NVIDIA48 GB VRAM864 GB/s$0.7/hr

Qwen3.8 27B (VLM) on L40S 48GB: Does It Fit, How Fast, What It Costs

Qwen3.8 27B (VLM) at FP8 (E4M3) needs 27.8 GB for its weights and 33.3 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
33.3 GB needed / 48 GB available
Decode speed
30.32
tok/s per stream
Aggregate
363.9
tok/s @ 8 concurrent
Cost / 1M tokens
$0.5344
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 GB33.3 GB30.32363.910.00 s$0.5344✓
2× L40S96 GB33.3 GB51.5512375.02 s$0.3143✓
4× L40S192 GB33.3 GB103.149492.52 s$0.1572✓
8× L40S384 GB33.3 GB206.2197951.28 s$0.0786✓
Concurrency vs context length
On 1× L40S 48GB 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?
4K481.07 GB✓ fits
8K292.15 GB✓ fits
33K88.59 GB✓ fits
66K417.18 GB✓ fits
131K234.36 GB✓ fits
Other GPUs that run Qwen3.8 27B (VLM)
Same workload, same quantization — ranked by value (tokens per dollar-hour).
GPUGPUsAggregate tok/sCost / 1M tok
RTX 5090 32GB2×2566$0.1083
AMD MI300X 192GB1×2232$0.3111
A100 40GB SXM41×652.8$0.3830
AMD MI325X 288GB1×2527$0.3847
A100 80GB SXM41×842.3$0.3957
Intel Gaudi 3 128GB1×1390$0.3997
Frequently asked questions

Can Qwen3.8 27B (VLM) run on L40S 48GB?

Yes. Qwen3.8 27B (VLM) at FP8 (E4M3) needs 33.3 GB including the KV cache, and L40S 48GB has 48 GB — so it fits on a single GPU.

How fast is Qwen3.8 27B (VLM) on L40S 48GB?

30.32 tokens/sec per stream and 363.9 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 10.00 s, and inter-token latency is 33.0 ms.

What does Qwen3.8 27B (VLM) on L40S 48GB cost per million tokens?

$0.5344 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 Qwen3.8 27B (VLM) need on L40S 48GB?

27.8 GB for the weights at FP8 (E4M3), plus 5.5 GB of KV cache for 8 concurrent requests at 8K context — 33.3 GB total. Every extra concurrent user at long context costs more, so leave headroom.

Is L40S 48GB the right choice for Qwen3.8 27B (VLM)?

It works. Compare $0.5344 per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 4× RTX 3080 10GB at $0.0511, and the fastest is 1× Cerebras CS-3 (WSE-3) at 8423 tok/s.

Adjust the workload yourself

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

Open in calculator