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

Qwen2 72B on H200 SXM5 141GB: Does It Fit, How Fast, What It Costs

Qwen2 72B at FP8 (E4M3) needs 72.7 GB for its weights and 94.2 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
94.2 GB needed / 141 GB available
Decode speed
64.37
tok/s per stream
Aggregate
772.5
tok/s @ 8 concurrent
Cost / 1M tokens
$1.44
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 GB94.2 GB64.37772.52.45 s$1.44✓
2× H200282 GB94.2 GB109.426261.24 s$0.8461✓
4× H200564 GB94.2 GB218.910506636.1 ms$0.4230✓
8× H2001128 GB94.2 GB437.742023333.1 ms$0.2115✓
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?
4K501.34 GB✓ fits
8K252.68 GB✓ fits
33K610.74 GB✓ fits
66K321.47 GB✓ fits
131K142.95 GB✓ fits
Other GPUs that run Qwen2 72B
Same workload, same quantization — ranked by value (tokens per dollar-hour).
GPUGPUsAggregate tok/sCost / 1M tok
RTX 5090 32GB4×3922$0.1416
A100 80GB SXM42×1094$0.6092
H100 SXM5 80GB2×1833$0.7577
AMD MI300X 192GB1×853.0$0.8142
L40S 48GB2×472.8$0.8226
AMD MI325X 288GB1×965.6$1.01
Frequently asked questions

Can Qwen2 72B run on H200 SXM5 141GB?

Yes. Qwen2 72B at FP8 (E4M3) needs 94.2 GB including the KV cache, and H200 SXM5 141GB has 141 GB — so it fits on a single GPU.

How fast is Qwen2 72B on H200 SXM5 141GB?

64.37 tokens/sec per stream and 772.5 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 2.45 s, and inter-token latency is 15.5 ms.

What does Qwen2 72B on H200 SXM5 141GB cost per million tokens?

$1.44 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 Qwen2 72B need on H200 SXM5 141GB?

72.7 GB for the weights at FP8 (E4M3), plus 21.5 GB of KV cache for 8 concurrent requests at 8K context — 94.2 GB total. Every extra concurrent user at long context costs more, so leave headroom.

Is H200 SXM5 141GB the right choice for Qwen2 72B?

It works. Compare $1.44 per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 8× RTX 4080 16GB at $0.1062, and the fastest is 4× Cerebras CS-3 (WSE-3) at 43774 tok/s.

Adjust the workload yourself

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

Open in calculator