# Problems with Local LLMs

> Source: <https://www.dotnetperls.com/2026_10_3_problems-local-llms>
> Published: 2026-10-03 07:00:00+00:00

I am **optimistic** about the potential of running **large language models** on **local** systems. Local LLMs have many benefits, and I run them frequently, mostly for chat or information lookups.

But for more complex or difficult tasks, like generating **complicated Rust functions**, I feel that **cloud-based** LLMs are a **better deal**. In trying to generate code on my local PC, I was successful but it took up to 30 minutes or an hour of 100% CPU and 100% GPU work.

I estimated my **cost** in **electricity** and it came out to about $0.02 to $0.04 for the generations. This might make sense in some cases, but running the same generations on **OpenRouter** with a modern Flash model (Gemini 3.8 Flash, GLM 5.3 Flash, Claude Sonnet 5.5) is about the **same price**, and usually finishes within **2 minutes**.

So **cloud-based AI** is both **faster**, **cheaper**, and also **higher quality** (based on a larger model). It does mean that your data is no longer "private" and if you are doing something questionable a model might refuse to generate text. There are drawbacks with both local and cloud, but often cloud is a better deal for code generation.