What are the hardware requirements for Hebrew Mistral 7B 200K?

Hebrew Mistral 7B 200K requires approximately 30 GB of VRAM and supports a context window of 256K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Hebrew Mistral 7B 200K and how large is it?

Hebrew Mistral 7B 200K is developed by yam-peleg, 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 Hebrew Mistral 7B 200K?

Hebrew Mistral 7B 200K is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Hebrew Mistral 7B 200K by yam-peleg — VRAM 30GB, 256K context

Name: Hebrew Mistral 7B 200K
Author: yam-peleg

Hebrew Mistral 7B 200K is an open-source language model by yam-peleg. Features: 7b LLM, VRAM: 30GB, Context: 256K, License: apache-2.0, LLM Explorer Score: 0.14.

Deploy:azure En Endpoints compatible He Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/yam-peleg/Hebrew-Mistral-7B-200K

Hebrew Mistral 7B 200K Parameters and Internals

Model Type

causal language model

Additional Notes

Model is focused on Hebrew language understanding and generation. It lacks moderation mechanisms.

Supported Languages

en (full proficiency), he (full proficiency)

Training Details

Context Length:

200000

Input Output

Input Format:

Text inputs using AutoTokenizer from the Transformers library.

Accepted Modalities:

text

Output Format:

Generated text responses decoded back from outputs.

LLM Name	Hebrew Mistral 7B 200K
Repository 🤗	https://huggingface.co/yam-peleg/Hebrew-Mistral-7B-200K
Model Size	7b
Required VRAM	30 GB
Updated	2026-07-30
Maintainer	yam-peleg
Model Type	mistral
Model Files	4.9 GB: 1-of-7 5.0 GB: 2-of-7 4.8 GB: 3-of-7 5.0 GB: 4-of-7 5.0 GB: 5-of-7 4.2 GB: 6-of-7 1.1 GB: 7-of-7
Supported Languages	en he
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	262144
Model Max Length	262144
Transformers Version	4.40.1
Tokenizer Class	LlamaTokenizer
Padding Token	[PAD]
Vocabulary Size	64001
Torch Data Type	float32

Rank the Hebrew Mistral 7B 200K 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 Hebrew Mistral 7B 200K

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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
Astral 256K 7B	250K / 14.4 GB	9	0
Astral 256K 7B V2	250K / 14.4 GB	8	0
Test001	128K / 14.5 GB	9	0

Note: green Score (e.g. "73.2") means that the model is better than yam-peleg/Hebrew-Mistral-7B-200K.