How I'm using local models from real-world coding
Summary
The author shares their experience using local AI models for real-world coding tasks.
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Making small local models actually useful for coding
The author created an open-source hybrid tool called Local Coding Agent to make small local models effective for coding tasks on consumer GPUs by using a cloud model for planning and local models for isolated execution, with error handling and testing features.
Running local models is good now
The author reports that running local AI models has become surprisingly good, with recent releases like GPT-OSS and Gemma 4 enabling agentic coding locally at about 75% accuracy of frontier models, a significant improvement from just months ago.
Local models went from mostly useless to actually useful really fast. What changed?
The post notes that local AI models have become significantly more useful over the past year, moving from toys to practical tools for coding and workflows, despite still lagging behind closed models for complex tasks.
@TheAhmadOsman: Local AI is the future Learning how to run Opensource models (Inference), how to evaluate them systematically (Evals), …
A tweet from @TheAhmadOsman emphasizes that local AI is the future and recommends learning skills like running open-source models, conducting evals, and customizing models through fine-tuning.
@vboykis: new post: how I develop recently using local models. the tooling is now good enough to do agentic workflows and everyon…
Vicki Boykis shares her experience using local AI models for development, noting that recent releases like Gemma 4 have made agentic workflows feasible locally with about 75% accuracy of frontier models.