Apple192 GB VRAM800 GB/s$0/hr

Mixtral 8x7B (MoE) on Mac M2 Ultra (192GB unified): Does It Fit, How Fast, What It Costs

Mixtral 8x7B (MoE) at FP8 (E4M3) needs 46.7 GB for its weights and 55.3 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
55.3 GB needed / 192 GB available
Decode speed
60.47
tok/s per stream
Aggregate
523.3
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 GB55.3 GB60.47523.315.70 s—✓
2× Mac384 GB55.3 GB102.820937.87 s—✓
4× Mac768 GB55.3 GB205.683723.95 s—✓
8× Mac1536 GB55.3 GB411.2334881.99 s—✓
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?
4K270549.8 MB✓ fits
8K1351.07 GB✓ fits
33K334.29 GB✓ fits
66K168.59 GB✓ fits
131K817.18 GB✓ fits
Other GPUs that run Mixtral 8x7B (MoE)
Same workload, same quantization — ranked by value (tokens per dollar-hour).
GPUGPUsAggregate tok/sCost / 1M tok
RTX 5090 32GB2×5526$0.0503
AMD MI300X 192GB1×4807$0.1445
L40S 48GB2×2664$0.1460
AMD MI325X 288GB1×5442$0.1787
A100 80GB SXM41×1814$0.1838
Intel Gaudi 3 128GB1×2993$0.1856
Frequently asked questions

Can Mixtral 8x7B (MoE) run on Mac M2 Ultra (192GB unified)?

Yes. Mixtral 8x7B (MoE) at FP8 (E4M3) needs 55.3 GB including the KV cache, and Mac M2 Ultra (192GB unified) has 192 GB — so it fits on a single GPU.

How fast is Mixtral 8x7B (MoE) on Mac M2 Ultra (192GB unified)?

60.47 tokens/sec per stream and 523.3 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 15.70 s, and inter-token latency is 16.5 ms.

What does Mixtral 8x7B (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 Mixtral 8x7B (MoE) need on Mac M2 Ultra (192GB unified)?

46.7 GB for the weights at FP8 (E4M3), plus 8.6 GB of KV cache for 8 concurrent requests at 8K context — 55.3 GB total. Every extra concurrent user at long context costs more, so leave headroom.

Is Mac M2 Ultra (192GB unified) the right choice for Mixtral 8x7B (MoE)?

It works. Compare — per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 8× RTX 3080 10GB at $0.0119, and the fastest is 2× Cerebras CS-3 (WSE-3) at 61674 tok/s.

Adjust the workload yourself

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

Open in calculator