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Does anyone have decent intuitions or hard clues on how big models like GPT-5.4, Gemini 3.1, and Opus 4.6 actually are, and how they compare to the best open models like GLM-5?

Are they all roughly in the same range now (for example around 1T params, maybe MoE), or are the closed models still much bigger?

Also curious about “pro” versions like GPT-5.4 Pro - is that likely a different model, or mostly the same model with more inference-time compute / longer reasoning / better orchestration?

Hi HN,

I have a 3D printer but I’m pretty bad at CAD. Using LLMs for coding has worked extremely well for me, so I’ve been trying to apply a similar workflow to CAD/modeling.

For simple functional parts (jigs, brackets, adapters, small fixtures), I can use an LLM + OpenSCAD in a loop: it writes OpenSCAD, I compile/render, I render a few views, the LLM “looks” at the images, and we iterate until it looks right. This is already helpful, but it hits a ceiling quickly. Anything beyond simple parametric primitives becomes painful (complex geometry, precise interfaces, assemblies, tolerances/fit, etc.).

I’m curious about two things. First: any intuition on when we’ll be able to generate models at a professional level, comparable to what LLMs can do for coding right now? Second: what will that workflow look like in practice? Will it stay mostly parametric (OpenSCAD / constraints), or will it look more like an interactive “CAD copilot” inside tools like SolidWorks/Fusion that can edit the feature tree via screenshot + click style interaction? Or something else entirely, like text turning into a full feature history with constraints and checks.

If you’re already doing this, what tools/workflows are giving the best results today, and where do they fail?

Thanks!