Framework Desktop: 64GB vs 128GB for local AI
The Framework Desktop, 128GB holds 33 of the 39 open models here, and the Framework Desktop, 64GB holds 27. 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 26 years against 45 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 | 27 | 33 |
| 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 26 years | Pays back in 45 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 | 256 years | 452 years |
| 200klight assistant use | 64 years | 113 years |
| 1Ma moderate coding-assistant day | 13 years | 23 years |
| 4Mheavy coding with an agent | 3.2 years | 5.6 years |
| 20Magents running most of the day | 11 monthsits ceiling | 19 monthsits 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 6 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 | 82 GB | 20 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 |
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. Graphics cards are priced as the card alone, so add the PC around one before comparing it with a complete computer. 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