Gemma-4 26B-A4B runs well on M5 MacBook

Local LLM coding is crossing the line from novelty to practical tool here, but the model still sounds like a strong assistant rather than a drop-in replacement for frontier cloud agents.

• –The standout metric is prompt throughput: fast prefill matters more than raw generation speed when you’re doing repo-scale agent workflows.
• –Low-power, low-heat operation changes the actual UX; a laptop that can run an agent without spinning fans is a different class of machine for mobile dev work.
• –The report is still a reminder that open models lag on autonomy and instruction quality, even when the hardware is finally good enough to support them.
• –For developers, the interesting shift is not “can local models code?” but “can they stay useful long enough, cheaply enough, and quietly enough to fit real work sessions?”
• –Opencode looks like a decent stress test for this trend because it exposes whether local inference can handle multi-step, tool-using behavior instead of just chat.