Qwen 3 30B-A3B (MoE) at FP8 (E4M3) needs 30.0 GB for its weights and 36.4 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 | 36.4 GB | 1723 | 20670 | 105.8 ms | $0.0336 | ✓ |
| 2× AMD | 384 GB | 36.4 GB | 2928 | 70278 | 67.9 ms | $0.0198 | ✓ |
| 4× AMD | 768 GB | 36.4 GB | 5857 | 281112 | 49.0 ms | $0.009881 | ✓ |
| 8× AMD | 1536 GB | 36.4 GB | 11713 | 1124448 | 39.5 ms | $0.004941 | ✓ |
| Context | Concurrent users | KV per request | Fits? |
|---|---|---|---|
| 4K | 402 | 412.3 MB | ✓ fits |
| 8K | 201 | 824.6 MB | ✓ fits |
| 33K | 50 | 3.22 GB | ✓ fits |
| 66K | 25 | 6.44 GB | ✓ fits |
| 131K | 12 | 12.88 GB | ✓ fits |
| GPU | GPUs | Aggregate tok/s | Cost / 1M tok |
|---|---|---|---|
| RTX 5090 32GB | 2× | 23762 | $0.0117 |
| A100 40GB SXM4 | 1× | 6045 | $0.0414 |
| AMD MI325X 288GB | 1× | 23400 | $0.0415 |
| A100 80GB SXM4 | 1× | 7800 | $0.0427 |
| Intel Gaudi 3 128GB | 1× | 12870 | $0.0432 |
| H100 SXM5 80GB | 1× | 13065 | $0.0532 |
Yes. Qwen 3 30B-A3B (MoE) at FP8 (E4M3) needs 36.4 GB including the KV cache, and AMD MI300X 192GB has 192 GB — so it fits on a single GPU.
1723 tokens/sec per stream and 20670 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 105.8 ms, and inter-token latency is 580.6 µs.
$0.0336 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.
30.0 GB for the weights at FP8 (E4M3), plus 6.4 GB of KV cache for 8 concurrent requests at 8K context — 36.4 GB total. Every extra concurrent user at long context costs more, so leave headroom.
It works. Compare $0.0336 per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 4× RTX 3080 10GB at $0.005513, and the fastest is 1× Cerebras CS-3 (WSE-3) at 78000 tok/s.
Same formulas, your context length, concurrency, and quantisation.