GPT-OSS 120B (MoE) at AWQ 4-bit needs 64.3 GB for its weights and 66.7 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 | 66.7 GB | 1081 | 12969 | 158.8 ms | $0.0535 | ✓ |
| 2× AMD | 384 GB | 66.7 GB | 1837 | 44096 | 94.5 ms | $0.0315 | ✓ |
| 4× AMD | 768 GB | 66.7 GB | 3675 | 176384 | 62.2 ms | $0.0157 | ✓ |
| 8× AMD | 1536 GB | 66.7 GB | 7349 | 705536 | 46.1 ms | $0.007874 | ✓ |
| Context | Concurrent users | KV per request | Fits? |
|---|---|---|---|
| 4K | 820 | 309.2 MB | ✓ fits |
| 8K | 416 | 618.5 MB | ✓ fits |
| 33K | 105 | 2.42 GB | ✓ fits |
| 66K | 52 | 4.83 GB | ✓ fits |
| 131K | 26 | 9.66 GB | ✓ fits |
| GPU | GPUs | Aggregate tok/s | Cost / 1M tok |
|---|---|---|---|
| RTX 5090 32GB | 4× | 59638 | $0.009316 |
| L40S 48GB | 2× | 7188 | $0.0541 |
| AMD MI325X 288GB | 1× | 14682 | $0.0662 |
| A100 80GB SXM4 | 1× | 4894 | $0.0681 |
| Intel Gaudi 3 128GB | 1× | 8075 | $0.0688 |
| H100 SXM5 80GB | 1× | 8198 | $0.0847 |
Yes. GPT-OSS 120B (MoE) at AWQ 4-bit needs 66.7 GB including the KV cache, and AMD MI300X 192GB has 192 GB — so it fits on a single GPU.
1081 tokens/sec per stream and 12969 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 158.8 ms, and inter-token latency is 925.3 µs.
$0.0535 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.
64.3 GB for the weights at AWQ 4-bit, plus 2.5 GB of KV cache for 8 concurrent requests at 8K context — 66.7 GB total. Every extra concurrent user at long context costs more, so leave headroom.
It works. Compare $0.0535 per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 8× RTX 3080 10GB at $0.004393, and the fastest is 2× Cerebras CS-3 (WSE-3) at 166400 tok/s.
Same formulas, your context length, concurrency, and quantisation.