Strix Halo Framework Desktop, 32GB vs Mac mini M6, 32GB for local AI
The Framework Desktop, 32GB holds 31 of the 51 current models here, and the Mac mini M6, 32GB holds 23. The Framework Desktop, 32GB costs $30 less. On Qwen3.8 27B, the strongest model both hold, the Framework Desktop, 32GB is about 1.4× faster: 10 tok/s against 6.9, both estimated from memory bandwidth. The Mac mini M6, 32GB pays for itself sooner, in 82 years against 91 years at 500k tokens a day.
| Strix Halo Framework Desktop, 32GB | Mac mini M6, 32GB | |
|---|---|---|
| Price | $1,269 | $1,299 |
| Memory | 32 GB | 32 GB |
| Usable by the GPU | 24 GB | 21 GB |
| Memory bandwidth | 256 GB/s | 170 GB/s |
| Power under load | 133 Wstand-in | 65 Wstand-in |
| Models that fit | 31 | 23 |
| Best model it runs | Qwen3.8 27B | Qwen3.8 27B |
| Speed on that model | 10 tok/s estimated | 6.9 tok/s estimated |
| Pay-back on that model | Pays back in 91 years | Pays back in 82 years |
Neither power figure above is measured on the machine beside it. Both are stand-ins borrowed from the nearest hardware the data does have, so the gap between them is not a difference between these two machines. Each machine's page names the figure it borrows and why. Every pay-back figure on this page prices its electricity from these numbers.
Run the numbers on the Strix Halo Framework Desktop, 32GB · or the Mac mini M6, 32GB
Jump to: The same money, two different machines · How much use it takes to pay back · What the extra memory buys · The assumptions behind both columns
The same money, two different machines
These two cost within $30 of each other: $1,269 for the Framework Desktop, 32GB and $1,299 for the Mac mini M6, 32GB. Framework makes one and Apple the other. Every other head-to-head on this site holds a piece of the hardware equal and asks what the price gap buys. This one holds the price, so the row that usually carries the answer is the row the two machines agree on, and everything under it is what the same money buys twice.
How much use it takes to pay back
Everything above is at 500k tokens a day. Pay-back moves with how much you actually run, so here are both machines on Qwen3.8 27B, the strongest model both hold, at the five levels of use the calculator names. The Mac mini M6, 32GB pays back sooner at every level up to 4M tokens a day. Above that the Strix Halo Framework Desktop, 32GB does.
| A day's use | Strix Halo Framework Desktop, 32GB | Mac mini M6, 32GB |
|---|---|---|
| 50ka few chats a day | 907 years | 821 years |
| 200klight assistant use | 227 years | 205 years |
| 1Ma moderate coding-assistant day | 45 years | 41 years |
| 4Mheavy coding with an agent | 11 years | 10 years |
| 20Magents running most of the day | 3.2 yearsits ceiling | 4.3 yearsits ceiling |
On Qwen3.8 27B neither machine can generate 20M tokens a day: the Strix Halo Framework Desktop, 32GB manages at most 14.3M and the Mac mini M6, 32GB at most 9.47M. Both figures on that row are for the most each can do.
Run the Strix Halo Framework Desktop, 32GB at 20M tokens a day · or the Mac mini M6, 32GB
What the extra memory buys
The Strix Halo Framework Desktop, 32GB holds 8 models the Mac mini M6, 32GB cannot at 32k of context. The strongest of them are what the difference in memory actually buys.
| Model | Weights | Needs at 32k | On the Strix Halo Framework Desktop, 32GB |
|---|---|---|---|
| Nemotron 3.5 Bolt 74B-A9BHaiku-class | 22 GB | 22 GB | 48 tok/s estimated |
| Qwen3.6 35B-A3BHaiku-class | 22 GB | 23 GB | 56 tok/s estimated |
| Gemma 4 31B itHaiku-class | 20 GB | 23 GB | 8.3 tok/s estimated |
| Qwen3-Coder 30B-A3BBelow every hosted tier | 19 GB | 22 GB | 27 tok/s estimated |
| Laguna XS 2.1not yet placed | 20 GB | 22 GB | 44 tok/s estimated |
| Ornith 1.5 35B-A3Bnot yet placed | 22 GB | 22 GB | 57 tok/s estimated |
2 more, on the Strix Halo Framework Desktop, 32GB page.
The extra memory buys context as well. Of the 23 current models both machines hold at 32k, 4 run to a longer window on the Strix Halo Framework Desktop, 32GB: the weights are a fixed size and the KV cache is not, so what the weights leave spare is what a longer context grows into. Qwen3.6 27B reaches 64k there against 32k on the Mac mini M6, 32GB, each the longest window the calculator offers that the machine still holds it at.
The Framework Desktop, 32GB is also head to head with the same box and the bigger chip: 64GB.
The Mac mini M6, 32GB is also head to head with another computer: MacBook Air M5 (13-inch), 16GB. With a graphics card: Radeon AI PRO R9700, 32GB. With the same machine at another memory size: 16GB · 24GB. With the machine it replaced: Mac mini M4, 32GB.
The assumptions behind both columns
Both columns use the same usage: 500k tokens a day at 15:1 input to output, 32k of context, $0.17 per kWh, and today's API prices held flat. Speeds marked estimated are worked out from memory bandwidth rather than measured, and pay-back scales with them. Change any of it in the calculator.
More head to head: everything the Strix Halo Framework Desktop, 32GB runs · everything the Mac mini M6, 32GB runs · every other match-up · the quickest pay-back at each level of use · every model against the frontier