What are the hardware requirements for Gemma 2B Openhermes?

Gemma 2B Openhermes 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 Gemma 2B Openhermes and how large is it?

Gemma 2B Openhermes is developed by QueryloopAI, a model with 2b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Gemma 2B Openhermes perform on standard benchmarks?

Gemma 2B Openhermes has the following published scores: MMLU 37.7. Compare against reference models on this page or on the LLM Explorer leaderboards.

Gemma 2B Openhermes by QueryloopAI — VRAM 10GB, 8K context

Name: Gemma 2B Openhermes
Author: QueryloopAI

Gemma 2B Openhermes is an open-source language model by QueryloopAI. Features: 2b LLM, VRAM: 10GB, Context: 8K, License: cc-by-nc-4.0, LLM Explorer Score: 0.15, Arc: 43.9, HellaSwag: 62.8, MMLU: 37.7, GSM8K: 5.6.

Axolotl Base model:finetune:google/gem... Base model:google/gemma-2b-it Chatml Conversational Dataset:mlabonne/chatml-openhe... Distillation En Endpoints compatible Feature-extraction Finetuned Gemma Generated from trainer Gpt4 Instruct Region:us Safetensors Sharded Synthetic data Tensorflow

Model Card on HF 🤗: https://huggingface.co/QueryloopAI/gemma-2b-openhermes

Gemma 2B Openhermes Parameters and Internals

Model Type

text generation, instruct, chatml

Use Cases

Areas:

research, non-commercial applications

Primary Use Cases:

chat-style interactions, language model tasks

Considerations:

Intended for non-commercial use, model is contingent on a chat template for conversational applications.

Additional Notes

Model integrates Axolotl's customization features for enhanced performance.

Supported Languages

en (English)

Training Details

Data Sources:

mlabonne/chatml-OpenHermes2.5-dpo-binarized-alpha

Methodology:

Fine-tuned on the OpenHermes-2.5 preference dataset using QLoRA.

Context Length:

1800

Hardware Used:

cuda (GPU)

Input Output

Input Format:

Text string input, structured for chat if needed.

Accepted Modalities:

text

Output Format:

Generated English text response.

Performance Tips:

Use chat template as recommended for optimal performance in conversational tasks.

LLM Name	Gemma 2B Openhermes
Repository 🤗	https://huggingface.co/QueryloopAI/gemma-2b-openhermes
Base Model(s)	Gemma 2B It google/gemma-2b-it
Model Size	2b
Required VRAM	10 GB
Updated	2026-07-26
Maintainer	QueryloopAI
Model Type	gemma
Model Files	4.9 GB: 1-of-3 5.0 GB: 2-of-3 0.1 GB: 3-of-3
Supported Languages	en
Model Architecture	GemmaModel
License	cc-by-nc-4.0
Context Length	8192
Model Max Length	8192
Transformers Version	4.38.2
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
Vocabulary Size	256000
Torch Data Type	float32

Rank the Gemma 2B Openhermes capabilities

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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 Gemma 2B Openhermes

Best Alternatives	Context / RAM	Downloads	Likes
Gemma 2B Def	8K / 2.2 GB	11	0

Note: green Score (e.g. "73.2") means that the model is better than QueryloopAI/gemma-2b-openhermes.