Apple128 GB VRAM546 GB/s$0/hr

Qwen2 7B on Mac M4 Max (128GB): Does It Fit, How Fast, What It Costs

Qwen2 7B at FP16 needs 15.2 GB for its weights and 19.0 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
19.0 GB needed / 128 GB available
Decode speed
23.29
tok/s per stream
Aggregate
279.4
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 GB19.0 GB23.29279.414.76 s—✓
2× Mac256 GB19.0 GB39.59950.17.40 s—✓
4× Mac512 GB19.0 GB79.1838013.71 s—✓
8× Mac1024 GB19.0 GB158.4152021.87 s—✓
Concurrency vs context length
On 1× Mac M4 Max (128GB) at FP16. KV cache scales linearly with context, so this is the number of users your GPUs can actually serve.
ContextConcurrent usersKV per requestFits?
4K480240.5 MB✓ fits
8K240481.0 MB✓ fits
33K601.88 GB✓ fits
66K303.76 GB✓ fits
131K157.52 GB✓ fits
Other GPUs that run Qwen2 7B
Same workload, same quantization — ranked by value (tokens per dollar-hour).
GPUGPUsAggregate tok/sCost / 1M tok
RTX 3090 24GB1×479.1$0.1450
RTX 5090 32GB1×917.2$0.1514
RTX 4090 24GB1×515.9$0.2154
AMD MI300X 192GB1×2713$0.2560
V100 SXM2 32GB1×460.6$0.3015
A100 40GB SXM41×793.3$0.3151
Frequently asked questions

Can Qwen2 7B run on Mac M4 Max (128GB)?

Yes. Qwen2 7B at FP16 needs 19.0 GB including the KV cache, and Mac M4 Max (128GB) has 128 GB — so it fits on a single GPU.

How fast is Qwen2 7B on Mac M4 Max (128GB)?

23.29 tokens/sec per stream and 279.4 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 14.76 s, and inter-token latency is 42.9 ms.

What does Qwen2 7B 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 7B need on Mac M4 Max (128GB)?

15.2 GB for the weights at FP16, plus 3.8 GB of KV cache for 8 concurrent requests at 8K context — 19.0 GB total. Every extra concurrent user at long context costs more, so leave headroom.

Is Mac M4 Max (128GB) the right choice for Qwen2 7B?

It works. Compare — per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 2× RTX 3080 10GB at $0.0840, and the fastest is 1× Cerebras CS-3 (WSE-3) at 10236 tok/s.

Adjust the workload yourself

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

Open in calculator