🔌
New: connect Claude & other AIs to GenAIList over MCP — research the catalog and contribute to the shared knowledge base. Learn how →
// RUN ON DATACENTER GPU
Run Pythia-2.8b on Datacenter GPU hardware
13 options ranked by estimated speed at Q4 / 8k context.
| Hardware | Est tok/s | Fits 8k? | Max ctx | ~Price |
|---|---|---|---|---|
| NVIDIA B200 → | ~4,438.8 | yes | 2648k | — |
| AMD Instinct MI325X → | ~2,946.4 | yes | 3547k | — |
| NVIDIA H200 → | ~2,663.3 | yes | 1933k | — |
| AMD Instinct MI300X 192GB → | ~2,602.7 | yes | 2648k | ~$15,000 |
| NVIDIA H100 SXM5 80GB → | ~1,858.7 | yes | 1076k | ~$30,000 |
| Intel Gaudi 3 → | ~1,699 | yes | 1750k | — |
| NVIDIA A100 SXM4 80GB → | ~1,131.3 | yes | 1076k | ~$15,000 |
| NVIDIA H100 PCIe 80GB → | ~1,109.7 | yes | 1076k | ~$25,000 |
| NVIDIA A100 PCIe 80GB → | ~1,073.6 | yes | 1076k | ~$12,000 |
| NVIDIA RTX PRO 6000 Blackwell → | ~994.3 | yes | 1301k | ~$8,500 |
| NVIDIA RTX 6000 Ada 48GB → | ~532.7 | yes | 627k | ~$6,800 |
| NVIDIA L40S 48GB → | ~479.4 | yes | 627k | ~$10,000 |
| AMD Radeon Pro W7900 48GB → | ~424.3 | yes | 627k | ~$3,999 |
Estimate at Q4 (memory-bound). Click any option for its full per-hardware estimate and measured numbers.
FAQ
What Datacenter GPU hardware runs Pythia-2.8b?▶
On GenAIList, 13 Datacenter GPU options can run Pythia-2.8b at Q4 — the fastest is the NVIDIA B200 at ~4,438.8 tok/s.
How fast is Pythia-2.8b on Datacenter GPU hardware?▶
Estimated generation speed ranges from ~424.3 to ~4,438.8 tok/s at Q4 (memory-bandwidth bound). Click any option for its full estimate and any measured numbers.