Framework Desktop: 64GB vs 128GB for local AI
The Framework Desktop, 128GB holds 41 of the 50 current models here, and the Framework Desktop, 64GB holds 34. The Framework Desktop, 64GB costs $1,490 less. On Qwen3.8 27B, the strongest model both hold, they run at much the same speed: 10 and 10 tok/s, both estimated from memory bandwidth. The Framework Desktop, 64GB pays for itself sooner, in 140 years against 246 years at 500k tokens a day.
| Strix Halo Framework Desktop, 64GB | Strix Halo Framework Desktop, 128GB | |
|---|---|---|
| Price | $1,959 | $3,449 |
| Memory | 64 GB | 128 GB |
| Usable by the GPU | 48 GB | 96 GB |
| Memory bandwidth | 256 GB/s | 256 GB/s |
| Power under load | 133 W | 133 W |
| Models that fit | 34 | 41 |
| Best model it runs | Qwen3.8 27B | Qwen3.8 27B |
| Speed on that model | 10 tok/s estimated | 10 tok/s estimated |
| Pay-back on that model | Pays back in 140 years | Pays back in 246 years |
Run the numbers on the Strix Halo Framework Desktop, 64GB · or the Strix Halo Framework Desktop, 128GB
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 Framework Desktop, 64GB 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 | Strix Halo Framework Desktop, 64GB | Strix Halo Framework Desktop, 128GB |
|---|---|---|
| 50ka few chats a day | 1,400 years | 2,464 years |
| 200klight assistant use | 350 years | 616 years |
| 1Ma moderate coding-assistant day | 70 years | 123 years |
| 4Mheavy coding with an agent | 17 years | 31 years |
| 20Magents running most of the day | 4.9 yearsits ceiling | 8.6 yearsits ceiling |
On Qwen3.8 27B neither machine can generate 20M tokens a day: the Strix Halo Framework Desktop, 64GB manages at most 14.3M and the Strix Halo Framework Desktop, 128GB at most 14.3M. Both figures on that row are for the most each can do.
Run the Strix Halo Framework Desktop, 64GB at 20M tokens a day · or the Strix Halo Framework Desktop, 128GB
What the extra memory buys
The Strix Halo Framework Desktop, 128GB holds 7 models the Strix Halo Framework Desktop, 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 Framework Desktop, 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 | 35 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 Framework Desktop, 128GB page.
The extra memory buys context as well. Of the 34 current models both machines hold at 32k, 4 run to a longer window on the Strix Halo Framework Desktop, 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. Nanbeige4.3 33B reaches 256k there against 64k on the Strix Halo Framework Desktop, 64GB, each the longest window the calculator offers that the machine still holds it at.
The Framework Desktop, 64GB is also head to head with another computer: GMKtec EVO-X2, 64GB. With a graphics card: GeForce RTX 5090, 32GB. With the same box and the smaller chip: 32GB.
The Framework Desktop, 128GB is also head to head with another computer: GMKtec EVO-X2, 128GB · GMKtec EVO-X3, 128GB · Minisforum MS-S1 Max, 128GB · Beelink GTR9 Pro, 128GB · Corsair AI Workstation 300, 128GB · HP Z2 Mini G1a, 128GB · Mac Studio M5 Max, 64GB.
Both sizes have a page of their own, with every machine here sold at that size, the models that fit it and what one step of memory buys: what 64 GB runs · what 128 GB runs.
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, 64GB runs · everything the Strix Halo Framework Desktop, 128GB runs · every other match-up · the quickest pay-back at each level of use · every model against the frontier