Ollama vs LM Studio vs vLLM vs llama.cpp: quale scegliere nel 2026?
Four tools, four jobs. Ollama and LM Studio are experience layers, llama.cpp is the engine, and vLLM is a production server. Here’s exactly which one to pick — and when.
Modelli linguistici di grandi dimensioni
Deep dives into large language models, prompt engineering, and AI chatbots
Requisiti di sistema per Ollama nel 2026: quanta RAM e VRAM ti servono davvero
The number-one reason a model fails to run isn’t a bug — it’s memory. Here’s exactly how much RAM and VRAM each Ollama model size needs, and a formula to know before you download.
Come installare Ollama nel 2026: Mac, Windows e Linux (guida passo passo)
Installing Ollama takes about two minutes on any OS. Here are the exact steps for Mac, Windows, and Linux, plus how to run your first model and fix the errors people actually hit.
I migliori modelli linguistici locali da eseguire su Ollama nel 2026 (ordinati per caso d’uso)
Ollama can run 100+ models, but you only need a handful. Here are the best local LLMs in 2026 ranked by what you’re actually trying to do — and the VRAM each one needs.
Il miglior LLM locale per la programmazione nel 2026 (testato su compiti reali)
A local coding model means your code never leaves your machine. Here are the best ones in 2026 — ranked by SWE-bench, hardware needs, and how they handle real refactors.
Modelli linguistici di grandi dimensioni open source vs. closed source nel 2026: un confronto completo
Should you build on an open model like Llama or a closed API like GPT? This guide compares open and closed LLMs on the things that actually decide the choice.
Allucinazioni nei modelli linguistici di grandi dimensioni nel 2026: perché si verificano e come evitarle
Why do AI models confidently make things up? This guide explains what causes LLM hallucinations, the different types, and the proven techniques to reduce them.
Ingegneria dei prompt nel 2026: 12 tecniche che funzionano davvero
Prompt engineering isn’t magic words — it’s a set of repeatable techniques. Here are the 12 that genuinely improve AI output in 2026, with examples and when to use each.
RAG spiegato: come funziona la generazione con recupero aumentato nel 2026
RAG is the technique behind almost every AI system that answers questions from your own documents. This guide explains how retrieval-augmented generation works — clearly, and without the jargon.
Fine-tuning vs RAG nel 2026: quando utilizzare l’uno o l’altro (e quando entrambi)
Fine-tuning and RAG are the two ways to customize a language model — and they solve different problems. This guide gives you a clear framework for choosing the right one.
