Apple192 GB VRAM800 GB/s$0/hr

OLMo 2 13B on Mac M2 Ultra (192GB unified): Does It Fit, How Fast, What It Costs

OLMo 2 13B at FP16 needs 26.0 GB for its weights and 36.7 GB in total at 8K context with 8 concurrent users. That means it fits on a single Mac M2 Ultra (192GB unified). Every figure is computed by tokcalc's open-source capacity model.

Fits?
Yes, 1 GPU
36.7 GB needed / 192 GB available
Decode speed
20.00
tok/s per stream
Aggregate
240.0
tok/s @ 8 concurrent
Cost / 1M tokens
—
1× Mac M2 Ultra (192GB unified) · quote required
What changes as you add Mac M2 Ultra (192GB unified)s
Tensor-parallel degree vs VRAM, throughput, and cost. Cost scales linearly with GPU count; decode throughput scales near-linearly too, so cost per token stays roughly flat.
GPUsTotal VRAMVRAM neededDecode tok/sAggregate tok/sTTFTCost / 1M tokFits?
1× Mac192 GB36.7 GB20.00240.015.86 s—✓
2× Mac384 GB36.7 GB34.00816.07.95 s—✓
4× Mac768 GB36.7 GB68.0032643.99 s—✓
8× Mac1536 GB36.7 GB136.0130562.01 s—✓
Concurrency vs context length
On 1× Mac M2 Ultra (192GB unified) at FP16. KV cache scales linearly with context, so this is the number of users your GPUs can actually serve.
ContextConcurrent usersKV per requestFits?
4K247687.2 MB✓ fits
8K1231.34 GB✓ fits
33K305.37 GB✓ fits
66K1510.74 GB✓ fits
131K721.47 GB✓ fits
Other GPUs that run OLMo 2 13B
Same workload, same quantization — ranked by value (tokens per dollar-hour).
GPUGPUsAggregate tok/sCost / 1M tok
RTX 5090 32GB2×1828$0.1520
AMD MI300X 192GB1×1590$0.4368
A100 40GB SXM41×465.0$0.5376
AMD MI325X 288GB1×1800$0.5401
A100 80GB SXM41×600.0$0.5556
Intel Gaudi 3 128GB1×990.0$0.5612
Frequently asked questions

Can OLMo 2 13B run on Mac M2 Ultra (192GB unified)?

Yes. OLMo 2 13B at FP16 needs 36.7 GB including the KV cache, and Mac M2 Ultra (192GB unified) has 192 GB — so it fits on a single GPU.

How fast is OLMo 2 13B on Mac M2 Ultra (192GB unified)?

20.00 tokens/sec per stream and 240.0 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 15.86 s, and inter-token latency is 50.0 ms.

What does OLMo 2 13B on Mac M2 Ultra (192GB unified) cost per million tokens?

— per 1M output tokens at 1× Mac M2 Ultra (192GB unified). That is the marginal hardware cost — add idle capacity, ops, and egress for the real figure.

How much VRAM does OLMo 2 13B need on Mac M2 Ultra (192GB unified)?

26.0 GB for the weights at FP16, plus 10.7 GB of KV cache for 8 concurrent requests at 8K context — 36.7 GB total. Every extra concurrent user at long context costs more, so leave headroom.

Is Mac M2 Ultra (192GB unified) the right choice for OLMo 2 13B?

It works. Compare — per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 4× RTX 3080 10GB at $0.0717, and the fastest is 1× Cerebras CS-3 (WSE-3) at 6000 tok/s.

Adjust the workload yourself

Same formulas, your context length, concurrency, and quantisation.

Open in calculator