Local 27B and 30B models are now genuinely useful for surgical coding on a 16 GB GPU -- and still so much slower and costlier per token that I rarely boot them.
Read the post →Pi starts at 1,500 tokens of context where my OpenCode setup needs 13,800. A week of extensions later I had every OpenCode feature -- and I dropped OpenCode for Pi.
Read the post →A $60 Android tablet in split screen replaced my macro pad and keeps Discord visible while I game. The buttons work even when my PC is locked or off.
Read the post →Ava turns an old Android tablet into a voice satellite, Qwen 3.5 4B runs on a $56 GPU, and the whole local Home Assistant voice assistant finally works -- wake word included.
Read the post →$10 of OpenCode Go buys $60 of tokens at Zen prices. Twelve days of using nothing else burned 22% of the month -- and the models and limits are the best I have tried.
Read the post →A month of GPT-5.4 through Codex and OpenCode: faster and smarter than every budget plan I run, but not three to seven times better when you are a light user.
Read the post →The Home Assistant Vibecode MCP plus OpenCode turned my espresso machine, sleep tracking, and LLM quota gauges into dashboard cards I never had to write by hand.
Read the post →Chutes, NanoGPT, and Z.ai all switched to token-based quotas. That is good news: match the model to the task, trim your context, and a cheap plan goes much further.
Read the post →Royal Kludge's hall-effect boards deliver 90% of the Keychron K2 HE experience for 60% of the price. What separates them is mostly sound, not switches or speed.
Read the post →Three budget coding plans, one light user: what $3 and $20 a month actually buy at Chutes, Z.ai, and Synthetic, and why the quota math is less obvious than the price tags.
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