What are the hardware requirements for Mistral Orpo Beta?

Mistral Orpo Beta requires approximately 14.4 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 Mistral Orpo Beta and how large is it?

Mistral Orpo Beta is developed by kaist-ai, a model with 7b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Mistral Orpo Beta perform on standard benchmarks?

Mistral Orpo Beta has the following published scores: MMLU 63.26. Compare against reference models on this page or on the LLM Explorer leaderboards.

Mistral Orpo Beta by kaist-ai — VRAM 14.4GB, 32K context

Name: Mistral Orpo Beta
Author: kaist-ai

Mistral Orpo Beta is an open-source language model by kaist-ai. Features: 7b LLM, VRAM: 14.4GB, Context: 32K, License: mit, LLM Explorer Score: 0.13, Arc: 61.2, HellaSwag: 84, MMLU: 63.3, GSM8K: 39.8.

Arxiv:2403.07691 Base model:finetune:mistralai/... Base model:mistralai/mistral-7... Conversational Dataset:argilla/ultrafeedback-... En Endpoints compatible Mistral Model-index Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/kaist-ai/mistral-orpo-beta

Mistral Orpo Beta Parameters and Internals

Model Type

text-generation

Additional Notes

Mistral-ORPO is a fine-tuned version of mistralai/Mistral-7B-v0.1 using ORPO, learning preference directly without supervised fine-tuning warmup.

Training Details

Data Sources:

argilla/ultrafeedback-binarized-preferences-cleaned

Data Volume:

61k instances

Methodology:

Odds Ratio Preference Optimization (ORPO)

LLM Name	Mistral Orpo Beta
Repository 🤗	https://huggingface.co/kaist-ai/mistral-orpo-beta
Base Model(s)	mistralai/Mistral-7B-v0.1 mistralai/Mistral-7B-v0.1
Model Size	7b
Required VRAM	14.4 GB
Updated	2026-08-05
Maintainer	kaist-ai
Model Type	mistral
Model Files	4.9 GB: 1-of-3 5.0 GB: 2-of-3 4.5 GB: 3-of-3
Supported Languages	en
Model Architecture	MistralForCausalLM
License	mit
Context Length	32768
Model Max Length	32768
Transformers Version	4.38.2
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the Mistral Orpo Beta 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 Mistral Orpo Beta

Best Alternatives	Context / RAM	Downloads	Likes
...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 kaist-ai/mistral-orpo-beta.