These Free Local AI Models Are INSANELY Good

10 free local AI models ranked by what actually runs on your hardware, from gpt-oss-120b to Gemma 3 and Phi-4-reasoning Ten free local AI models ranked not by benchmark hype but by whether your actual machine can run them, from Alibaba's Qwen3-235B-A22B down to OpenAI's gpt-oss-20b and gpt-oss-120b. This is a real hardware-first countdown for anyone searching local ai, open weight models, or ai agents you can self-host without an API bill. Each entry names the real parameter counts, active-parameter sizes, and VRAM requirements: GLM-5's 744B parameters needing terabytes at full precision, Mistral Small 4 folding four model families into one 119B system, Thinking Machines Lab's Inkling-Small waking only 12B of its 276B parameters per word, DeepSeek V4 Flash landing July 31st and running through LM Studio, Meta's Llama 4 Scout with its 10-million-token context window, and Microsoft's Phi-4-reasoning beating far bigger models on a 16GB gaming card via MIT license. The final two are OpenAI's own gpt-oss-20b (16GB, o3-mini-level reasoning) and gpt-oss-120b (near o4-mini parity on a single 80GB GPU, clocked at 30+ tokens/sec on a 128GB Strix Halo mini PC). Along the way it covers why local inference is memory-bandwidth bound, not compute bound, and why an Apple M3 Max with unified memory can beat a faster RTX 4090 that simply can't fit the model. The close breaks down exactly what to download based on how much memory is actually sitting in your machine right now. For anyone tracking ai news, machine learning releases, or the future of ai who wants an actual buyer's guide instead of a leaderboard screenshot, this is the video that tells you which model your hardware can run tonight. Chapters: 0:00 The 16GB Model That Changes Everything 0:25 The Model You'll Never Actually Run 1:54 Free To Take, Impossible To Fit 3:31 One Model To Replace Four, If You Can Host It 4:52 The One Where Size Stopped Mattering 6:27 Newest Doesn't Mean Best, Right? 7:58 Ten Million Tokens Of Memory 9:11 The One You Can Grab Tonight 10:52 The Tiny Model Bullying Giants 12:33 OpenAI Finally Opens Up 13:44 The Big One You Can Actually Own 15:15 So What Should You Download Tools & resources mentioned: - gpt-oss-120b / gpt-oss-20b: https://openai.com/index/introducing-gpt-oss/ - LM Studio: https://lmstudio.ai - Ollama: https://ollama.com - Qwen3-235B-A22B (Alibaba) - GLM-5 (Z.ai) - Mistral Small 4 - Inkling-Small (Thinking Machines Lab) - DeepSeek V4 Flash - Llama 4 Scout (Meta) - Gemma 3 (Google) - Phi-4-reasoning (Microsoft): https://huggingface.co About The Stack The Stack helps you build with AI. Each video takes one tool, model, or workflow and shows how it works in a few focused minutes, with the real benchmarks and real costs. We go deep on Claude Code and Cursor for AI coding, AI agents and MCP servers, the open-source AI tools and GitHub repos most people miss, RAG and vector search, fine-tuning, and running local LLMs on your own machine with Ollama and LM Studio. We compare models like ChatGPT and Claude, test AI automation with Zapier, Make, and n8n, and flag the tools that actually ship. Subscribe for new breakdowns: https://www.youtube.com/@the-stack-ai?sub_confirmation=1 #localai #openweights #aiagents #machinelearning #opensourceai