Reading path

I'm comparing the stack options

Hardware, model, and tooling head-to-heads. No vendor numbers passed as facts: operator-reproduced where I have the data, vendor-labelled where I do not.

5 articles, in reading order

  1. The Engineering Honesty Manifesto

    The rule that gates every number in the comparisons below: I do not quote a figure I have not measured, or I label it as a vendor claim.

  2. DGX Spark vs Apple Mac Studio: Which Wins for Local LLMs?

    The desk-scale hardware split: GB10 unified memory versus Apple's unified memory, two different stories about what 'desktop AI' means.

  3. Mistral Small 4 vs Qwen 3.6 vs GLM-5.1 on a Single DGX Spark

    The model layer on GB10: three serious self-hostable options, the throughput each one delivers, and the vision-versus-quant trade I lost.

  4. Coding Assistants on a Sovereign Stack: Claude Code, opencode, Aider, OpenClaw (and why Vibe got retired)

    The coding-agent layer: four tools that occupy the same slot, why I kept two and dropped two.

  5. What 'Sovereign' Actually Means in 2026 (And What It Doesn't)

    Close the loop: the six-dimension test for whether any of these stacks actually delivers sovereignty, not just the marketing version.

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