Apple192 GB VRAM800 GB/s$0/hr

Qwen 3 235B-A22B (MoE) on Mac M2 Ultra (192GB unified): Does It Fit, How Fast, What It Costs

Qwen 3 235B-A22B (MoE) at AWQ 4-bit needs 129.3 GB for its weights and 141.9 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
141.9 GB needed / 192 GB available
Decode speed
37.82
tok/s per stream
Aggregate
306.8
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 GB141.9 GB37.82306.826.76 s—✓
2× Mac384 GB141.9 GB64.29122713.40 s—✓
4× Mac768 GB141.9 GB128.649096.71 s—✓
8× Mac1536 GB141.9 GB257.2196363.37 s—✓
Concurrency vs context length
On 1× Mac M2 Ultra (192GB unified) at AWQ 4-bit. KV cache scales linearly with context, so this is the number of users your GPUs can actually serve.
ContextConcurrent usersKV per requestFits?
4K79807.5 MB✓ fits
8K391.58 GB✓ fits
33K96.31 GB✓ fits
66K412.62 GB✓ fits
131K225.23 GB✓ fits
Other GPUs that run Qwen 3 235B-A22B (MoE)
Same workload, same quantization — ranked by value (tokens per dollar-hour).
GPUGPUsAggregate tok/sCost / 1M tok
RTX 5090 32GB8×55300$0.0201
L40S 48GB4×6666$0.1167
A100 80GB SXM42×3857$0.1728
H100 SXM5 80GB2×6461$0.2150
AMD MI300X 192GB1×3007$0.2310
H200 SXM5 141GB2×9258$0.2400
Frequently asked questions

Can Qwen 3 235B-A22B (MoE) run on Mac M2 Ultra (192GB unified)?

Yes. Qwen 3 235B-A22B (MoE) at AWQ 4-bit needs 141.9 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 235B-A22B (MoE) on Mac M2 Ultra (192GB unified)?

37.82 tokens/sec per stream and 306.8 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 26.76 s, and inter-token latency is 26.4 ms.

What does Qwen 3 235B-A22B (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 235B-A22B (MoE) need on Mac M2 Ultra (192GB unified)?

129.3 GB for the weights at AWQ 4-bit, plus 12.6 GB of KV cache for 8 concurrent requests at 8K context — 141.9 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 235B-A22B (MoE)?

It works. Compare — per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 8× RTX 5090 32GB at $0.0201, and the fastest is 4× Cerebras CS-3 (WSE-3) at 154298 tok/s.

Adjust the workload yourself

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

Open in calculator