Apple64 GB VRAM400 GB/s$0/hr

Gemma 2 27B on Mac M3 Max (64GB): Does It Fit, How Fast, What It Costs

Gemma 2 27B at FP8 (E4M3) needs 27.0 GB for its weights and 51.7 GB in total at 8K context with 8 concurrent users. That means it fits on a single Mac M3 Max (64GB). Every figure is computed by tokcalc's open-source capacity model.

Fits?
Yes, 1 GPU
51.7 GB needed / 64 GB available
Decode speed
14.44
tok/s per stream
Aggregate
129.6
tok/s @ 8 concurrent
Cost / 1M tokens
—
1× Mac M3 Max (64GB) · quote required
What changes as you add Mac M3 Max (64GB)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× Mac64 GB51.7 GB14.44129.663.29 s—✓
2× Mac128 GB51.7 GB24.56518.531.67 s—✓
4× Mac256 GB51.7 GB49.11207415.85 s—✓
8× Mac512 GB51.7 GB98.2282967.94 s—✓
Concurrency vs context length
On 1× Mac M3 Max (64GB) at FP8 (E4M3). KV cache scales linearly with context, so this is the number of users your GPUs can actually serve.
ContextConcurrent usersKV per requestFits?
4K231.54 GB✓ fits
8K113.09 GB✓ fits
33K212.35 GB✓ fits
66K124.70 GB✓ fits
131K049.39 GB✗ does not fit
Other GPUs that run Gemma 2 27B
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
L40S 48GB2×1273$0.3055
AMD MI325X 288GB1×2600$0.3739
A100 80GB SXM41×866.7$0.3846
Intel Gaudi 3 128GB1×1430$0.3885
Frequently asked questions

Can Gemma 2 27B run on Mac M3 Max (64GB)?

Yes. Gemma 2 27B at FP8 (E4M3) needs 51.7 GB including the KV cache, and Mac M3 Max (64GB) has 64 GB — so it fits on a single GPU.

How fast is Gemma 2 27B on Mac M3 Max (64GB)?

14.44 tokens/sec per stream and 129.6 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 63.29 s, and inter-token latency is 69.2 ms.

What does Gemma 2 27B on Mac M3 Max (64GB) cost per million tokens?

— per 1M output tokens at 1× Mac M3 Max (64GB). That is the marginal hardware cost — add idle capacity, ops, and egress for the real figure.

How much VRAM does Gemma 2 27B need on Mac M3 Max (64GB)?

27.0 GB for the weights at FP8 (E4M3), plus 24.7 GB of KV cache for 8 concurrent requests at 8K context — 51.7 GB total. Every extra concurrent user at long context costs more, so leave headroom.

Is Mac M3 Max (64GB) the right choice for Gemma 2 27B?

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 2× Cerebras CS-3 (WSE-3) at 29467 tok/s.

Adjust the workload yourself

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

Open in calculator