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

Qwen2 7B on H200 SXM5 141GB: Does It Fit, How Fast, What It Costs

Qwen2 7B at FP16 needs 15.2 GB for its weights and 19.0 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
19.0 GB needed / 141 GB available
Decode speed
204.7
tok/s per stream
Aggregate
2457
tok/s @ 8 concurrent
Cost / 1M tokens
$0.4523
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 GB19.0 GB204.72457287.1 ms$0.4523✓
2× H200282 GB19.0 GB348.08353159.0 ms$0.2660✓
4× H200564 GB19.0 GB696.13341194.5 ms$0.1330✓
8× H2001128 GB19.0 GB139213364462.2 ms$0.0665✓
Concurrency vs context length
On 1× H200 SXM5 141GB at FP16. KV cache scales linearly with context, so this is the number of users your GPUs can actually serve.
ContextConcurrent usersKV per requestFits?
4K535240.5 MB✓ fits
8K267481.0 MB✓ fits
33K661.88 GB✓ fits
66K333.76 GB✓ fits
131K167.52 GB✓ fits
Other GPUs that run Qwen2 7B
Same workload, same quantization — ranked by value (tokens per dollar-hour).
GPUGPUsAggregate tok/sCost / 1M tok
RTX 3090 24GB1×479.1$0.1450
RTX 5090 32GB1×917.2$0.1514
RTX 4090 24GB1×515.9$0.2154
AMD MI300X 192GB1×2713$0.2560
V100 SXM2 32GB1×460.6$0.3015
A100 40GB SXM41×793.3$0.3151
Frequently asked questions

Can Qwen2 7B run on H200 SXM5 141GB?

Yes. Qwen2 7B at FP16 needs 19.0 GB including the KV cache, and H200 SXM5 141GB has 141 GB — so it fits on a single GPU.

How fast is Qwen2 7B on H200 SXM5 141GB?

204.7 tokens/sec per stream and 2457 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 287.1 ms, and inter-token latency is 4.9 ms.

What does Qwen2 7B on H200 SXM5 141GB cost per million tokens?

$0.4523 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 7B need on H200 SXM5 141GB?

15.2 GB for the weights at FP16, plus 3.8 GB of KV cache for 8 concurrent requests at 8K context — 19.0 GB total. Every extra concurrent user at long context costs more, so leave headroom.

Is H200 SXM5 141GB the right choice for Qwen2 7B?

It works. Compare $0.4523 per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 2× RTX 3080 10GB at $0.0840, and the fastest is 1× Cerebras CS-3 (WSE-3) at 10236 tok/s.

Adjust the workload yourself

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

Open in calculator