design make it an exciting option for tailored conversational AI experiences.

Conclusion

The landscape of uncensored LLMs available for local deployment is as dynamic as it is diverse. From models like GPT-4All and Llama 2 Uncensored—delivering state-of-the-art language understanding—to specialized conversational engines like Vicuna and OpenAssistant, each option brings its own strengths and challenges. Our top 10 list has been crafted to help you navigate these choices, balancing performance, ease of deployment, and the flexibility to bypass conventional content restrictions.

For developers and researchers invested in privacy and customizability, these models represent a significant advancement in local AI deployments. Whether you’re building a sophisticated conversational agent, experimenting with creative content generation, or developing domain-specific applications, the uncensored nature of these LLMs provides freedom and innovation. Keep in mind that while performance is important, matching the right model to your hardware and project requirements is essential. We recommend testing a few models in small-scale trials before committing to a full-scale deployment.

In summary, the future of uncensored LLMs running locally is bright, with each of these models offering something unique for various applications. Choose based on your specific needs—be it cost, performance, or flexibility—and embark on a journey where your ideas are free from the shackles of unnecessary censorship.