NVIDIA288 GB VRAM8,000 GB/s$8/hr

Pixtral 12B (VLM) on B300 SXM 288GB: 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 B300 SXM 288GB. Every figure is computed by tokcalc's open-source capacity model.

Fits?
Yes, 1 GPU
34.7 GB needed / 288 GB available
Decode speed
216.7
tok/s per stream
Aggregate
2600
tok/s @ 8 concurrent
Cost / 1M tokens
$0.8547
1× B300 SXM 288GB
What changes as you add B300 SXM 288GBs
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× B300288 GB34.7 GB216.72600296.8 ms$0.8547✓
2× B300576 GB34.7 GB368.38840163.8 ms$0.5028✓
4× B3001152 GB34.7 GB736.73536096.9 ms$0.2514✓
8× B3002304 GB34.7 GB147314144063.4 ms$0.1257✓
Concurrency vs context length
On 1× B300 SXM 288GB at FP16. KV cache scales linearly with context, so this is the number of users your GPUs can actually serve.
ContextConcurrent usersKV per requestFits?
4K393687.2 MB✓ fits
8K1961.34 GB✓ fits
33K495.37 GB✓ fits
66K2410.74 GB✓ fits
131K1221.47 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 B300 SXM 288GB?

Yes. Pixtral 12B (VLM) at FP16 needs 34.7 GB including the KV cache, and B300 SXM 288GB has 288 GB — so it fits on a single GPU.

How fast is Pixtral 12B (VLM) on B300 SXM 288GB?

216.7 tokens/sec per stream and 2600 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 296.8 ms, and inter-token latency is 4.6 ms.

What does Pixtral 12B (VLM) on B300 SXM 288GB cost per million tokens?

$0.8547 per 1M output tokens at 1× B300 SXM 288GB ($8.00/hr). 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 B300 SXM 288GB?

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 B300 SXM 288GB the right choice for Pixtral 12B (VLM)?

It works. Compare $0.8547 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