Strix Halo GMKtec EVO-X2, 128GB vs MacBook Pro M5 Pro (16-inch), 64GB for local AI
The GMKtec EVO-X2, 128GB holds 39 of the 48 current models here, and the MacBook Pro M5 Pro (16-inch), 64GB holds 32. The GMKtec EVO-X2, 128GB costs $499 less. On Qwen3.8 27B, the strongest model both hold, the MacBook Pro M5 Pro (16-inch), 64GB is about 1.2× faster: 12 tok/s against 10, both estimated from memory bandwidth. The GMKtec EVO-X2, 128GB pays for itself sooner, in 267 years against 269 years at 500k tokens a day.
| Strix Halo GMKtec EVO-X2, 128GB | MacBook Pro M5 Pro (16-inch), 64GB | |
|---|---|---|
| Price | $3,500 | $3,999 |
| Memory | 128 GB | 64 GB |
| Usable by the GPU | 96 GB | 48 GB |
| Memory bandwidth | 256 GB/s | 307 GB/s |
| Power under load | 150 W | 140 Wstand-in |
| Models that fit | 39 | 32 |
| Best model it runs | Qwen3.8 27B | Qwen3.8 27B |
| Speed on that model | 10 tok/s estimated | 12 tok/s estimated |
| Pay-back on that model | Pays back in 267 years | Pays back in 269 years |
The 140 W beside the MacBook Pro M5 Pro (16-inch), 64GB is a stand-in, not a figure for that machine: the data borrows it from the nearest hardware it does have, and the machine's own page names which and why. So the two figures above are not like for like, and the electricity in its pay-back here is priced from a borrowed number.
Run the numbers on the Strix Halo GMKtec EVO-X2, 128GB · or the MacBook Pro M5 Pro (16-inch), 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 Qwen3.8 27B, the strongest model both hold, at the five levels of use the calculator names. The Strix Halo GMKtec EVO-X2, 128GB pays back sooner at every level up to 4M tokens a day. Above that the MacBook Pro M5 Pro (16-inch), 64GB does.
| A day's use | Strix Halo GMKtec EVO-X2, 128GB | MacBook Pro M5 Pro (16-inch), 64GB |
|---|---|---|
| 50ka few chats a day | 2,670 years | 2,694 years |
| 200klight assistant use | 667 years | 673 years |
| 1Ma moderate coding-assistant day | 133 years | 135 years |
| 4Mheavy coding with an agent | 33 years | 34 years |
| 20Magents running most of the day | 9.4 yearsits ceiling | 7.9 yearsits ceiling |
On Qwen3.8 27B neither machine can generate 20M tokens a day: the Strix Halo GMKtec EVO-X2, 128GB manages at most 14.3M and the MacBook Pro M5 Pro (16-inch), 64GB at most 17.1M. Both figures on that row are for the most each can do.
Run the Strix Halo GMKtec EVO-X2, 128GB at 20M tokens a day · or the MacBook Pro M5 Pro (16-inch), 64GB
What the extra memory buys
The Strix Halo GMKtec EVO-X2, 128GB holds 7 models the MacBook Pro M5 Pro (16-inch), 64GB 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 GMKtec EVO-X2, 128GB |
|---|---|---|---|
| Ling 3.0 flashHaiku-class | 78 GB | 78 GB | 41 tok/s estimated |
| Qwen3.5 122B-A10BHaiku-class | 78 GB | 79 GB | 20 tok/s estimated |
| gpt-oss-120bBelow every hosted tier | 63 GB | 65 GB | 37 tok/s measured |
| Mistral Small 4 (119B-2603)Below every hosted tier | 74 GB | 75 GB | 32 tok/s estimated |
| Qwen3-Coder NextBelow every hosted tier | 48 GB | 49 GB | 54 tok/s estimated |
| Devstral 2 123BBelow every hosted tier | 75 GB | 87 GB | 2.2 tok/s estimated |
1 more, on the Strix Halo GMKtec EVO-X2, 128GB page.
The extra memory buys context as well. Of the 32 current models both machines hold at 32k, 3 run to a longer window on the Strix Halo GMKtec EVO-X2, 128GB: 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 30B reaches 128k there against 64k on the MacBook Pro M5 Pro (16-inch), 64GB, each the longest window the calculator offers that the machine still holds it at.
The GMKtec EVO-X2, 128GB is also head to head with another computer: Mac mini M5 Pro, 24GB · Mac Studio M5 Max, 128GB · DGX Spark, 128GB · MacBook Air M5 (15-inch), 16GB · Framework Desktop, 128GB · Mac Studio M5 Max, 64GB. With a graphics card: RTX PRO 6000 Blackwell, 96GB · Radeon AI PRO R9700, 32GB. With the same machine at another memory size: 64GB.
The MacBook Pro M5 Pro (16-inch), 64GB is also head to head with another computer: Mac mini M5 Pro, 24GB · Mac Studio M5 Max, 128GB · DGX Spark, 128GB · MacBook Air M5 (15-inch), 16GB · Beelink GTR9 Pro, 128GB · Minisforum MS-S1 Max, 128GB. With a graphics card: RTX PRO 6000 Blackwell, 96GB · Radeon AI PRO R9700, 32GB. With the same machine at another memory size: 24GB · 48GB.
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 GMKtec EVO-X2, 128GB runs · everything the MacBook Pro M5 Pro (16-inch), 64GB runs · every other match-up · the quickest pay-back at each level of use · every model against the frontier