What are the hardware requirements for Mistral 7B V0.3?

Mistral 7B V0.3 requires approximately 14.5 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 Mistral 7B V0.3 and how large is it?

Mistral 7B V0.3 is developed by MaziyarPanahi, 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 7B V0.3 perform on standard benchmarks?

Mistral 7B V0.3 has the following published scores: MMLU 63.7. Compare against reference models on this page or on the LLM Explorer leaderboards.

Mistral 7B V0.3 by MaziyarPanahi — VRAM 14.5GB, 32K context

Name: Mistral 7B V0.3
Author: MaziyarPanahi

Mistral 7B V0.3 is an open-source language model by MaziyarPanahi. Features: 7b LLM, VRAM: 14.5GB, Context: 32K, License: apache-2.0, LLM Explorer Score: 0.16, Arc: 60.7, HellaSwag: 83, MMLU: 63.7, GSM8K: 35.

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

Model Card on HF 🤗: https://huggingface.co/MaziyarPanahi/Mistral-7B-v0.3

Mistral 7B V0.3 Parameters and Internals

Model Type

large language model

Use Cases

Primary Use Cases:

text generation

Limitations:

Does not have any moderation mechanisms.

Considerations:

Looking forward to engaging with the community on ways to make the model finely respect guardrails, allowing for deployment in environments requiring moderated outputs.

Additional Notes

The model extends the vocabulary to 32768 words compared to its predecessor, Mistral-7B-v0.2.

Responsible Ai Considerations

Mitigation Strategies:

The model does not have any moderation mechanisms.

LLM Name	Mistral 7B V0.3
Repository 🤗	https://huggingface.co/MaziyarPanahi/Mistral-7B-v0.3
Model Size	7b
Required VRAM	14.5 GB
Updated	2026-07-31
Maintainer	MaziyarPanahi
Model Type	mistral
Model Files	5.0 GB: 1-of-3 5.0 GB: 2-of-3 4.5 GB: 3-of-3
Model Architecture	AutoModelForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.42.0.dev0
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32768
Torch Data Type	bfloat16

Rank the Mistral 7B V0.3 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

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