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This week's biggest open-source AI developments: Alibaba's efficient new model outperforms its massive predecessor, Mistral releases a 675B frontier model under permissive license, and local inference adoption accelerates
Forget 700B parameter flagships you can't run. Here are the open-weight models that deliver real performance on consumer hardware - with actual benchmarks.
Alibaba's new 35B model matches Claude Sonnet 4.5 on benchmarks while running locally on an RTX 4090. Here's what you need to know.
Ollama delivers 40% faster inference while llama.cpp finds a permanent home at Hugging Face. Two developments that secure the future of running AI on your own hardware.
The popular local inference tool now installs and configures OpenClaw automatically, giving desktop users access to AI agents running Kimi-K2.5 and GLM-5 with a single command.
Step-by-step guide to building a private document search system that runs entirely on your computer, no cloud services required
A tier-by-tier comparison of the top open-weight LLMs you can run locally, from 8GB laptops to 24GB gaming GPUs to Apple Silicon Macs.
Step-by-step guide to running a private, local AI chatbot that rivals ChatGPT - no subscription, no data collection, no internet required.
Qwen 3.5 offers a 397B MoE flagship and smaller local models under Apache 2.0, but Alibaba's benchmarks need independent testing.
A 3.35B parameter multilingual model outperforms larger competitors on underserved languages - and runs locally on consumer hardware. Privacy-first AI for the rest of the world.
