Mac Studio M5 Max vs M5 Ultra for local AI
Short answer
Get the M5 Max with 128 GB if you want to run models up to about 70B parameters, or large mixture-of-experts models like gpt-oss 120B; it costs far less and handles almost everything a single person runs locally. Get the M5 Ultra only if you need more than 128 GB for the very largest open models, or roughly double the speed on big dense models.
Apple's August 2026 Mac Studio comes with two chips. For local AI, the choice comes down to how much memory you need and how much you are willing to pay for speed.
Specs that matter for AI
From Apple's announcement and tech specs:
| M5 Max | M5 Ultra | |
|---|---|---|
| CPU | 18-core | Up to 36-core |
| GPU | Up to 40-core | Up to 80-core |
| Unified memory | 36 GB base, up to 128 GB | 96 GB base, up to 512 GB |
| Memory bandwidth | Up to 614 GB/s | 1.2 TB/s |
| Starting price (US) | $2,499 | $5,499 |
The 512 GB M5 Ultra ships later than the other configurations (late October 2026, according to MacRumors).
Speed: a quick estimate
Text generation speed is limited by how fast the chip can read the model from memory. A useful ceiling is bandwidth ÷ size of the active weights. Real results usually land at 60 to 80 percent of it.
| Model (4-bit) | Size read per token | M5 Max ceiling | M5 Ultra ceiling |
|---|---|---|---|
| 8B dense | ~5 GB | ~120 tok/s | ~240 tok/s |
| 32B dense | ~19 GB | ~32 tok/s | ~63 tok/s |
| 70B dense | ~42 GB | ~15 tok/s | ~29 tok/s |
| 120B mixture of experts, ~5B active (gpt-oss 120B) | ~3 GB | very fast | very fast |
These are estimates from the formula, not measurements. Mixture-of-experts models only read their active experts for each token, which is why a 120B model of that kind can feel quicker than a 32B dense one, as long as all of its weights fit in memory.
Reading speed for people is around 5 to 10 tokens per second, so anything above that feels responsive in chat. Speed matters more for coding agents and long documents, where the model reads and writes thousands of tokens per task.
Which to choose
M5 Max with 128 GB is the sweet spot for most people:
- Runs every popular model up to 70B at 4-bit, plus large mixture-of-experts models such as gpt-oss 120B (about 65 GB) and Qwen 3.5 122B (about 81 GB).
- Leaves room to keep a coding model and a chat model loaded at the same time.
- Costs a fraction of a high-memory Ultra.
M5 Ultra makes sense when:
- You want to run the largest open models (200B+ parameters, or 400B+ mixture-of-experts models), which need 256 GB or 512 GB.
- You run big dense models all day and twice the speed is worth the price.
- You also use the Mac for heavy video, 3D or training work that benefits from the extra GPU cores.
Avoid the low-memory versions of either chip if local AI is the main reason you are buying. A 36 GB M5 Max runs the same models as a much cheaper Mac mini, just faster.
Before you buy
Memory cannot be upgraded later, so configure the Mac Studio for the largest model you expect to run in the next few years, not just today. Use how much memory you need to size it, and check the current price of your configuration on Apple's store. If a Mac Studio is more than you need, see Mac mini vs Mac Studio for local AI.
Frequently asked questions
How much faster is the M5 Ultra than the M5 Max for LLMs?
Up to about twice as fast at generating text with large models, because it has about twice the memory bandwidth (1.2 TB/s vs up to 614 GB/s, per Apple). With small models, both are fast enough that the difference matters less.
Can the M5 Max run a 70B model?
Yes, with 128 GB of memory. A 70B model at 4-bit takes about 42 GB plus room for context, which fits with plenty to spare. Expect roughly 10 to 14 tokens per second, which is comfortable for reading along.
Is the base M5 Ultra with 96 GB a good buy for AI?
Usually not. For about twice the price of an M5 Max, it has less memory than a 128 GB M5 Max. Its extra bandwidth only pays off if the models you run fit in 96 GB and you need the speed.