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How to setup a local coding agent on macOS

ikyle.me

June 12, 2026

9 min read

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67/100

Summary

Gemma 4 26B-A4B and Qwen3.6 35B-A3B can be run locally on macOS using llama.cpp, MTP speculative decoding, and multimodal support. The setup aims to provide a fast and reliable local coding agent to avoid interruptions from internet failures.

Key Takeaways

The local coding agent setup on macOS utilizes Gemma 4 26B-A4B and Qwen3.6 with llama.cpp, achieving usable speeds for coding tasks.
The Gemma 4 model with Multi-Token Prediction (MTP) improved generation speed by approximately 24%, reaching 72.2 tokens per second.
The optimal configuration for MTP on an Apple M1 Max was found to be using 3 draft tokens, balancing speed and performance.
The complete model setup requires about 17 GB of storage, including the main model and MTP draft model.

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Community Sentiment

Mixed

Positives

Using omlx.ai has streamlined the process of downloading and launching multiple models, enhancing the user experience for local AI on macOS.
The responsiveness of the developers behind the local inference tools is commendable, indicating a strong commitment to improving the open-source project.
Running local models can provide privacy and reliability, making them a viable alternative to AI-as-a-Service solutions.

Concerns

Local models often struggle with performance compared to hosted solutions, leading to frustration for users who invest time and resources.
Benchmarking with only 128 tokens is insufficient for evaluating model performance, risking misleading conclusions about speed and efficiency.
There is a lack of focus on the quality of outputs in local AI discussions, with many prioritizing speed over the usefulness of generated content.