Phi-3 Mini 3.8B at FP16 needs 7.6 GB for its weights and 33.4 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 | 33.4 GB | 513.2 | 6158 | 127.2 ms | $0.1579 | ✓ |
| 2× AMD | 576 GB | 33.4 GB | 872.4 | 20937 | 78.8 ms | $0.0929 | ✓ |
| 4× AMD | 1152 GB | 33.4 GB | 1745 | 83747 | 54.4 ms | $0.0464 | ✓ |
| 8× AMD | 2304 GB | 33.4 GB | 3489 | 334989 | 42.2 ms | $0.0232 | ✓ |
| Context | Concurrent users | KV per request | Fits? |
|---|---|---|---|
| 4K | 174 | 1.61 GB | ✓ fits |
| 8K | 87 | 3.22 GB | ✓ fits |
| 33K | 21 | 12.88 GB | ✓ fits |
| 66K | 10 | 25.77 GB | ✓ fits |
| 131K | 5 | 51.54 GB | ✓ fits |
| GPU | GPUs | Aggregate tok/s | Cost / 1M tok |
|---|---|---|---|
| RTX 5090 32GB | 2× | 6253 | $0.0444 |
| AMD MI300X 192GB | 1× | 5439 | $0.1277 |
| A100 40GB SXM4 | 1× | 1591 | $0.1572 |
| A100 80GB SXM4 | 1× | 2053 | $0.1624 |
| Intel Gaudi 3 128GB | 1× | 3387 | $0.1640 |
| H100 SXM5 80GB | 1× | 3438 | $0.2020 |
Yes. Phi-3 Mini 3.8B at FP16 needs 33.4 GB including the KV cache, and AMD MI325X 288GB has 288 GB — so it fits on a single GPU.
513.2 tokens/sec per stream and 6158 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 127.2 ms, and inter-token latency is 1.9 ms.
$0.1579 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.
7.6 GB for the weights at FP16, plus 25.8 GB of KV cache for 8 concurrent requests at 8K context — 33.4 GB total. Every extra concurrent user at long context costs more, so leave headroom.
It works. Compare $0.1579 per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 4× RTX 3080 10GB at $0.0209, and the fastest is 1× Cerebras CS-3 (WSE-3) at 20526 tok/s.
Same formulas, your context length, concurrency, and quantisation.