MacBook Pro M5 (14-inch): 16GB vs 32GB for local AI
The MacBook Pro M5 (14-inch), 32GB holds 23 of the 50 current models here, and the MacBook Pro M5 (14-inch), 16GB holds 13. The MacBook Pro M5 (14-inch), 16GB costs $400 less. On Gemma 4 12B, the strongest model both hold, they run at much the same speed: 14 and 14 tok/s, both estimated from memory bandwidth. Both pay for themselves in 157 years at 500k tokens a day, though that is each machine on its own strongest model rather than on the same one.
| MacBook Pro M5 (14-inch), 16GB | MacBook Pro M5 (14-inch), 32GB | |
|---|---|---|
| Price | $1,999 | $2,399 |
| Memory | 16 GB | 32 GB |
| Usable by the GPU | 10.5 GB | 21 GB |
| Memory bandwidth | 153 GB/s | 153 GB/s |
| Power under load | 65 Wstand-in | 65 Wstand-in |
| Models that fit | 13 | 23 |
| Best model it runs | Gemma 4 12B | Qwen3.8 27B |
| Speed on that model | 14 tok/s estimatedGemma 4 12B | 6.2 tok/s estimatedQwen3.8 27B |
| Pay-back on that model | Pays back in 157 years | Pays back in 157 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 what the row shows is one borrowed figure printed twice. 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 MacBook Pro M5 (14-inch), 16GB · or the MacBook Pro M5 (14-inch), 32GB
Jump to: Side by side on Gemma 4 12B · How much use it takes to pay back · What the extra memory buys · The assumptions behind both columns
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.
| MacBook Pro M5 (14-inch), 16GB | MacBook Pro M5 (14-inch), 32GB | |
|---|---|---|
| Speed | 14 tok/s estimated | 14 tok/s estimated |
| Pay-back | Pays back in 157 years | Pays back in 188 years |
Run Gemma 4 12B on the MacBook Pro M5 (14-inch), 16GB · or on the MacBook Pro M5 (14-inch), 32GB
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 MacBook Pro M5 (14-inch), 16GB 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 | MacBook Pro M5 (14-inch), 16GB | MacBook Pro M5 (14-inch), 32GB |
|---|---|---|
| 50ka few chats a day | 1,569 years | 1,883 years |
| 200klight assistant use | 392 years | 471 years |
| 1Ma moderate coding-assistant day | 78 years | 94 years |
| 4Mheavy coding with an agent | 20 years | 24 years |
| 20Magents running most of the day | 4.0 yearsits ceiling | 4.7 yearsits ceiling |
On Gemma 4 12B neither machine can generate 20M tokens a day: the MacBook Pro M5 (14-inch), 16GB manages at most 19.8M and the MacBook Pro M5 (14-inch), 32GB at most 19.8M. Both figures on that row are for the most each can do.
Run the MacBook Pro M5 (14-inch), 16GB at 20M tokens a day · or the MacBook Pro M5 (14-inch), 32GB
What the extra memory buys
The MacBook Pro M5 (14-inch), 32GB holds 10 models the MacBook Pro M5 (14-inch), 16GB cannot at 32k of context. The strongest of them are what the difference in memory actually buys.
| Model | Weights | Needs at 32k | On the MacBook Pro M5 (14-inch), 32GB |
|---|---|---|---|
| Qwen3.8 27BSonnet-class | 16 GB | 19 GB | 6.2 tok/s estimated |
| Qwen3.6 27BHaiku-class | 17 GB | 19 GB | 6 tok/s estimated |
| Muse Glimmer 30BHaiku-class | 17 GB | 18 GB | 6.4 tok/s estimated |
| Gemma 4 26B-A4BHaiku-class | 17 GB | 18 GB | 13 tok/s estimated |
| GLM-4.7-FlashHaiku-class | 18 GB | 20 GB | 13 tok/s estimated |
| Granite 4.2 8BBelow every hosted tier | 5.3 GB | 11 GB | 11 tok/s estimated |
4 more, on the MacBook Pro M5 (14-inch), 32GB page.
The extra memory buys context as well. Of the 13 current models both machines hold at 32k, 7 run to a longer window on the MacBook Pro M5 (14-inch), 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. Gemma 4 12B reaches 256k there against 128k on the MacBook Pro M5 (14-inch), 16GB, each the longest window the calculator offers that the machine still holds it at.
The MacBook Pro M5 (14-inch), 16GB is also head to head with a graphics card: GeForce RTX 5090, 32GB.
The MacBook Pro M5 (14-inch), 32GB is also head to head with another computer: Mac Studio M5 Max, 36GB · Mac mini M5 Pro, 48GB.
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 16 GB runs · what 32 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 MacBook Pro M5 (14-inch), 16GB runs · everything the MacBook Pro M5 (14-inch), 32GB runs · every other match-up · the quickest pay-back at each level of use · every model against the frontier