The PyTorch error on a Mac carries one number that people search for. This one is from a 16 GB Mac (AudioLDM2 #20):
RuntimeError: MPS backend out of memory (MPS allocated: 18.02 GB, other allocations: 107.10 MB, max allowed: 18.13 GB). Tried to allocate 4.50 MB on private pool.
In my earlier note I measured where it comes from on my 48 GB Mac. "max allowed" is PYTORCH_MPS_HIGH_WATERMARK_RATIO, 1.7 by default, times the GPU working set macOS recommends, which torch.mps.recommended_max_memory() returns. One machine can't tell you what that number is on the others, so I read it off other people's errors.
On 24 October I searched GitHub for issues that quote the error with its "max allowed" value. That gave 250 issues and pull requests, 167 of them with a number in the text. Most values fall into a few groups, and where a reporter named their Mac's memory, the groups line up with the size. Divided by 1.7, each value gives the working set macOS gave the GPU on that machine.
| Mac memory | max allowed, GiB | GPU working set, GiB | share of memory | reports | seen |
|---|---|---|---|---|---|
| 8 GB | 9.07 | 5.33 | 67 % | 27 | 2023 – 2026 |
| 16 GB | 18.13 | 10.67 | 67 % | 18 | 2023 – 2026 |
| 24 GB | 27.20 | 16.00 | 67 % | 9 | Jan 2025 – Jan 2026 |
| 24 GB | 30.19 | 17.76 | 74 % | 3 | Dec 2025 – Sep 2026 |
| 32 GB | 36.27 | 21.33 | 67 % | 6 | 2024 – 2025 |
| 36 GB | 45.90 | 27.00 | 75 % | 3 | 2024 – 2026 |
| 48 GB | 63.65 | 37.44 | 78 % | 4, plus mine | Sep – Oct 2026 |
| 64 GB | 81.60 | 48.00 | 75 % | 7 | Dec 2023 – Apr 2025 |
| 64 GB | 88.13 | 51.84 | 81 % | 6 | Mar – Oct 2026 |
| 128 GB | 163.20 | 96.00 | 75 % | 4 | 2024 – 2025 |
| 128 GB | 182.78 | 107.52 | 84 % | 2 | Dec 2025 – Jan 2026 |
Older PyTorch versions label these numbers "GB" and newer ones "GiB". Both are the binary unit: 1.7 × two thirds × 16 GiB is exactly 18.13.
Until late 2025 the rule looks simple. macOS gave the GPU two thirds of memory on Macs up to 32 GB and three quarters above that. Reports from late 2025 on show larger shares on the 24 GB, 64 GB and 128 GB Macs. The three 64 GB reports that name their system all say macOS 26. The 8 and 16 GB values haven't moved. My own 48 GB Mac runs macOS 26.5.2 and returns 37.44 GiB, 78 %.
Two limits on what this shows: the newer rows rest on two to six reports each, and I can't tell from them whether macOS or the chip made the difference.
At the default ratio the limit is above physical memory on every row of the table: 1.7 × two thirds is 113 % of memory, and 1.7 × 84 % is 143 %. By the time a job reaches "max allowed", it has been swapping for a while. That matches my own measurement: on my Mac, swap began between 33.5 and 36 GB of footprint, far below the 63.65 GiB limit. The advice at the end of the error, a ratio of 0.0, removes the limit, so the job can swap further.
If you'd rather get a clean error than a swapping Mac, set the limit below your memory, for example a ratio of 1.0, which is the working set itself. Set the low ratio with it: on PyTorch 2.14, a high ratio below 1.4 set on its own fails with "invalid low watermark ratio 1.4".
PYTORCH_MPS_HIGH_WATERMARK_RATIO=1.0 PYTORCH_MPS_LOW_WATERMARK_RATIO=0.8 python your_script.py
To see your own Mac's working set:
import torch
print(torch.mps.recommended_max_memory() / 2**30, "GiB")
About a third of the reports show other limits, such as 1.70 GiB, 3.40 GiB, 6.77 GiB or 3.00 GiB. Those aren't the Mac's default. An app or a user set its own ratio or cap: one video tool caps MPS at 3 GiB even on a 128 GB Mac. Another 20 reports sit at 7.93, and I couldn't tie that value to one Mac size. If your number is far below the table, look in the tool's settings before you blame the Mac.
Two reports for each row. The full list of 167 is in the data file.