Can I run bge-reranker-v2.5-gemma2-lightweight-gptq on an RTX 3060 12 GB?

Yes

Its published weights (6.17 GB) fit in the 10.8 GB an RTX 3060 12 GB can use, with room for ≈ 8K tokens of context.

Full analysis of bge-reranker-v2.5-gemma2-lightweight-gptq Everything that runs on RTX 3060 12 GB Get the weights on Hugging Face

hf download boboliu/bge-reranker-v2.5-gemma2-lightweight-gptq

Files and context on RTX 3060 12 GB

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.

File	Size	On RTX 3060 12 GB	Context (16-bit)	Context (8-bit)
As published	6.17 GB	Fits	8K	8K
4-bit (estimate)	5.20 GB	Fits	8K	8K

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

NVIDIA H100Yes
RTX 5090Yes
RTX 4090Yes
RTX 3090Yes
RTX 5060 Ti 16 GBYes
RTX 3060 12 GBYes
RTX 4060Probably, at 4-bit
Mac with 32 GBYes
Mac with 64 GBYes
Mac with 128 GBYes

Popular models that run on RTX 3060 12 GB

Qwen3-0.6BQwen · 752M
gpt2openai-community · 137M
Qwen3-Coder-30B-A3B-Instruct-GGUFunsloth · 30.5B
Qwen2.5-0.5B-InstructQwen · 494M
Qwen2.5-1.5B-InstructQwen · 1.54B
Qwen3-4BQwen · 4.02B
Qwen3.5-4BQwen · 4.66B
Ornith-1.5-9B-GGUFornith-ai · 9.20B

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.