Qwen 3 8B at FP16 needs 16.0 GB for its weights and 25.7 GB in total at 8K context with 8 concurrent users. That means it fits on a single AMD MI300X 192GB. 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 | 192 GB | 25.7 GB | 215.3 | 2584 | 235.2 ms | $0.2688 | ✓ |
| 2× AMD | 384 GB | 25.7 GB | 366.0 | 8785 | 133.0 ms | $0.1581 | ✓ |
| 4× AMD | 768 GB | 25.7 GB | 732.1 | 35139 | 81.5 ms | $0.0791 | ✓ |
| 8× AMD | 1536 GB | 25.7 GB | 1464 | 140556 | 55.8 ms | $0.0395 | ✓ |
| Context | Concurrent users | KV per request | Fits? |
|---|---|---|---|
| 4K | 291 | 618.5 MB | ✓ fits |
| 8K | 145 | 1.21 GB | ✓ fits |
| 33K | 36 | 4.83 GB | ✓ fits |
| 66K | 18 | 9.66 GB | ✓ fits |
| 131K | 9 | 19.33 GB | ✓ fits |
| GPU | GPUs | Aggregate tok/s | Cost / 1M tok |
|---|---|---|---|
| RTX 5090 32GB | 1× | 873.6 | $0.1590 |
| V100 SXM2 32GB | 1× | 438.8 | $0.3166 |
| A100 40GB SXM4 | 1× | 755.6 | $0.3309 |
| AMD MI325X 288GB | 1× | 2925 | $0.3324 |
| A100 80GB SXM4 | 1× | 975.0 | $0.3419 |
| Intel Gaudi 3 128GB | 1× | 1609 | $0.3453 |
Yes. Qwen 3 8B at FP16 needs 25.7 GB including the KV cache, and AMD MI300X 192GB has 192 GB — so it fits on a single GPU.
215.3 tokens/sec per stream and 2584 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 235.2 ms, and inter-token latency is 4.6 ms.
$0.2688 per 1M output tokens at 1× AMD MI300X 192GB ($2.50/hr). That is the marginal hardware cost — add idle capacity, ops, and egress for the real figure.
16.0 GB for the weights at FP16, plus 9.7 GB of KV cache for 8 concurrent requests at 8K context — 25.7 GB total. Every extra concurrent user at long context costs more, so leave headroom.
It works. Compare $0.2688 per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 4× RTX 3080 10GB at $0.0441, and the fastest is 1× Cerebras CS-3 (WSE-3) at 9750 tok/s.
Same formulas, your context length, concurrency, and quantisation.