Apple64 GB VRAM400 GB/s$0/hr

Pixtral 12B (VLM) on Mac M3 Max (64GB): Does It Fit, How Fast, What It Costs

Pixtral 12B (VLM) at FP16 needs 24.0 GB for its weights and 34.7 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
34.7 GB needed / 64 GB available
Decode speed
10.83
tok/s per stream
Aggregate
130.0
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 GB34.7 GB10.83130.028.21 s—✓
2× Mac128 GB34.7 GB18.42442.014.13 s—✓
4× Mac256 GB34.7 GB36.8317687.08 s—✓
8× Mac512 GB34.7 GB73.6770723.55 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?
4K59687.2 MB✓ fits
8K291.34 GB✓ fits
33K75.37 GB✓ fits
66K310.74 GB✓ fits
131K121.47 GB✓ fits
Other GPUs that run Pixtral 12B (VLM)
Same workload, same quantization — ranked by value (tokens per dollar-hour).
GPUGPUsAggregate tok/sCost / 1M tok
RTX 5090 32GB2×1980$0.1403
AMD MI300X 192GB1×1723$0.4032
A100 40GB SXM41×503.8$0.4963
AMD MI325X 288GB1×1950$0.4986
A100 80GB SXM41×650.0$0.5128
Intel Gaudi 3 128GB1×1073$0.5180
Frequently asked questions

Can Pixtral 12B (VLM) run on Mac M3 Max (64GB)?

Yes. Pixtral 12B (VLM) at FP16 needs 34.7 GB including the KV cache, and Mac M3 Max (64GB) has 64 GB — so it fits on a single GPU.

How fast is Pixtral 12B (VLM) on Mac M3 Max (64GB)?

10.83 tokens/sec per stream and 130.0 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 28.21 s, and inter-token latency is 92.3 ms.

What does Pixtral 12B (VLM) 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 Pixtral 12B (VLM) need on Mac M3 Max (64GB)?

24.0 GB for the weights at FP16, plus 10.7 GB of KV cache for 8 concurrent requests at 8K context — 34.7 GB total. Every extra concurrent user at long context costs more, so leave headroom.

Is Mac M3 Max (64GB) the right choice for Pixtral 12B (VLM)?

It works. Compare — per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 4× RTX 3080 10GB at $0.0662, and the fastest is 1× Cerebras CS-3 (WSE-3) at 6500 tok/s.

Adjust the workload yourself

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

Open in calculator