LLaMA Factory
Fine-tune large language models with minimal resources.
Open-weight models, frameworks, and tools you can run locally or self-host for privacy and customisation.
Open-source AI tools let you run models and frameworks on your own hardware or servers, giving you full control over your data and customization options. These tools are used by developers, researchers, and organizations that need privacy, cost control, or the ability to modify AI behavior. They solve the problems of vendor lock-in, data privacy concerns, and the need for specialized configurations.
Privacy-focused enterprises
Compliance-heavy organizations use self-hosted open-source AI to keep sensitive data on-premises and avoid cloud vendor dependencies.
Researchers developing models
Academic and research teams use open frameworks to experiment with custom architectures, train on proprietary datasets, and publish reproducible work.
Edge device applications
Embedded systems engineers and IoT developers deploy lightweight open models directly on phones, cameras, and IoT devices for offline inference.
Compare total cost of ownership
Look beyond the free software cost to include hardware, hosting, maintenance, and developer time needed to deploy and manage the solution yourself.
Evaluate ease of local setup
Check documentation, community support, and available guides for installation on your preferred hardware or infrastructure, especially if you lack DevOps expertise.
Check integration ecosystem
Verify what existing tools, libraries, and platforms the framework or model works with, and whether it supports common deployment targets like Docker or Kubernetes.
Assess model performance fit
Compare model size, speed, accuracy, and memory requirements against your actual use case—smaller models run faster locally but may sacrifice quality.
Fine-tune large language models with minimal resources.
Open-source framework for building real-time conversational AI agents
Open-weight multimodal model from Meta for text, images, and audio.
Open-weight 1 trillion parameter multimodal model for coding and security tasks.
Open-source generative AI model for images
Open-weight AI safety research partnership for model training and monitoring.
Open training framework for building and scaling large mixture-of-experts models.
Local semantic search and RAG system for your documents.
AI model training technique to remove specific information from language models
Train coding models to generate watercolor paintings using reinforcement learning.
Browse, share, and download community-created AI art models.
Open-weight AI model optimized to run efficiently on Mac computers.
Open-source framework for training AI agents with reinforcement learning.
Open-source RAG engine with document processing and agent capabilities.
Open-source AI that converts natural language questions into SQL queries.
Benchmarks open-source AI agents on reasoning and planning tasks.
Decentralized hosting for AI models and demos on blockchain
Pioneering AI research lab advancing deep learning and AI
AI agent framework for building multi-platform chatbots.
Open-source framework for building and customizing generative AI models.
Constrained decoding for structured LLM outputs
Open-source vision model that grounds language to visual regions for precise image understanding
Open 501B parameter model you can customize and deploy yourself.
Open-source multimodal AI model for image and text understanding
Fine-tune large language models with minimal resources.
Open-source framework for building real-time conversational AI agents
Open-weight multimodal model from Meta for text, images, and audio.
Open-weight 1 trillion parameter multimodal model for coding and security tasks.
Open-source generative AI model for images
Open-weight AI safety research partnership for model training and monitoring.
Open training framework for building and scaling large mixture-of-experts models.
Local semantic search and RAG system for your documents.
AI model training technique to remove specific information from language models
Train coding models to generate watercolor paintings using reinforcement learning.
Browse, share, and download community-created AI art models.
Open-weight AI model optimized to run efficiently on Mac computers.
Open-source framework for training AI agents with reinforcement learning.
Open-source RAG engine with document processing and agent capabilities.
Open-source AI that converts natural language questions into SQL queries.
Benchmarks open-source AI agents on reasoning and planning tasks.
Decentralized hosting for AI models and demos on blockchain
Pioneering AI research lab advancing deep learning and AI
AI agent framework for building multi-platform chatbots.
Open-source framework for building and customizing generative AI models.
Constrained decoding for structured LLM outputs
Open-source vision model that grounds language to visual regions for precise image understanding
Open 501B parameter model you can customize and deploy yourself.
Open-source multimodal AI model for image and text understanding