OLMo 2 13B at FP16 needs 26.0 GB for its weights and 36.7 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 | 36.7 GB | 150.0 | 1800 | 362.6 ms | $0.5401 | ✓ |
| 2× AMD | 576 GB | 36.7 GB | 255.0 | 6120 | 196.9 ms | $0.3177 | ✓ |
| 4× AMD | 1152 GB | 36.7 GB | 510.0 | 24480 | 113.4 ms | $0.1589 | ✓ |
| 8× AMD | 2304 GB | 36.7 GB | 1020 | 97920 | 71.7 ms | $0.0794 | ✓ |
| Context | Concurrent users | KV per request | Fits? |
|---|---|---|---|
| 4K | 390 | 687.2 MB | ✓ fits |
| 8K | 195 | 1.34 GB | ✓ fits |
| 33K | 48 | 5.37 GB | ✓ fits |
| 66K | 24 | 10.74 GB | ✓ fits |
| 131K | 12 | 21.47 GB | ✓ fits |
| GPU | GPUs | Aggregate tok/s | Cost / 1M tok |
|---|---|---|---|
| RTX 5090 32GB | 2× | 1828 | $0.1520 |
| AMD MI300X 192GB | 1× | 1590 | $0.4368 |
| A100 40GB SXM4 | 1× | 465.0 | $0.5376 |
| A100 80GB SXM4 | 1× | 600.0 | $0.5556 |
| Intel Gaudi 3 128GB | 1× | 990.0 | $0.5612 |
| H100 SXM5 80GB | 1× | 1005 | $0.6910 |
Yes. OLMo 2 13B at FP16 needs 36.7 GB including the KV cache, and AMD MI325X 288GB has 288 GB — so it fits on a single GPU.
150.0 tokens/sec per stream and 1800 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 362.6 ms, and inter-token latency is 6.7 ms.
$0.5401 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.
26.0 GB for the weights at FP16, plus 10.7 GB of KV cache for 8 concurrent requests at 8K context — 36.7 GB total. Every extra concurrent user at long context costs more, so leave headroom.
It works. Compare $0.5401 per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 4× RTX 3080 10GB at $0.0717, and the fastest is 1× Cerebras CS-3 (WSE-3) at 6000 tok/s.
Same formulas, your context length, concurrency, and quantisation.