AI models explained: Mistral Large 4, the diffusion model Mercury 2, Jev that chooses instead of writes, and which model to run on your own laptop.
Not every language model works the same way, and the difference decides what you use it for. This topic explains per model how it works, what it costs and what the maker's numbers do and do not tell you.
Mercury 2 doesn't write word by word but refines a whole answer at once; according to its maker it reaches more than 1,000 tokens per second that way. Jev from TypeSafe writes no text at all, but picks from a list and gives a probability with it: read about the model itself and about the principle, with PHP examples. Mistral Large 4 is the first European open-weight model with a trillion parameters, and the article also says what "open" doesn't mean there yet.
If you want to run a model on your own computer, start with Which AI model can you run on your own laptop?, with speeds measured on a 16 GB laptop and a step-by-step plan for Ollama.
Which AI model can you run locally on an ordinary 16 GB laptop? Qwen3.5 and Gemma 4 compared, with measured speeds, a step-by-step Ollama setup, tasks to start with and the two settings that make the most difference.
Mistral Large 4 has been on Hugging Face since 29 October: a trillion parameters, 610 GB at 4 bits. What the licence allows, what it costs, what hardware you need and how it scores against the open and closed top.
Jev does not write text; it answers multiple-choice questions with a probability for each answer. The principle in plain language, with PHP examples you can copy, up to Claude and Jev working together.
Jev by TypeSafe AI writes no text: it picks from your list and attaches probabilities. What independent tests measure, what a decision costs, and when plain code or a trained classifier is the better choice.
Inception's Mercury 2 doesn't write word by word; it refines a whole answer at once. How that works, how fast it is and where it makes a difference.