Apple128 GB VRAM546 GB/s$0/hr

Qwen 2.5-VL 72B (VLM) on Mac M4 Max (128GB): Does It Fit, How Fast, What It Costs

Qwen 2.5-VL 72B (VLM) at FP8 (E4M3) needs 72.0 GB for its weights and 93.5 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
93.5 GB needed / 128 GB available
Decode speed
7.394
tok/s per stream
Aggregate
59.03
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 GB93.5 GB7.39459.03138.95 s—✓
2× Mac256 GB93.5 GB12.57236.169.50 s—✓
4× Mac512 GB93.5 GB25.14944.434.77 s—✓
8× Mac1024 GB93.5 GB50.28377817.40 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 Qwen 2.5-VL 72B (VLM)
Same workload, same quantization — ranked by value (tokens per dollar-hour).
GPUGPUsAggregate tok/sCost / 1M tok
RTX 5090 32GB4×3960$0.1403
A100 80GB SXM42×1105$0.6033
H100 SXM5 80GB2×1851$0.7504
AMD MI300X 192GB1×861.3$0.8063
L40S 48GB2×477.4$0.8147
AMD MI325X 288GB1×975.0$0.9972
Frequently asked questions

Can Qwen 2.5-VL 72B (VLM) run on Mac M4 Max (128GB)?

Yes. Qwen 2.5-VL 72B (VLM) at FP8 (E4M3) needs 93.5 GB including the KV cache, and Mac M4 Max (128GB) has 128 GB — so it fits on a single GPU.

How fast is Qwen 2.5-VL 72B (VLM) on Mac M4 Max (128GB)?

7.394 tokens/sec per stream and 59.03 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 138.95 s, and inter-token latency is 135.2 ms.

What does Qwen 2.5-VL 72B (VLM) 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 Qwen 2.5-VL 72B (VLM) need on Mac M4 Max (128GB)?

72.0 GB for the weights at FP8 (E4M3), plus 21.5 GB of KV cache for 8 concurrent requests at 8K context — 93.5 GB total. Every extra concurrent user at long context costs more, so leave headroom.

Is Mac M4 Max (128GB) the right choice for Qwen 2.5-VL 72B (VLM)?

It works. Compare — per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 8× RTX 4080 16GB at $0.1052, and the fastest is 4× Cerebras CS-3 (WSE-3) at 44200 tok/s.

Adjust the workload yourself

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

Open in calculator