Can you run griffith-bigdata/GRAST-SQL-0.6B-BIRD-Reranker on RTX 4090 24GB?

Yes — griffith-bigdata/GRAST-SQL-0.6B-BIRD-Reranker fits on RTX 4090 24GB: estimated 2.28 GB (weights + KV cache) against 24 GB.

Hugging Bay is intentionally crawlable for search engines, answer engines, user-requested AI fetches, frontier AI assistants, and open-source agents. Public pages describe verified open-source AI artifact metadata, provenance, licenses, community trust signals, and selective hosted mirrors with hashes. Hugging Bay does not bypass gated or restricted upstream access controls.

Machine-readable entrypoints: robots.txt, AI search guidance, well-known AI search JSON, AI citation packs, well-known AI citation JSON, llms.txt, llms-full.txt, AI crawler policy, AI bot allowlist, answer-engine manifest, agent manifest, OpenAPI, and indexing status.

Yes — griffith-bigdata/GRAST-SQL-0.6B-BIRD-Reranker fits on RTX 4090 24GB: estimated 2.28 GB (weights + KV cache) against 24 GB.

Verdict across common GPUs

Next steps

• Open griffith-bigdata/GRAST-SQL-0.6B-BIRD-Reranker on Hugging Bay — trust verdict, hosted files, reviews.
• Machine-readable deployment plan (JSON)
• Raw fit report (JSON)

Methodology: weights + KV-cache estimate from parameter count, quant precision, and declared context. Not a benchmark; runtimes differ. Data recomputed hourly.