Insights, Releases & Local AI Guides
Stay up to date with new Loco releases, local inference benchmarks, architecture deep-dives, and tutorials for running offline AI models.
GPT OSS: The Complete Guide to OpenAI's Open-Weight AI Models
Explore GPT OSS, OpenAI's open-weight AI model family, including gpt-oss-120b, gpt-oss-20b and the specialized gpt-oss-safeguard models. Learn why OpenAI released open-weight models, how the Mixture-of-Experts architecture works, what makes GPT OSS different from traditional cloud AI, how much hardware you need to run it locally, how quantization changes the requirements, what the models can do, and why GPT OSS is one of the most important developments in local AI.
Phi: The Complete Guide to Microsoft's Phi AI Models and Phi-4
Explore the history of Microsoft's Phi AI models, from Phi-1 and Phi-2 to Phi-3, Phi-3.5, Phi-4, Phi-4-mini and Phi-4-multimodal. Learn why Phi became one of the most important small language model families, how Microsoft uses synthetic data to achieve surprising performance from compact models, what makes Phi-4 different, how Phi Silica brings AI directly onto Windows devices, and which Phi models are best for local AI.
Kimi: The Complete Guide to Moonshot AI's Kimi Models and Kimi K3
Explore the history of Moonshot AI and the Kimi model family, from the original Kimi chatbot and long-context breakthroughs to Kimi K2, K2.5, K2.6, K2.7 Code, and the enormous new Kimi K3. Learn how Kimi's Mixture-of-Experts architecture works, what makes Kimi K3 different, how Agent Swarm works, what hardware is required to run Kimi locally, how quantization changes the equation, and why Moonshot AI is pushing open-weight AI toward increasingly autonomous systems.
GLM: The Complete Guide to Z.ai's GLM AI Models and GLM-5.3
Explore the history of GLM and Z.ai, from Tsinghua University research and GLM-130B to ChatGLM, GLM-4, GLM-4.5, GLM-5, GLM-5.3, and the new GLM-5.3-Flash. Learn how GLM evolved, how its Mixture-of-Experts architecture works, what makes its latest models powerful, which GLM models can run locally, what hardware they require, and where Z.ai is taking the GLM family next.
Mistral: The Complete Guide to Mistral AI Models and Mistral Large 4
Explore the history of Mistral AI, from its founding in France and the original Mistral 7B to Mixtral, Mistral Large 3, Mistral Small 4, and the new Mistral Large 4. Learn about Mistral's model families, architectures, local AI options, hardware requirements, licensing, and the future of open-weight AI.
Llama: The Complete Guide to Meta's Llama AI Models and Llama 4
Explore the history of Meta's Llama AI models, from the original LLaMA to Llama 2, Llama 3, and the multimodal Llama 4 generation. Learn about Scout, Maverick, MoE architecture, context windows, local hardware requirements, licensing, quantization, and what could come next.
Gemma: The Complete Guide to Google’s Gemma AI Models and Gemma 4
Explore the history of Google's Gemma AI models, from the original Gemma to Gemma 4. Learn about Gemma 4 31B, 26B A4B, 12B Unified, E4B and E2B, multimodal capabilities, reasoning, local hardware requirements, quantization, QAT, and which Gemma model is best for your PC.
DeepSeek: The Complete Guide to DeepSeek AI Models and DeepSeek V4.1
Discover the story behind DeepSeek, from its origins in quantitative finance to the breakthrough V3 and R1 models and the latest DeepSeek V4.1 Flash. Explore its architecture, reasoning capabilities, model variants, local AI potential, hardware requirements, and what comes next.
Qwen: The Complete Guide to Qwen AI Models and Qwen3.8
Explore the history of Qwen, Alibaba's AI model family, and the latest Qwen3.8 generation. Learn about Qwen3.8-27B, Qwen3.8-Max, Flash-Next, model variants, local hardware requirements, quantization, capabilities, and what we know about Qwen4.
Local AI for Developers: Build Software With AI on Your Own Computer
Discover how developers can use local AI for coding, debugging, documentation, research, automation, and building private AI-powered applications directly on their own computers.
How Private Is Local AI? Understanding AI Data Privacy
How private is local AI? Learn how running AI on your own computer can help keep prompts and sensitive information under your control, and what you still need to do to stay secure.
Local AI vs Cloud AI for Businesses: Which Is Better?
Compare local AI and cloud AI for business use, including privacy, cost, performance, scalability, security, and how to choose the right approach for your organization.
Can You Run AI Without an Internet Connection?
Can AI work without the internet? Learn how local AI works offline, what you need to run AI without an internet connection, and what features still require online access.
What Are GGUF Models? A Beginner’s Guide to Local AI Model Files
Learn what GGUF models are, why they are widely used for local AI, how quantization affects model size and performance, and how to choose the right model for your computer.
How Much RAM Do You Need for Local AI?
How much RAM do you actually need to run AI locally? Learn how RAM affects local AI performance and what you can realistically run with 8 GB, 16 GB, 32 GB, and 64 GB of memory.
The Best Small AI Models for Running AI Locally
Discover why small AI models are becoming so useful for local AI, how model size affects speed and intelligence, and how to choose the right model for your computer.
What Is Local AI? A Beginner’s Guide
Discover what local AI is, how it works, why people are running AI on their own computers, and what you need to get started.
Local AI vs Cloud AI: What’s the Difference?
Learn the differences between local AI and cloud AI, including privacy, cost, hardware, internet access, performance, and which approach is right for you.