Mac Studio vs RTX 4090: which local AI box?

The capacity story

Apple’s unified memory is usable model memory — macOS lets the GPU address most of it, so a 64GB Studio comfortably loads 70B models at Q4, and 128GB configs reach gpt-oss-120b-class MoE models or 70B at higher quants. No consumer NVIDIA card can hold these at any price; you would need multiple GPUs or workstation silicon.

The speed story

The 4090 processes prompts several times faster — the gap that matters most for RAG and long-context work — and generates faster on anything that fits in 24GB. The M2 Ultra’s roughly 800 GB/s of memory bandwidth keeps generation speed respectable once the model is loaded; it is the long-prompt prefill where Macs feel slow.

The MLX ecosystem (plus Ollama and llama.cpp Metal backends) has matured quickly and covers the mainstream open models well.

Total cost and practicality

The 4090 price in the table is a bare card — add a capable PSU, case, CPU, and RAM if you are not upgrading an existing rig. The Mac Studio is a complete, silent computer that idles near 10W and peaks around 300W; a 4090 rig under load can pull 600W+ with fans to match.

Image and video generation remains the 4090’s uncontested territory — CUDA tooling for Stable Diffusion and Flux is far ahead of anything on Metal.

Which Mac config to buy

M2 Ultra 64GB is the sweet spot: Ultra-class 800 GB/s bandwidth at the lowest big-memory price. M2 Max 64GB is cheaper but has half the bandwidth — noticeably slower generation on large models. Go 128GB only if you specifically want 100B-class models; see the alternate configs table below for live prices, and the Mac mini M4 Pro 48GB as the budget path to 30B-class models.

FAQ

Can a Mac Studio run 70B models?

Yes. A 64GB Mac Studio runs 70B models at Q4 through Ollama, LM Studio, or MLX, with usable generation speed on Ultra-class chips. 128GB configs add headroom for higher quants and long context.

Is a Mac Studio faster than an RTX 4090 for LLMs?

No — when the model fits in the 4090’s 24GB, the 4090 wins clearly, especially on prompt processing. The Mac wins by running models that do not fit in 24GB at all.

What about a Mac mini instead of a Studio?

A Mac mini M4 Pro with 48GB runs 30B-class models well and is the cheapest Apple path into local AI, but bandwidth limits it on bigger models. For 70B and up you want a Studio with an Ultra chip.