Apple64 GB VRAM400 GB/s$0/hr

Qwen2 7B on Mac M3 Max (64GB): 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 M3 Max (64GB). Every figure is computed by tokcalc's open-source capacity model.

Fits?
Yes, 1 GPU
19.0 GB needed / 64 GB available
Decode speed
17.06
tok/s per stream
Aggregate
204.7
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 GB19.0 GB17.06204.717.92 s—✓
2× Mac128 GB19.0 GB29.00696.18.98 s—✓
4× Mac256 GB19.0 GB58.0127844.51 s—✓
8× Mac512 GB19.0 GB116.0111372.27 s—✓
Concurrency vs context length
On 1× Mac M3 Max (64GB) at FP16. KV cache scales linearly with context, so this is the number of users your GPUs can actually serve.
ContextConcurrent usersKV per requestFits?
4K207240.5 MB✓ fits
8K103481.0 MB✓ fits
33K251.88 GB✓ fits
66K123.76 GB✓ fits
131K67.52 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 M3 Max (64GB)?

Yes. Qwen2 7B at FP16 needs 19.0 GB including the KV cache, and Mac M3 Max (64GB) has 64 GB — so it fits on a single GPU.

How fast is Qwen2 7B on Mac M3 Max (64GB)?

17.06 tokens/sec per stream and 204.7 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 17.92 s, and inter-token latency is 58.6 ms.

What does Qwen2 7B 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 Qwen2 7B need on Mac M3 Max (64GB)?

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 M3 Max (64GB) 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