NVIDIA48 GB VRAM864 GB/s$0.7/hr

Pixtral 12B (VLM) on L40S 48GB: 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 L40S 48GB. Every figure is computed by tokcalc's open-source capacity model.

Fits?
Yes, 1 GPU
34.7 GB needed / 48 GB available
Decode speed
23.40
tok/s per stream
Aggregate
280.8
tok/s @ 8 concurrent
Cost / 1M tokens
$0.6925
1× L40S 48GB
What changes as you add L40S 48GBs
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× L40S48 GB34.7 GB23.40280.84.37 s$0.6925✓
2× L40S96 GB34.7 GB39.78954.72.20 s$0.4073✓
4× L40S192 GB34.7 GB79.5638191.12 s$0.2037✓
8× L40S384 GB34.7 GB159.115276572.9 ms$0.1018✓
Concurrency vs context length
On 1× L40S 48GB at FP16. KV cache scales linearly with context, so this is the number of users your GPUs can actually serve.
ContextConcurrent usersKV per requestFits?
4K35687.2 MB✓ fits
8K171.34 GB✓ fits
33K45.37 GB✓ fits
66K210.74 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 L40S 48GB?

Yes. Pixtral 12B (VLM) at FP16 needs 34.7 GB including the KV cache, and L40S 48GB has 48 GB — so it fits on a single GPU.

How fast is Pixtral 12B (VLM) on L40S 48GB?

23.40 tokens/sec per stream and 280.8 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 4.37 s, and inter-token latency is 42.7 ms.

What does Pixtral 12B (VLM) on L40S 48GB cost per million tokens?

$0.6925 per 1M output tokens at 1× L40S 48GB ($0.7000/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 L40S 48GB?

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 L40S 48GB the right choice for Pixtral 12B (VLM)?

It works. Compare $0.6925 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