What are the hardware requirements for Multilingual Mistral?

Multilingual Mistral requires approximately 93.5 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 Multilingual Mistral and how large is it?

Multilingual Mistral is developed by gagan3012, 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 Multilingual Mistral perform on standard benchmarks?

Multilingual Mistral has the following published scores: MMLU 61.38. Compare against reference models on this page or on the LLM Explorer leaderboards.

Multilingual Mistral by gagan3012 — VRAM 93.5GB, 32K context

Name: Multilingual Mistral
Author: gagan3012

Multilingual Mistral is an open-source language model by gagan3012. Features: 7b LLM, VRAM: 93.5GB, Context: 32K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.12, Arc: 62.3, HellaSwag: 81.8, MMLU: 61.4, GSM8K: 40.3.

Azale-ai/starstreak-7b-beta Conversational Davidkim205/komt-mistral-7b-v1 Endpoints compatible Gagan3012/mistral arabic dpo Giux78/zefiro-7b-beta-ita-v0.1 Instruct Manishiitg/open-aditi-hi-v1 Mixtral Model-index Moe Openbuddy/openbuddy-zephyr-7b-... Openchat/openchat-3.5-0106 Region:us Safetensors Sharded Tensorflow Vagosolutions/sauerkrautlm-7b-...

Model Card on HF 🤗: https://huggingface.co/gagan3012/Multilingual-mistral

Multilingual Mistral Parameters and Internals

Model Type

text-generation

LLM Name	Multilingual Mistral
Repository 🤗	https://huggingface.co/gagan3012/Multilingual-mistral
Model Size	7b
Required VRAM	93.5 GB
Updated	2026-07-18
Maintainer	gagan3012
Model Type	mixtral
Instruction-Based	Yes
Model Files	9.9 GB: 1-of-10 10.0 GB: 2-of-10 10.0 GB: 3-of-10 10.0 GB: 4-of-10 10.0 GB: 5-of-10 10.0 GB: 6-of-10 10.0 GB: 7-of-10 10.0 GB: 8-of-10 10.0 GB: 9-of-10 3.6 GB: 10-of-10
Model Architecture	MixtralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.36.2
Tokenizer Class	LlamaTokenizer
Padding Token	<s>
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the Multilingual Mistral 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 Multilingual Mistral

Best Alternatives	Context / RAM	Downloads	Likes
Mini Mixtral V0.2	32K / 25.8 GB	3923	4
OpenMistral MoE	32K / 48.3 GB	1218	0
Magiq 3	32K / 37.1 GB	5	3
FNCARL9000	32K / 48.3 GB	8	0
Bigstral 12B 32K 8xMoE	32K / 163.3 GB	12	2
CollAIborate4x7B	32K / 48.7 GB	6	1
CollAIborate4x7B	32K / 48.7 GB	1	1
OpenMistral MoE	32K / 48.3 GB	6	0
...t V0.2 2x7B MoE 6.0bpw H6 EXL2	32K / 9.9 GB	3	1

Note: green Score (e.g. "73.2") means that the model is better than gagan3012/Multilingual-mistral.