What are the hardware requirements for Zephyr 7B Beta?

Zephyr 7B 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 Zephyr 7B Beta and how large is it?

Zephyr 7B Beta is developed by HuggingFaceH4, 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 Zephyr 7B Beta perform on standard benchmarks?

Zephyr 7B Beta has the following published scores: MMLU 61.06, LMSYS ELO 1068. Compare against reference models on this page or on the LLM Explorer leaderboards.

Zephyr 7B Beta by HuggingFaceH4 — VRAM 14.4GB, 32K context

Name: Zephyr 7B Beta
Rating: 3 (2 reviews)
Author: HuggingFaceH4

Zephyr 7B Beta is an open-source language model by HuggingFaceH4. Features: 7b LLM, VRAM: 14.4GB, Context: 32K, License: mit, LLM Explorer Score: 0.41, ELO: 1068, Arc: 62, HellaSwag: 84.5, MMLU: 61.1, GSM8K: 11.4.

Arxiv:2305.14233 Arxiv:2305.18290 Arxiv:2310.01377 Arxiv:2310.16944 Base model:finetune:mistralai/... Base model:mistralai/mistral-7... Conversational Dataset:huggingfaceh4/ultracha... Dataset:huggingfaceh4/ultrafee... Deploy:azure En Endpoints compatible Generated from trainer Mistral Model-index Pytorch Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/HuggingFaceH4/zephyr-7b-beta

Zephyr 7B Beta Benchmarks

LMSys ELO: 1068 vs 1272 (so35)^-16%

ARC: 62.03 vs 96.7 (so35)^-35.9%

HellaSwag: 84.53 vs 95.3 (gpt4)^-11.3%

MMLU: 61.06 vs 88.3 (so35)^-30.8%

GSM8K: 11.37 vs 96.4 (so35)^-88.2%

LLME Score: 0.41141

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

Zephyr 7B Beta (HuggingFaceH4/zephyr-7b-beta)

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Zephyr 7B Beta Parameters and Internals

Model Type

text generation, chatbot

Use Cases

Areas:

chat

Applications:

assistant

Primary Use Cases:

chatbot applications

Limitations:

not aligned to human preferences for safety within the RLHF phase, can produce problematic outputs when prompted

Additional Notes

Zephyr-7B-β can produce problematic outputs, especially when prompted, due to the lack of human preference alignment and in-the-loop filtering.

Supported Languages

en (primary)

Training Details

Data Sources:

HuggingFaceH4/ultrachat_200k, HuggingFaceH4/ultrafeedback_binarized

Methodology:

Direct Preference Optimization (DPO)

Input Output

Input Format:

structured message input format (role-based behavior)

Accepted Modalities:

text

Output Format:

text generation output

Performance Tips:

Direct Preference Optimization (DPO) improves performance.

LLM Name	Zephyr 7B Beta
Repository 🤗	https://huggingface.co/HuggingFaceH4/zephyr-7b-beta
Base Model(s)	mistralai/Mistral-7B-v0.1 mistralai/Mistral-7B-v0.1
Model Size	7b
Required VRAM	14.4 GB
Updated	2026-05-29
Maintainer	HuggingFaceH4
Model Type	mistral
Model Files	1.9 GB: 1-of-8 1.9 GB: 2-of-8 2.0 GB: 3-of-8 1.9 GB: 4-of-8 2.0 GB: 5-of-8 1.9 GB: 6-of-8 2.0 GB: 7-of-8 0.8 GB: 8-of-8 1.9 GB: 1-of-8 1.9 GB: 2-of-8 2.0 GB: 3-of-8 1.9 GB: 4-of-8 2.0 GB: 5-of-8 1.9 GB: 6-of-8 2.0 GB: 7-of-8 0.8 GB: 8-of-8
Supported Languages	en
Model Architecture	MistralForCausalLM
License	mit
Context Length	32768
Model Max Length	32768
Transformers Version	4.35.0
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	32000
Torch Data Type	bfloat16

Quantized Models of the Zephyr 7B Beta

Model	Likes	Downloads	VRAM
Zephyr 7B Beta Marlin	0	30	4 GB
Dj Zephyr 7B Q5 K M GGUF	0	31	5 GB
Dj Zephyr 7B F16 GGUF	1	24	14 GB
Zephyr 7B Beta GGUF	231	2355	3 GB
Zephyr 7B Beta GGUF	0	803	2 GB
Zephyr 7B Beta GGUF	0	470	3 GB
Zephyr 7B Beta Marlin	0	126	4 GB
Zephyr 7B Beta GPTQ	1	11	4 GB
Vietzephyr 7B Lora 8bit	0	7	0 GB
Zephyr 7B Beta Agent Instruct	1	8	0 GB

Best Alternatives to Zephyr 7B Beta

Best Alternatives	Context / RAM	Downloads	Likes
...Nemo Instruct 2407 Abliterated	1000K / 24.5 GB	134	20
MegaBeam Mistral 7B 512K	512K / 14.4 GB	8631	54
SpydazWeb AI HumanAI RP	512K / 14.4 GB	24	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	8176	17
Hebrew Mistral 7B 200K	256K / 30 GB	1378	15
Astral 256K 7B V2	250K / 14.4 GB	5	0
Astral 256K 7B	250K / 14.4 GB	5	0

Rank the Zephyr 7B Beta Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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

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Release v20260328a

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Zephyr 7B Beta by HuggingFaceH4