Qwen 2.5 14B at FP16 needs 28.0 GB for its weights and 40.9 GB in total at 8K context with 8 concurrent users. That means it fits on a single AMD MI325X 288GB. 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× AMD | 288 GB | 40.9 GB | 139.3 | 1671 | 388.2 ms | $0.5817 | ✓ |
| 2× AMD | 576 GB | 40.9 GB | 236.8 | 5683 | 209.7 ms | $0.3422 | ✓ |
| 4× AMD | 1152 GB | 40.9 GB | 473.6 | 22731 | 119.9 ms | $0.1711 | ✓ |
| 8× AMD | 2304 GB | 40.9 GB | 947.1 | 90926 | 74.9 ms | $0.0855 | ✓ |
| Context | Concurrent users | KV per request | Fits? |
|---|---|---|---|
| 4K | 322 | 824.6 MB | ✓ fits |
| 8K | 161 | 1.61 GB | ✓ fits |
| 33K | 40 | 6.44 GB | ✓ fits |
| 66K | 20 | 12.88 GB | ✓ fits |
| 131K | 10 | 25.77 GB | ✓ fits |
| GPU | GPUs | Aggregate tok/s | Cost / 1M tok |
|---|---|---|---|
| RTX 5090 32GB | 2× | 1697 | $0.1637 |
| AMD MI300X 192GB | 1× | 1476 | $0.4704 |
| A100 80GB SXM4 | 1× | 557.1 | $0.5983 |
| Intel Gaudi 3 128GB | 1× | 919.3 | $0.6043 |
| H100 SXM5 80GB | 1× | 933.2 | $0.7441 |
| B200 SXM 192GB | 1× | 2229 | $0.7479 |
Yes. Qwen 2.5 14B at FP16 needs 40.9 GB including the KV cache, and AMD MI325X 288GB has 288 GB — so it fits on a single GPU.
139.3 tokens/sec per stream and 1671 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 388.2 ms, and inter-token latency is 7.2 ms.
$0.5817 per 1M output tokens at 1× AMD MI325X 288GB ($3.50/hr). That is the marginal hardware cost — add idle capacity, ops, and egress for the real figure.
28.0 GB for the weights at FP16, plus 12.9 GB of KV cache for 8 concurrent requests at 8K context — 40.9 GB total. Every extra concurrent user at long context costs more, so leave headroom.
It works. Compare $0.5817 per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 8× RTX 3080 10GB at $0.0386, and the fastest is 8× RTX 3080 10GB at 11517 tok/s.
Same formulas, your context length, concurrency, and quantisation.