Mistral Large 3 (256K) at AWQ 4-bit needs 129.3 GB for its weights and 150.2 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 | 150.2 GB | 87.89 | 1055 | 1.82 s | $0.9218 | ✓ |
| 2× AMD | 576 GB | 150.2 GB | 149.4 | 3586 | 926.7 ms | $0.5423 | ✓ |
| 4× AMD | 1152 GB | 150.2 GB | 298.8 | 14343 | 478.4 ms | $0.2711 | ✓ |
| 8× AMD | 2304 GB | 150.2 GB | 597.6 | 57373 | 254.2 ms | $0.1356 | ✓ |
| Context | Concurrent users | KV per request | Fits? |
|---|---|---|---|
| 4K | 121 | 1.31 GB | ✓ fits |
| 8K | 60 | 2.62 GB | ✓ fits |
| 33K | 15 | 10.47 GB | ✓ fits |
| 66K | 7 | 20.94 GB | ✓ fits |
| 131K | 3 | 41.88 GB | ✓ fits |
| GPU | GPUs | Aggregate tok/s | Cost / 1M tok |
|---|---|---|---|
| RTX 5090 32GB | 8× | 17135 | $0.0648 |
| L40S 48GB | 4× | 2065 | $0.3766 |
| A100 80GB SXM4 | 2× | 1195 | $0.5578 |
| H100 SXM5 80GB | 2× | 2002 | $0.6937 |
| AMD MI300X 192GB | 1× | 931.6 | $0.7454 |
| H200 SXM5 141GB | 2× | 2869 | $0.7747 |
Yes. Mistral Large 3 (256K) at AWQ 4-bit needs 150.2 GB including the KV cache, and AMD MI325X 288GB has 288 GB — so it fits on a single GPU.
87.89 tokens/sec per stream and 1055 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 1.82 s, and inter-token latency is 11.4 ms.
$0.9218 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.
129.3 GB for the weights at AWQ 4-bit, plus 20.9 GB of KV cache for 8 concurrent requests at 8K context — 150.2 GB total. Every extra concurrent user at long context costs more, so leave headroom.
It works. Compare $0.9218 per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 8× RTX 5090 32GB at $0.0648, and the fastest is 4× Cerebras CS-3 (WSE-3) at 47811 tok/s.
Same formulas, your context length, concurrency, and quantisation.