New Ministral 3 14B vs Mistral Small 3.2 24B Review

I review data accuracy retrieval and inference speed for the new Ministral 3 14B model vs older Mistral Small 3.2 24B. Older and larger 24B model wins this time. 

 

Ollama and MLX-VLM Accuracy Review (Qwen3-VL and Mistral Small 3.2)

I was running detail tests to compare accuracy for the same models (Qwen3-VL and Mistral Small 3.2) running on Ollama and MLX-VLM (recent 0.3.7 version). MLX-VLM runs faster, but with lower accuracy. The same is valid across different models.

 

Qwen3-VL Accuracy Differences on Ollama vs MLX

I run couple of tests with structured data extraction using newest Qwen3-VL model on Mac Mini M4 Pro with 64GB. I discovered the same Qwen3-VL model with the same level of quantantization performs differently on Ollama vs. MLX. It seems model conversion step is crucial and we must evaluate model performance on different platforms before going to production. 

 

LLM Structured Output for Function Calling with Ollama

I explain how function calling works with LLM. This is often confused concept, LLM doesn't call a function - LLM retuns JSON response with values to be used for function call from your environment. In this example I'm using Sparrow agent, to call a function. 

 

Secure and Private: On-Premise Invoice Processing with LangChain and Ollama RAG

The Ollama desktop tool helps run LLMs locally on your machine. This tutorial explains how I implemented a pipeline with LangChain and Ollama for on-premise invoice processing. Running LLM on-premise provides many advantages in terms of security and privacy. Ollama works similarly to Docker; you can think of it as Docker for LLMs. You can pull and run multiple LLMs. This allows to switch between LLMs without changing RAG pipeline.