Apple128 GB VRAM546 GB/s$0/hr

Qwen2 72B on Mac M4 Max (128GB): Does It Fit, How Fast, What It Costs

Qwen2 72B at FP8 (E4M3) needs 72.7 GB for its weights and 94.2 GB in total at 8K context with 8 concurrent users. That means it fits on a single Mac M4 Max (128GB). Every figure is computed by tokcalc's open-source capacity model.

Fits?
Yes, 1 GPU
94.2 GB needed / 128 GB available
Decode speed
7.323
tok/s per stream
Aggregate
58.46
tok/s @ 8 concurrent
Cost / 1M tokens
—
1× Mac M4 Max (128GB) · quote required
What changes as you add Mac M4 Max (128GB)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× Mac128 GB94.2 GB7.32358.46140.30 s—✓
2× Mac256 GB94.2 GB12.45233.870.18 s—✓
4× Mac512 GB94.2 GB24.90935.435.10 s—✓
8× Mac1024 GB94.2 GB49.79374117.57 s—✓
Concurrency vs context length
On 1× Mac M4 Max (128GB) 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?
4K411.34 GB✓ fits
8K202.68 GB✓ fits
33K510.74 GB✓ fits
66K221.47 GB✓ fits
131K142.95 GB✓ fits
Other GPUs that run Qwen2 72B
Same workload, same quantization — ranked by value (tokens per dollar-hour).
GPUGPUsAggregate tok/sCost / 1M tok
RTX 5090 32GB4×3922$0.1416
A100 80GB SXM42×1094$0.6092
H100 SXM5 80GB2×1833$0.7577
AMD MI300X 192GB1×853.0$0.8142
L40S 48GB2×472.8$0.8226
AMD MI325X 288GB1×965.6$1.01
Frequently asked questions

Can Qwen2 72B run on Mac M4 Max (128GB)?

Yes. Qwen2 72B at FP8 (E4M3) needs 94.2 GB including the KV cache, and Mac M4 Max (128GB) has 128 GB — so it fits on a single GPU.

How fast is Qwen2 72B on Mac M4 Max (128GB)?

7.323 tokens/sec per stream and 58.46 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 140.30 s, and inter-token latency is 136.6 ms.

What does Qwen2 72B on Mac M4 Max (128GB) cost per million tokens?

— per 1M output tokens at 1× Mac M4 Max (128GB). That is the marginal hardware cost — add idle capacity, ops, and egress for the real figure.

How much VRAM does Qwen2 72B need on Mac M4 Max (128GB)?

72.7 GB for the weights at FP8 (E4M3), plus 21.5 GB of KV cache for 8 concurrent requests at 8K context — 94.2 GB total. Every extra concurrent user at long context costs more, so leave headroom.

Is Mac M4 Max (128GB) the right choice for Qwen2 72B?

It works. Compare — per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 8× RTX 4080 16GB at $0.1062, and the fastest is 4× Cerebras CS-3 (WSE-3) at 43774 tok/s.

Adjust the workload yourself

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

Open in calculator