Side by side
| M5 Max | M5 Ultra | |
|---|---|---|
| Memory sizes | 36, 48, 64, 128 GB | 96, 256, 512 GB |
| Memory bandwidth | 460–614 GB/s | 1,200 GB/s |
| For models, at most | about 96 GB | about 384 GB |
| Models that run well | 47 of 73 | 61 of 73 |
| MLX seat class | Pro Latest | Ultra Latest |
| Found in | MacBook Pro (14-inch, M5 Pro or M5 Max), MacBook Pro (16-inch, M5 Pro or M5 Max), Mac Studio (M5 Max or M5 Ultra) | Mac Studio (M5 Max or M5 Ultra) |
Speed with popular models
Tokens a second for one conversation, each chip at its largest memory size (128 GB and 512 GB), with the best version of the model that fits.
| Model | M5 Max | M5 Ultra |
|---|---|---|
| Llama 3.1 8B Instruct8B | 33–58 8-bit | 64–113 8-bit |
| gpt-oss-20b21B · 3.6B active | 145–259 native 4.25-bit | 284–505 native 4.25-bit |
| Qwen3.6 35B A3B35B · 3B active | 86–154 8-bit | 169–300 8-bit |
| Qwen3.8 27B27B | 10–17 8-bit | 19–33 8-bit |
| Llama 3.3 70B Instruct70B | 4–7 8-bit | 14–24 4-bit |
| gpt-oss-120b117B · 5.1B active | 102–182 native 4.25-bit | 200–356 native 4.25-bit |
| Qwen3.5 122B A10B122B · 10B active | 49–88 4-bit | 51–91 8-bit |
| DeepSeek V4 Flash 0731284B · 13B active | 67–120 2-bit lower quality | 39–70 8-bit |
Questions
- Is the M5 Ultra faster than the M5 Max for LLMs?
- The M5 Ultra reads memory about 95% faster than the M5 Max (1,200 vs 614 GB/s), so it writes about 95% faster with any model that fits both. Reading a long prompt depends on GPU compute instead, which this comparison doesn’t cover.
- Which can run bigger models, the M5 Max or the M5 Ultra?
- The M5 Ultra: The M5 Ultra goes up to 512 GB of memory, the M5 Max to 128 GB. At its largest it runs 61 of 73 open models well, against 47.
More comparisons
- M1 Max vs M5 Max
- M3 Ultra vs M5 Max
- M4 Pro vs M5 Max
- M4 Max vs M5 Max
- M5 Pro vs M5 Max
- M3 Ultra vs M5 Ultra
- M4 Max vs M5 Ultra
The M5 Max for local AI · The M5 Ultra for local AI · Compare every model · The best Mac for local LLMs
How it’s worked out
Memory: the model’s parameters at 8, 6, 4, 3 or 2 bits per weight plus MLX’s group scales (half a bit per weight), or its native format, with room for the context on top. By default macOS lets the GPU use about 75% of unified memory. Speed: memory bandwidth divided by the bytes read per token is the ceiling for one conversation; in llama.cpp’s public Apple Silicon benchmarks real runs reach about 45% to 80% of it, which is the range shown. These are estimates, not measurements: measure your own Mac on MLX Bench. Model figures from each official model card, chip figures from Apple’s Tech Specs. Checked 2026-10-19. Same data as mlx.app/compare.