Mac mini M5 Pro, 24GB vs Strix Halo Corsair AI Workstation 300, 64GB for local AI
The Corsair AI Workstation 300, 64GB holds 27 of the 39 open models here, and the Mac mini M5 Pro, 24GB holds 13. The Mac mini M5 Pro, 24GB costs $1 less. On Gemma 4 12B, the strongest model both hold, the Mac mini M5 Pro, 24GB is about 1.2× faster: 29 tok/s against 24, both estimated from memory bandwidth. The Corsair AI Workstation 300, 64GB pays for itself sooner, in 22 years against 135 years at 500k tokens a day, though that is each machine on its own strongest model rather than on the same one.
| Mac mini M5 Pro, 24GB | Strix Halo Corsair AI Workstation 300, 64GB | |
|---|---|---|
| Price | $1,699 | $1,700 |
| Memory | 24 GB | 64 GB |
| Usable by the GPU | 16 GB | 48 GB |
| Memory bandwidth | 307 GB/s | 256 GB/s |
| Power under load | 140 Wstand-in | 133 Wstand-in |
| Models that fit | 13 | 27 |
| Best model it runs | Gemma 4 12B | Qwen3.8 27B |
| Speed on that model | 29 tok/s estimatedGemma 4 12B | 10 tok/s estimatedQwen3.8 27B |
| Pay-back on that model | Pays back in 135 years | Pays back in 22 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 Mac mini M5 Pro, 24GB · or the Strix Halo Corsair AI Workstation 300, 64GB
The same money, two different machines
These two cost within $1 of each other: $1,699 for the Mac mini M5 Pro, 24GB and $1,700 for the Corsair AI Workstation 300, 64GB. Apple makes one and Corsair 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.
Side by side on Gemma 4 12B
The table above gives each machine the strongest model it can hold, and those are not the same model, so the two speeds in it are not a race. Gemma 4 12B is the strongest model both machines hold, so this is the pair running the same work.
| Mac mini M5 Pro, 24GB | Strix Halo Corsair AI Workstation 300, 64GB | |
|---|---|---|
| Speed | 29 tok/s estimated | 24 tok/s estimated |
| Pay-back | Pays back in 135 years | Pays back in 139 years |
Run Gemma 4 12B on the Mac mini M5 Pro, 24GB · or on the Strix Halo Corsair AI Workstation 300, 64GB
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 the same model, at the five levels of use the calculator names. The Mac mini M5 Pro, 24GB pays back sooner at every level of use, so this is not a choice that turns on how hard you work it.
| A day's use | Mac mini M5 Pro, 24GB | Strix Halo Corsair AI Workstation 300, 64GB |
|---|---|---|
| 50ka few chats a day | 1,353 years | 1,394 years |
| 200klight assistant use | 338 years | 348 years |
| 1Ma moderate coding-assistant day | 68 years | 70 years |
| 4Mheavy coding with an agent | 17 years | 17 years |
| 20Magents running most of the day | 3.4 years | 3.5 years |
Run the Mac mini M5 Pro, 24GB at 20M tokens a day · or the Strix Halo Corsair AI Workstation 300, 64GB
What the extra memory buys
The Strix Halo Corsair AI Workstation 300, 64GB holds 14 models the Mac mini M5 Pro, 24GB 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 Corsair AI Workstation 300, 64GB |
|---|---|---|---|
| Qwen3.8 27BSonnet-class | 16 GB | 19 GB | 10 tok/s estimated |
| Qwen3.6 27BHaiku-class | 17 GB | 19 GB | 10 tok/s estimated |
| Qwen3.6 35B-A3BHaiku-class | 22 GB | 23 GB | 56 tok/s estimated |
| Muse Glimmer 30BHaiku-class | 17 GB | 18 GB | 11 tok/s estimated |
| Gemma 4 26B-A4BHaiku-class | 17 GB | 18 GB | 41 tok/s estimated |
| Gemma 4 31B itHaiku-class | 20 GB | 26 GB | 7.4 tok/s estimated |
8 more, on the Strix Halo Corsair AI Workstation 300, 64GB page.
The extra memory buys context as well. Of the 13 models both machines hold at 32k, 3 run to a longer window on the Strix Halo Corsair AI Workstation 300, 64GB: 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. Granite 4.2 8B reaches 128k there against 32k on the Mac mini M5 Pro, 24GB, each the longest window the calculator offers that the machine still holds it at.
The Mac mini M5 Pro, 24GB is also head to head with another computer: Mac Studio M5 Max, 128GB · DGX Spark, 128GB · GMKtec EVO-X2, 128GB · MacBook Air M5 (15-inch), 16GB · MacBook Pro M5 Pro (16-inch), 64GB. With a graphics card: RTX PRO 6000 Blackwell, 96GB · Radeon AI PRO R9700, 32GB. With the same machine at another memory size: 48GB · 64GB. With the machine it replaced: Mac mini M4 Pro, 24GB.
The Corsair AI Workstation 300, 64GB is also head to head with the same box and the bigger chip: 128GB.
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 Mac mini M5 Pro, 24GB runs · everything the Strix Halo Corsair AI Workstation 300, 64GB runs · every other match-up · the quickest pay-back at each level of use · every model against the frontier