Apple192 GB VRAM800 GB/s$0/hr

Qwen 3 30B-A3B (MoE) on Mac M2 Ultra (192GB unified): Does It Fit, How Fast, What It Costs

Qwen 3 30B-A3B (MoE) at FP8 (E4M3) needs 30.0 GB for its weights and 36.4 GB in total at 8K context with 8 concurrent users. That means it fits on a single Mac M2 Ultra (192GB unified). Every figure is computed by tokcalc's open-source capacity model.

Fits?
Yes, 1 GPU
36.4 GB needed / 192 GB available
Decode speed
260.0
tok/s per stream
Aggregate
2250
tok/s @ 8 concurrent
Cost / 1M tokens
—
1× Mac M2 Ultra (192GB unified) · quote required
What changes as you add Mac M2 Ultra (192GB unified)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× Mac192 GB36.4 GB260.022503.67 s—✓
2× Mac384 GB36.4 GB442.090001.85 s—✓
4× Mac768 GB36.4 GB884.036000941.4 ms—✓
8× Mac1536 GB36.4 GB1768144000485.7 ms—✓
Concurrency vs context length
On 1× Mac M2 Ultra (192GB unified) 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?
4K402412.3 MB✓ fits
8K201824.6 MB✓ fits
33K503.22 GB✓ fits
66K256.44 GB✓ fits
131K1212.88 GB✓ fits
Other GPUs that run Qwen 3 30B-A3B (MoE)
Same workload, same quantization — ranked by value (tokens per dollar-hour).
GPUGPUsAggregate tok/sCost / 1M tok
RTX 5090 32GB2×23762$0.0117
AMD MI300X 192GB1×20670$0.0336
A100 40GB SXM41×6045$0.0414
AMD MI325X 288GB1×23400$0.0415
A100 80GB SXM41×7800$0.0427
Intel Gaudi 3 128GB1×12870$0.0432
Frequently asked questions

Can Qwen 3 30B-A3B (MoE) run on Mac M2 Ultra (192GB unified)?

Yes. Qwen 3 30B-A3B (MoE) at FP8 (E4M3) needs 36.4 GB including the KV cache, and Mac M2 Ultra (192GB unified) has 192 GB — so it fits on a single GPU.

How fast is Qwen 3 30B-A3B (MoE) on Mac M2 Ultra (192GB unified)?

260.0 tokens/sec per stream and 2250 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 3.67 s, and inter-token latency is 3.8 ms.

What does Qwen 3 30B-A3B (MoE) on Mac M2 Ultra (192GB unified) cost per million tokens?

— per 1M output tokens at 1× Mac M2 Ultra (192GB unified). That is the marginal hardware cost — add idle capacity, ops, and egress for the real figure.

How much VRAM does Qwen 3 30B-A3B (MoE) need on Mac M2 Ultra (192GB unified)?

30.0 GB for the weights at FP8 (E4M3), plus 6.4 GB of KV cache for 8 concurrent requests at 8K context — 36.4 GB total. Every extra concurrent user at long context costs more, so leave headroom.

Is Mac M2 Ultra (192GB unified) the right choice for Qwen 3 30B-A3B (MoE)?

It works. Compare — per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 4× RTX 3080 10GB at $0.005513, and the fastest is 1× Cerebras CS-3 (WSE-3) at 78000 tok/s.

Adjust the workload yourself

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

Open in calculator