Apple192 GB VRAM800 GB/s$0/hr

Gemma 2 9B on Mac M2 Ultra (192GB unified): Does It Fit, How Fast, What It Costs

Gemma 2 9B at FP16 needs 18.0 GB for its weights and 40.5 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
40.5 GB needed / 192 GB available
Decode speed
28.89
tok/s per stream
Aggregate
346.7
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 GB40.5 GB28.89346.710.99 s—✓
2× Mac384 GB40.5 GB49.1111795.51 s—✓
4× Mac768 GB40.5 GB98.2247152.77 s—✓
8× Mac1536 GB40.5 GB196.4188591.40 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?
4K1231.41 GB✓ fits
8K612.82 GB✓ fits
33K1511.27 GB✓ fits
66K722.55 GB✓ fits
131K345.10 GB✓ fits
Other GPUs that run Gemma 2 9B
Same workload, same quantization — ranked by value (tokens per dollar-hour).
GPUGPUsAggregate tok/sCost / 1M tok
RTX 5090 32GB2×2640$0.1052
AMD MI300X 192GB1×2297$0.3024
AMD MI325X 288GB1×2600$0.3739
A100 80GB SXM41×866.7$0.3846
Intel Gaudi 3 128GB1×1430$0.3885
H100 SXM5 80GB1×1452$0.4784
Frequently asked questions

Can Gemma 2 9B run on Mac M2 Ultra (192GB unified)?

Yes. Gemma 2 9B at FP16 needs 40.5 GB including the KV cache, and Mac M2 Ultra (192GB unified) has 192 GB — so it fits on a single GPU.

How fast is Gemma 2 9B on Mac M2 Ultra (192GB unified)?

28.89 tokens/sec per stream and 346.7 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 10.99 s, and inter-token latency is 34.6 ms.

What does Gemma 2 9B 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 Gemma 2 9B need on Mac M2 Ultra (192GB unified)?

18.0 GB for the weights at FP16, plus 22.5 GB of KV cache for 8 concurrent requests at 8K context — 40.5 GB total. Every extra concurrent user at long context costs more, so leave headroom.

Is Mac M2 Ultra (192GB unified) the right choice for Gemma 2 9B?

It works. Compare — per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 8× RTX 3080 10GB at $0.0248, and the fastest is 8× RTX 3080 10GB at 17916 tok/s.

Adjust the workload yourself

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

Open in calculator