What hardware do I need if I want to try scaling LLM inference infrastructure locally before deploying everything to AWS or GCP
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The searches the AI actually ran for this prompt.
SEED QUERY
What hardware do I need if I want to try scaling LLM inference infrastructure locally before deploying everything to AWS or GCP
3 real searches · 1 real-search pass
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
ChatGPT real searches (3)
Classes come from the query-classifier (a local Laya model). 3 of 3 calls are low-confidence (under 50%) — hover a query in the table to see its confidence.
Searches and sources
ChatGPT3 real searches · gpt-6
vLLM hardware requirements GPU memory tensor parallelism documentation 2026 Google ↗
NVIDIA RTX 5090 specifications 32GB memory official Google ↗
NVIDIA RTX PRO 6000 Blackwell workstation edition 96GB official specifications Google ↗
- Parallelism and Scaling · docs.vllm.ai
- vLLM · huggingface.co
Queries
3 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
vLLM hardware requirements GPU memory tensor parallelism documentation 2026 OBSERVED | Google ↗ AI Mode ↗ | — | Instruction | — | — | 1x of 1 | |
NVIDIA RTX 5090 specifications 32GB memory official OBSERVED | Google ↗ AI Mode ↗ | — | Other / navigational | — | — | 1x of 1 | |
NVIDIA RTX PRO 6000 Blackwell workstation edition 96GB official specifications OBSERVED | Google ↗ AI Mode ↗ | — | Definition | — | — | 1x of 1 |