What is your actual local LLM stack right now?

Reddit r/LocalLLaMA / 4/21/2026

💬 OpinionIdeas & Deep AnalysisTools & Practical Usage

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Key Points

The author argues that day-to-day differences in a local LLM setup often come more from the surrounding system configuration than from the model itself.
Key components called out include the backend and frontend choices, whether RAG is used, quantization settings, GPU offloading, context configuration, and prompt formatting.
The post notes that many local stacks look impressive in screenshots but become frustrating after a few days of real use.
Instead of chasing benchmark wins, the author asks what people actually run daily and which parts of their stack turned out to matter more than expected.

I keep trying new models, but the bigger difference usually comes from the setup around them, not the model itself.

Backend
frontend
RAG or no RAG
quant choice
GPU offload
context settings
prompt format
whatever janky glue holds it together

A lot of local setups look great in screenshots, then feel annoying in real use after two days.

Right now I am more interested in stacks that people actually stick with than benchmark wins.

What are you running daily, and what part of your setup ended up mattering way more than expected?

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