What are the hardware requirements for Zephyr Sft?

Zephyr Sft 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 Sft and how large is it?

Zephyr Sft is developed by unsloth, a model with 7.2b 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 Zephyr Sft?

Zephyr Sft is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Zephyr Sft by unsloth — VRAM 14.4GB, 32K context

Name: Zephyr Sft
Author: unsloth

Zephyr Sft is an open-source language model by unsloth. Features: 7.2b LLM, VRAM: 14.4GB, Context: 32K, License: apache-2.0, LLM Explorer Score: 0.11.

Conversational En Endpoints compatible Mistral Region:us Safetensors Sft Sharded Tensorflow Unsloth Zephyr

Model Card on HF 🤗: https://huggingface.co/unsloth/zephyr-sft

Zephyr Sft Benchmarks

LLME Score: 0.11018

^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)

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Zephyr Sft Parameters and Internals

Model Type

text generation

Use Cases

Applications:

Research, Commercial Applications

Additional Notes

All notebooks are beginner-friendly, allowing for quick finetuning with added datasets and exporting capabilities.

LLM Name	Zephyr Sft
Repository 🤗	https://huggingface.co/unsloth/zephyr-sft
Model Size	7.2b
Required VRAM	14.4 GB
Updated	2026-05-06
Maintainer	unsloth
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	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.44.2
Tokenizer Class	LlamaTokenizer
Padding Token	<unk>
Vocabulary Size	32000
Torch Data Type	bfloat16

Quantized Models of the Zephyr Sft

Model	Likes	Downloads	VRAM
Zephyr DPO 4bit	0	90	4 GB
Rezephyr Merged 4bit	0	61	4 GB

Best Alternatives to Zephyr Sft

Best Alternatives	Context / RAM	Downloads	Likes
...Web AI HumanAI 012 INSTRUCT XA	512K / 14.4 GB	9	0
...Web AI HumanAI 012 INSTRUCT IA	512K / 14.4 GB	8	0
...Web AI HumanAI 011 INSTRUCT ML	512K / 14.4 GB	7	0
14	512K / 14.5 GB	319	0
SpydazWeb HumanAI M2	512K / GB	38	0
...dazWeb AI HumanAI 011 INSTRUCT	512K / 14.4 GB	14	1
SpydazWeb AI HumanAI 009 CHAT	512K / 14.4 GB	6	0
SpydazWeb AI HumanAI 007	512K / 14.4 GB	5	0
...Web AI HumanAI 012 INSTRUCT MX	512K / 14.4 GB	8	0
SpydazWeb AI HumanAI 010 CHAT	512K / 14.4 GB	7	0

Note: green Score (e.g. "73.2") means that the model is better than unsloth/zephyr-sft.

Rank the Zephyr Sft 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 Sft by unsloth