This Local AI Engine Claims 2x Faster Than llama.cpp

Magnitude is a new open-source local LLM inference engine that claims it runs models up to 2x faster than llama.cpp on a Mac by tuning its kernels to your exact hardware. In this video I explain why local models run slower than they should, how per-device kernel tuning works, and the difference between prefill and decode speed. Then I install it on Apple Silicon, race it against llama.cpp on the same model. 🔗 Relevant Links Magnitude Repo - https://github.com/magnitudedev/magni... Magnitude Docs - https://docs.magnitude.dev/ ❤️ More about us Radically better observability stack: https://betterstack.com/ Written tutorials: https://betterstack.com/community/ Example projects: https://github.com/BetterStackHQ 📱 Socials Twitter:   / betterstackhq   Instagram:   / betterstackhq   TikTok:   / betterstack   LinkedIn:   / betterstack   📌 Chapters: 0:00 Magnitude Claims 2x Faster Than llama.cpp 0:35 Why Local AI Models Can Run Slower Than Expected 0:58 How Magnitude Tunes Kernels for Your Hardware 1:50 Installing Magnitude and Downloading a Local Model 2:30 Magnitude vs llama.cpp Speed Test 2:53 Connect Claude Code on a Local Model 3:25 How Magnitude’s Inference Engine Works 4:03 Magnitude vs llama.cpp, Ollama, MLX, vLLM and SGLang 4:35 Is Magnitude Really 2x Faster? 5:40 Independent Magnitude Benchmarks 6:10 Magnitude’s Current Limitations 6:45 macOS Setup Issues and Model Storage 7:06 Should You Install Magnitude?