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RTX 4090 24GB vs Mac 128GB unified for local LLMs
| accelerator | usable | models fit (of 46) | price anchor | cheapest rental ≥ size |
|---|---|---|---|---|
| RTX 4090 24GB | 24 GiB | 22 | $1,599 launch MSRP (Wikipedia GeForce RTX 40 series (launch 2022-10-12), retrieved 2026-10-20) | RunPod RTX 5090 32GB @ $0.99/h |
| Mac 128GB unified | 96.0 GiB | 31 | MSRP not sourced — verify yourself | RunPod H200 141GB @ $4.59/h |
VRAM: modelvram.com open dataset (CC BY 4.0 / MIT, retrieved 2026-10-20), best sensible quant, 8k context. Rentals: modelvram.com public table (self-stated check 2026-09-29, retrieved 2026-10-20). Partial re-verify 2026-10-20: Lambda A100 40GB $1.99/h CONFIRMED on lambda.ai/pricing (fetched directly); Lambda H100 rows ambiguous on-page ($3.99 vs $4.09 configs) → not adopted; RunPod & Vast pricing pages are JS-rendered, no extractable static figures — verify rates visually before spending.
Only RTX 4090 24GB fits (0)
none
Only Mac 128GB unified fits (9)
AliceAI Foundation 80B-A3B (MoE)Kolibri-1 (MoE)Llama 3.1 70BMistral Medium 3.5 128BNemotron 3 Super 120B-A12B (MoE)Qwen3-Coder-Next (80B MoE)Qwen3.5 122B-A10B (MoE)Qwen3.8 Flash Next (180B MoE)gpt-oss-120b
FAQ
Which is better for local LLM: RTX 4090 24GB or Mac 128GB unified?
It depends on which models you want: RTX 4090 24GB fits 22 of 46 dataset models, Mac 128GB unified fits 31; the 'only one fits' lists above are usually the deciding factor. Dataset: modelvram.com CC BY 4.0, retrieved 2026-10-20.
Is Mac 128GB unified worth the extra money over RTX 4090 24GB?
We publish no street prices (no dated source → user-entered). Take both cards' street prices into the break-even calculator against cited rental rates and your usage.
Do these numbers include KV cache?
Yes — 'total @8k' includes KV cache + runtime overhead per dataset methodology; long contexts extrapolate linearly (see method).
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