What are the hardware requirements for EverythingBagel DPO 7B?

EverythingBagel DPO 7B requires approximately 14.5 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed EverythingBagel DPO 7B and how large is it?

EverythingBagel DPO 7B is developed by OmnicromsBrain, a model with 7b 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 EverythingBagel DPO 7B?

EverythingBagel DPO 7B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

EverythingBagel DPO 7B by OmnicromsBrain — VRAM 14.5GB, 32K context

Name: EverythingBagel DPO 7B
Author: OmnicromsBrain

EverythingBagel DPO 7B is an open-source language model by OmnicromsBrain. Features: 7b LLM, VRAM: 14.5GB, Context: 32K, Merged, LLM Explorer Score: 0.12.

Merged Model Base model:jondurbin/bagel-dpo... Base model:sanjiwatsuki/silico... Conversational Endpoints compatible Jondurbin/bagel-dpo-7b-v0.5 Mistral Region:us Safetensors Sanjiwatsuki/silicon-maid-7b Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/OmnicromsBrain/EverythingBagel-DPO-7B

EverythingBagel DPO 7B Parameters and Internals

LLM Name	EverythingBagel DPO 7B
Repository 🤗	https://huggingface.co/OmnicromsBrain/EverythingBagel-DPO-7B
Base Model(s)	jondurbin/bagel-dpo-7b-v0.5 Silicon Maid 7B jondurbin/bagel-dpo-7b-v0.5 SanjiWatsuki/Silicon-Maid-7B
Merged Model	Yes
Model Size	7b
Required VRAM	14.5 GB
Updated	2026-08-03
Maintainer	OmnicromsBrain
Model Type	mistral
Model Files	9.9 GB: 1-of-2 4.6 GB: 2-of-2
Model Architecture	MistralForCausalLM
Context Length	32768
Model Max Length	32768
Transformers Version	4.40.0
Tokenizer Class	LlamaTokenizer
Padding Token	<unk>
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the EverythingBagel DPO 7B 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 EverythingBagel DPO 7B

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...Nemo Instruct 2407 Abliterated	1000K / 24.5 GB	220	20
MegaBeam Mistral 7B 512K	512K / 14.4 GB	8470	54
SpydazWeb AI HumanAI RP	512K / 14.4 GB	16	1
SpydazWeb AI HumanAI 002	512K / 14.4 GB	18	1
...daz Web AI ChatML 512K Project	512K / 14.5 GB	12	0
MegaBeam Mistral 7B 300K	282K / 14.4 GB	3779	16
MegaBeam Mistral 7B 300K	282K / 14.4 GB	8018	17
Hebrew Mistral 7B 200K	256K / 30 GB	23	15
Astral 256K 7B	250K / 14.4 GB	9	0
Astral 256K 7B V2	250K / 14.4 GB	8	0

Note: green Score (e.g. "73.2") means that the model is better than OmnicromsBrain/EverythingBagel-DPO-7B.