Qwen 2.5-VL 7B (VLM) at FP16 needs 14.0 GB for its weights and 17.8 GB in total at 8K context with 8 concurrent users. That means it fits on a single H100 PCIe 80GB. Every figure is computed by tokcalc's open-source capacity model.
| GPUs | Total VRAM | VRAM needed | Decode tok/s | Aggregate tok/s | TTFT | Cost / 1M tok | Fits? |
|---|---|---|---|---|---|---|---|
| 1× H100 | 80 GB | 17.8 GB | 92.86 | 1114 | 344.2 ms | $0.4986 | ✓ |
| 2× H100 | 160 GB | 17.8 GB | 157.9 | 3789 | 188.0 ms | $0.2933 | ✓ |
| 4× H100 | 320 GB | 17.8 GB | 315.7 | 15154 | 109.0 ms | $0.1466 | ✓ |
| 8× H100 | 640 GB | 17.8 GB | 631.4 | 60617 | 69.5 ms | $0.0733 | ✓ |
| Context | Concurrent users | KV per request | Fits? |
|---|---|---|---|
| 4K | 280 | 240.5 MB | ✓ fits |
| 8K | 140 | 481.0 MB | ✓ fits |
| 33K | 35 | 1.88 GB | ✓ fits |
| 66K | 17 | 3.76 GB | ✓ fits |
| 131K | 8 | 7.52 GB | ✓ fits |
| GPU | GPUs | Aggregate tok/s | Cost / 1M tok |
|---|---|---|---|
| RTX 3090 24GB | 1× | 521.5 | $0.1332 |
| RTX 5090 32GB | 1× | 998.4 | $0.1391 |
| RTX 4090 24GB | 1× | 561.6 | $0.1978 |
| AMD MI300X 192GB | 1× | 2953 | $0.2352 |
| V100 SXM2 32GB | 1× | 501.4 | $0.2770 |
| A100 40GB SXM4 | 1× | 863.6 | $0.2895 |
Yes. Qwen 2.5-VL 7B (VLM) at FP16 needs 17.8 GB including the KV cache, and H100 PCIe 80GB has 80 GB — so it fits on a single GPU.
92.86 tokens/sec per stream and 1114 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 344.2 ms, and inter-token latency is 10.8 ms.
$0.4986 per 1M output tokens at 1× H100 PCIe 80GB ($2.00/hr). That is the marginal hardware cost — add idle capacity, ops, and egress for the real figure.
14.0 GB for the weights at FP16, plus 3.8 GB of KV cache for 8 concurrent requests at 8K context — 17.8 GB total. Every extra concurrent user at long context costs more, so leave headroom.
It works. Compare $0.4986 per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 2× RTX 3080 10GB at $0.0772, and the fastest is 1× Cerebras CS-3 (WSE-3) at 11143 tok/s.
Same formulas, your context length, concurrency, and quantisation.