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Mac 64GB unified vs A100 80GB for local LLMs
| accelerator | usable | models fit (of 46) | price anchor | cheapest rental ≥ size |
|---|---|---|---|---|
| Mac 64GB unified | 48.0 GiB | 26 | MSRP not sourced — verify yourself | RunPod A100 80GB @ $1.59/h |
| A100 80GB | 80 GiB | 31 | MSRP not sourced — verify yourself | RunPod A100 80GB @ $1.59/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 Mac 64GB unified fits (0)
none
Only A100 80GB fits (5)
Mistral Medium 3.5 128BNemotron 3 Super 120B-A12B (MoE)Qwen3.5 122B-A10B (MoE)Qwen3.8 Flash Next (180B MoE)gpt-oss-120b
FAQ
Which is better for local LLM: Mac 64GB unified or A100 80GB?
It depends on which models you want: Mac 64GB unified fits 26 of 46 dataset models, A100 80GB 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 A100 80GB worth the extra money over Mac 64GB unified?
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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