GPT-NeoX 20B at FP8 (E4M3) needs 20.0 GB for its weights and 90.9 GB in total at 8K context with 8 concurrent users. That means it fits on a single Intel Gaudi 3 128GB. 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× Intel | 128 GB | 90.9 GB | 160.9 | 1931 | 393.4 ms | $0.2878 | ✓ |
| 2× Intel | 256 GB | 90.9 GB | 273.5 | 6564 | 212.2 ms | $0.1693 | ✓ |
| 4× Intel | 512 GB | 90.9 GB | 547.0 | 26255 | 121.1 ms | $0.0846 | ✓ |
| 8× Intel | 1024 GB | 90.9 GB | 1094 | 105019 | 75.6 ms | $0.0423 | ✓ |
| Context | Concurrent users | KV per request | Fits? |
|---|---|---|---|
| 4K | 24 | 4.43 GB | ✓ fits |
| 8K | 12 | 8.86 GB | ✓ fits |
| 33K | 3 | 35.43 GB | ✓ fits |
| 66K | 1 | 70.87 GB | ✓ fits |
| 131K | 0 | 141.73 GB | ✗ does not fit |
| GPU | GPUs | Aggregate tok/s | Cost / 1M tok |
|---|---|---|---|
| RTX 5090 32GB | 4× | 14257 | $0.0390 |
| A100 80GB SXM4 | 2× | 3978 | $0.1676 |
| H100 SXM5 80GB | 2× | 6663 | $0.2084 |
| AMD MI300X 192GB | 1× | 3101 | $0.2240 |
| L40S 48GB | 2× | 1718 | $0.2263 |
| AMD MI325X 288GB | 1× | 3510 | $0.2770 |
Yes. GPT-NeoX 20B at FP8 (E4M3) needs 90.9 GB including the KV cache, and Intel Gaudi 3 128GB has 128 GB — so it fits on a single GPU.
160.9 tokens/sec per stream and 1931 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 393.4 ms, and inter-token latency is 6.2 ms.
$0.2878 per 1M output tokens at 1× Intel Gaudi 3 128GB ($2.00/hr). That is the marginal hardware cost — add idle capacity, ops, and egress for the real figure.
20.0 GB for the weights at FP8 (E4M3), plus 70.9 GB of KV cache for 8 concurrent requests at 8K context — 90.9 GB total. Every extra concurrent user at long context costs more, so leave headroom.
It works. Compare $0.2878 per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 8× RTX 4080 16GB at $0.0292, and the fastest is 4× Cerebras CS-3 (WSE-3) at 159120 tok/s.
Same formulas, your context length, concurrency, and quantisation.