What are the hardware requirements for Bge Reranker V2 Gemma Fine Tuning?

Bge Reranker V2 Gemma Fine Tuning requires approximately 10 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Bge Reranker V2 Gemma Fine Tuning and how large is it?

Bge Reranker V2 Gemma Fine Tuning is developed by bespin-global, a model with 2.5b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Bge Reranker V2 Gemma Fine Tuning?

Bge Reranker V2 Gemma Fine Tuning is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Bge Reranker V2 Gemma Fine Tuning by bespin-global — VRAM 10GB, 8K context

Name: Bge Reranker V2 Gemma Fine Tuning
Author: bespin-global

Bge Reranker V2 Gemma Fine Tuning is an open-source language model by bespin-global. Features: 2.5b LLM, VRAM: 10GB, Context: 8K, LLM Explorer Score: 0.12.

Endpoints compatible Gemma Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/bespin-global/bge-reranker-v2-gemma-fine-tuning

Bge Reranker V2 Gemma Fine Tuning Parameters and Internals

LLM Name	Bge Reranker V2 Gemma Fine Tuning
Repository 🤗	https://huggingface.co/bespin-global/bge-reranker-v2-gemma-fine-tuning
Model Size	2.5b
Required VRAM	10 GB
Updated	2026-07-18
Maintainer	bespin-global
Model Type	gemma
Model Files	4.9 GB: 1-of-3 5.0 GB: 2-of-3 0.1 GB: 3-of-3
Model Architecture	GemmaForCausalLM
Context Length	8192
Model Max Length	8192
Transformers Version	4.41.1
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
Vocabulary Size	256000
Torch Data Type	float32

Rank the Bge Reranker V2 Gemma Fine Tuning capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

Best Alternatives to Bge Reranker V2 Gemma Fine Tuning

Best Alternatives	Context / RAM	Downloads
Sherlock Gemma Finetuned	8K / 2.2 GB	6
Geko3	8K / 5.1 GB	7
Gemma Ko V01	8K / 5.1 GB	11
M3 Sft Orca It Base	8K / 10 GB	11
M3 Sft Orca It Base	8K / 10 GB	5
Orca Gemma It DPO	8K / 10 GB	5
Gemma EPFL	8K / 10 GB	5
M3 Sft It DPO	8K / 10 GB	10
M3 Sft Gemma It	8K / 10 GB	9
M3 Sft Gemma	8K / 10 GB	7

Note: green Score (e.g. "73.2") means that the model is better than bespin-global/bge-reranker-v2-gemma-fine-tuning.