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Can I run bge-reranker-v2.5-gemma2-lightweight-gptq on an NVIDIA H100?

Yes

Its published weights (6.17 GB) fit in the 72.0 GB an NVIDIA H100 can use, with room for ≈ 8K tokens of context.

Full analysis of bge-reranker-v2.5-gemma2-lightweight-gptq Everything that runs on NVIDIA H100 Get the weights on Hugging Face
hf download boboliu/bge-reranker-v2.5-gemma2-lightweight-gptq

Files and context on NVIDIA H100

Each file of bge-reranker-v2.5-gemma2-lightweight-gptq (and of GGUF versions the site has analyzed), and how much context fits next to it, with the context cache in 16-bit or 8-bit.

FileSizeOn NVIDIA H100 Context (16-bit)Context (8-bit)
As published6.17 GBFits8K8K
4-bit (estimate)5.20 GBFits8K8K

bge-reranker-v2.5-gemma2-lightweight-gptq on other hardware

Popular models that run on NVIDIA H100

Assumes 90% of the card's memory is usable and at least 4K tokens of context for one conversation, with the context cache in 16-bit unless noted. Fits leaves at least 20% of that memory for context; Tight leaves less.