Technical / Comparison
NobodyWho vs RunAnywhere: On-Device Inference Engine Comparison
NobodyWho vs RunAnywhere compared on performance, features, platform support and licensing.
Updates and technical notes from the NobodyWho team.
NobodyWho vs RunAnywhere compared on performance, features, platform support and licensing.
Everyone is talking about Jev - here it is in 25 lines of Python.
Mobile memory warnings and handling them in Rust.
How many worker threads should you use for CPU inference? Not all of them.
So how exactly do you make your LLM output a JSON? What happens under the hood? And how do you make it reliable and fast? Diving into constrained sampling.
What extra stuff is needed to properly run a language model? Besides the weights of a language model, what is the gguf metadata that we need to parse and use?