Can I Run OLMo 2 on Mac Studio (M3 Ultra, 256 GB)?
Written by Jakub Rusinowski · Last updated November 26, 2024
Yes — comfortably
Yes, comfortably — OLMo 2 13B Instruct at Q8_0 needs about 22.1 GB of the 192 GB usable on Mac Studio (M3 Ultra, 256 GB), leaving ~169.9 GB spare and running at ~23.3 tok/s (estimated), with room for about 4,096 tokens of context.
Confidence: high · Recommended quantization: Q8_0 · Estimated speed: ~23.3 tok/s
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Mac Studio (M3 Ultra, 256 GB) — what it gives a model
| Usable memory for models | 192 GB |
| Memory bandwidth | 819 GB/s |
| Form factor | Desktop |
| Operating system | macOS |
| Memory upgradeable | No — soldered |
OLMo 2 on Mac Studio (M3 Ultra, 256 GB): memory by quantization
| Quant | Memory needed | Fits 192 GB? | Max context | Est. speed | Download |
|---|---|---|---|---|---|
| F16 | 34.9 GB | ✓ Yes | 4K | ~14 tok/s | 27.4 GB |
| Q8_0 | 22.1 GB | ✓ Yes | 4K | ~23.3 tok/s | 14.6 GB |
| Q6_K | 18.7 GB | ✓ Yes | 4K | ~28.2 tok/s | 11.2 GB |
| Q5_K_M | 17.2 GB | ✓ Yes | 4K | ~31.1 tok/s | 9.7 GB |
| Q4_K_M | 15.8 GB | ✓ Yes | 4K | ~34.6 tok/s | 8.3 GB |
| Q3_K_M | 13.4 GB | ✓ Yes | 4K | ~42.6 tok/s | 5.8 GB |
| Q2_K | 12 GB | ✓ Yes | 4K | ~48.8 tok/s | 4.5 GB |
Which OLMo 2 sizes fit
| Variant | Needs at Q4_K_M | Fits? | Est. speed |
|---|---|---|---|
| OLMo 2 13B Instruct | 15.8 GB | ✓ Fits | ~34.6 tok/s |
| OLMo 2 7B Instruct | 9.5 GB | ✓ Fits | ~56.8 tok/s |
What to watch out for
- Context is capped at about 4,096 tokens before memory runs out, which is short for document or agent work.
- Memory on this machine is not upgradeable, so the configuration you buy is the ceiling for every model you will ever run on it.
Mac Studio M3 Ultra 256 GB limitations
- The largest single-box unified memory pool available, but at roughly half the memory bandwidth of a high-end discrete GPU — very large models load, then run slowly.
- Memory is soldered; the configuration chosen at purchase is permanent.
Recommended setup
Ollama or LM Studio (Metal) — MLX for the fastest Apple-native throughput
How these numbers are calculated
- Memory need = quantized weights + KV cache at 8,192 tokens (f16) + 0.8 GB runtime overhead.
- 256 GB unified memory at 819 GB/s, shared between CPU and GPU.
- macOS reserves a share of unified memory for the system, so not all of it is available to a model.
- Throughput is a memory-bandwidth roofline estimate, not a measurement. It is labelled "estimated" everywhere it appears.
- KV cache is computed from this model's published attention configuration.
FAQ
Can I run OLMo 2 on Mac Studio (M3 Ultra, 256 GB)?
Yes, comfortably — OLMo 2 13B Instruct at Q8_0 needs about 22.1 GB of the 192 GB usable on Mac Studio (M3 Ultra, 256 GB), leaving ~169.9 GB spare and running at ~23.3 tok/s (estimated), with room for about 4,096 tokens of context.
Which quantization of OLMo 2 should I use on Mac Studio (M3 Ultra, 256 GB)?
Q8_0 — it needs about 22.1 GB of the 192 GB available, downloads as roughly 14.6 GB, and runs at an estimated 23.3 tokens/sec with up to 4K of context.
What limits OLMo 2 on Mac Studio (M3 Ultra, 256 GB)?
Nothing binding — the model fits with headroom and generates at a usable speed on this hardware.
Which runtime should I use?
Ollama or LM Studio (Metal) — MLX for the fastest Apple-native throughput
Other Computers
Other Models on Mac Studio (M3 Ultra, 256 GB)
- Phi 3.5 Family on Mac Studio (M3 Ultra, 256 GB)
- Phi-4 Family on Mac Studio (M3 Ultra, 256 GB)
- Phi-4 Mini on Mac Studio (M3 Ultra, 256 GB)
- Poolside Laguna XS 2.1 on Mac Studio (M3 Ultra, 256 GB)
- Qwen 2.5 Family on Mac Studio (M3 Ultra, 256 GB)
OLMo 2 on GPUs
- OLMo 2 on NVIDIA GeForce RTX 5080
- OLMo 2 on NVIDIA GeForce RTX 5070 Ti
- OLMo 2 on NVIDIA GeForce RTX 5060 Ti 16GB
- OLMo 2 on NVIDIA GeForce RTX 5060 Ti 8GB