01Tag · AI models

#AI models

7 posts

AI models: how to match a model to the task (not to its name), when a smaller one is enough, and how to count cost. Profiles, not 'general intelligence'.

AI Infrastructure01/06/2026

DeepSeek vs Mistral vs Qwen: which AI model for what

Three leading model families, three distinct profiles. Head-to-head based on measured parameters - and when to choose which.

AI Infrastructure01/06/2026

How to choose an AI model for the task (not the hype)

There’s no single best model. There’s the right model for the job - chosen by measurement, not by name. A practical guide to selection.

AI Infrastructure01/06/2026

When fine-tuning makes sense (and when RAG is enough)

When fine-tuning makes sense: selection criteria, costs, and pitfalls. When RAG solves the problem cheaper, and when model training is the only way.

AI Infrastructure01/06/2026

Small specialized AI model vs large LLM

Small AI model vs large LLM: when a specialized 7B outperforms a general GPT-4-class model, the cost difference, and how to choose correctly for your business.

AI Infrastructure01/06/2026

Reasoning vs instruct models: when AI should think

Reasoning models excel at tough decisions - but they're slow, expensive, and empty when forced into simple tasks. When thinking pays off.

AI Agents01/06/2026

RAG vs fine-tuning: how to give a model your company’s knowledge

Two paths to a model that knows your business. When RAG is enough, when fine-tuning is needed - and why RAG is usually the answer.

AI Agents01/06/2026

Vision AI in business: photos and documents a model understands

A model that sees. Vision AI reads documents, describes photos, and extracts data from images - where it actually saves hours.

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