NVIDIA141 GB VRAM4,800 GB/s$4/hr

Qwen 2.5-VL 72B (VLM) on H200 SXM5 141GB: Does It Fit, How Fast, What It Costs

Qwen 2.5-VL 72B (VLM) at FP8 (E4M3) needs 72.0 GB for its weights and 93.5 GB in total at 8K context with 8 concurrent users. That means it fits on a single H200 SXM5 141GB. Every figure is computed by tokcalc's open-source capacity model.

Fits?
Yes, 1 GPU
93.5 GB needed / 141 GB available
Decode speed
65.00
tok/s per stream
Aggregate
780.0
tok/s @ 8 concurrent
Cost / 1M tokens
$1.42
1× H200 SXM5 141GB
What changes as you add H200 SXM5 141GBs
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× H200141 GB93.5 GB65.00780.02.43 s$1.42✓
2× H200282 GB93.5 GB110.526521.23 s$0.8379✓
4× H200564 GB93.5 GB221.010608630.3 ms$0.4190✓
8× H2001128 GB93.5 GB442.042432330.2 ms$0.2095✓
Concurrency vs context length
On 1× H200 SXM5 141GB 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?
4K511.34 GB✓ fits
8K252.68 GB✓ fits
33K610.74 GB✓ fits
66K321.47 GB✓ fits
131K142.95 GB✓ fits
Other GPUs that run Qwen 2.5-VL 72B (VLM)
Same workload, same quantization — ranked by value (tokens per dollar-hour).
GPUGPUsAggregate tok/sCost / 1M tok
RTX 5090 32GB4×3960$0.1403
A100 80GB SXM42×1105$0.6033
H100 SXM5 80GB2×1851$0.7504
AMD MI300X 192GB1×861.3$0.8063
L40S 48GB2×477.4$0.8147
AMD MI325X 288GB1×975.0$0.9972
Frequently asked questions

Can Qwen 2.5-VL 72B (VLM) run on H200 SXM5 141GB?

Yes. Qwen 2.5-VL 72B (VLM) at FP8 (E4M3) needs 93.5 GB including the KV cache, and H200 SXM5 141GB has 141 GB — so it fits on a single GPU.

How fast is Qwen 2.5-VL 72B (VLM) on H200 SXM5 141GB?

65.00 tokens/sec per stream and 780.0 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 2.43 s, and inter-token latency is 15.4 ms.

What does Qwen 2.5-VL 72B (VLM) on H200 SXM5 141GB cost per million tokens?

$1.42 per 1M output tokens at 1× H200 SXM5 141GB ($4.00/hr). That is the marginal hardware cost — add idle capacity, ops, and egress for the real figure.

How much VRAM does Qwen 2.5-VL 72B (VLM) need on H200 SXM5 141GB?

72.0 GB for the weights at FP8 (E4M3), plus 21.5 GB of KV cache for 8 concurrent requests at 8K context — 93.5 GB total. Every extra concurrent user at long context costs more, so leave headroom.

Is H200 SXM5 141GB the right choice for Qwen 2.5-VL 72B (VLM)?

It works. Compare $1.42 per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 8× RTX 4080 16GB at $0.1052, and the fastest is 4× Cerebras CS-3 (WSE-3) at 44200 tok/s.

Adjust the workload yourself

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

Open in calculator