Running local models is good now

2026-06-16 | original

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Why This Matters

The advancements in local models now offer near-parity with cloud-based models in terms of speed and accuracy, making them more viable for developers and consumers seeking privacy, customization, and reduced latency. This shift could significantly impact how AI tools are integrated into everyday workflows, fostering greater independence from cloud services.

Key Takeaways

Local models now perform at about 75% the accuracy and speed of frontier models, enabling more complex tasks locally.
Recent releases like Google’s Gemma 4 have made local AI more practical for coding, proofreading, and research automation.
The improved capabilities of local models support privacy-focused, customizable AI workflows without relying on cloud-based APIs.

Jun 15 2026

I’ve been working with local models since they came out, and finally, they’re surprisingly good now.

I have a 2022 M2 Mac with 64 GB RAM and 1TB storage and I’ve used

across a lot of different system setups like

raw llama.cpp with Open WebUI

llama-cpp-python

Ollama

llamafiles and

LM Studio

Where are local models now?

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Explore topics: llama.cpp gpt-oss lm studio google gemma ollama