What are the hardware requirements for Mistral Nemo Base 2407?

Mistral Nemo Base 2407 requires approximately 24.5 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Mistral Nemo Base 2407 and how large is it?

Mistral Nemo Base 2407 is developed by mistralai, a model with 12.2b 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 Mistral Nemo Base 2407?

Mistral Nemo Base 2407 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Mistral Nemo Base 2407 by mistralai — VRAM 24.5GB, 128K context

Name: Mistral Nemo Base 2407
Author: mistralai

Mistral Nemo Base 2407 is an open-source language model by mistralai. Features: 12.2b LLM, VRAM: 24.5GB, Context: 128K, License: MNPL-0.1, LLM Explorer Score: 0.24.

De En Es Eval-results Fr It Ja Mistral Mistral-common Pt Region:us Ru Safetensors Sharded Tensorflow Vllm Zh

Model Card on HF 🤗: https://huggingface.co/mistralai/Mistral-Nemo-Base-2407

Mistral Nemo Base 2407 Parameters and Internals

Model Type

generative text

Use Cases

Areas:

research, commercial applications

Additional Notes

Mistral-Nemo-Base-2407 is a pretrained base model and does not have moderation mechanisms.

Supported Languages

en (English), fr (French), de (German), es (Spanish), it (Italian), pt (Portuguese), ru (Russian), zh (Chinese), ja (Japanese)

Training Details

Data Sources:

multilingual and code data

Methodology:

pretrained base

Context Length:

128000

Model Architecture:

transformer

Input Output

Accepted Modalities:

text

Performance Tips:

Use a temperature of 0.3 for optimal performance.

LLM Name	Mistral Nemo Base 2407
Repository 🤗	https://huggingface.co/mistralai/Mistral-Nemo-Base-2407
Model Size	12.2b
Required VRAM	24.5 GB
Updated	2026-07-04
Maintainer	mistralai
Model Files	24.5 GB 4.9 GB: 1-of-5 4.9 GB: 2-of-5 4.9 GB: 3-of-5 4.9 GB: 4-of-5 4.9 GB: 5-of-5
Supported Languages	en fr de es it pt ru zh ja
Model Architecture	MambaSSM
License	MNPL-0.1
Context Length	131072
Model Max Length	131072
Tokenizer Class	PreTrainedTokenizerFast
Vocabulary Size	131072

Rank the Mistral Nemo Base 2407 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

Quantized Models of the Mistral Nemo Base 2407

Model	Likes	Downloads	VRAM
Normistral 11B Warm	11	240	22 GB

Best Alternatives to Mistral Nemo Base 2407

Best Alternatives	Context / RAM	Downloads	Likes
Mistral Nemo Instruct 2407	128K / 24.5 GB	258592	1687
... Instruct 2407 Absolute Heresy	128K / 24.5 GB	119	4
MistralAI Nemo Instruct ChatML	0K / 24.5 GB	3	2
...Nemo Instruct 2407 Abliterated	0K / 24.5 GB	86	3

Note: green Score (e.g. "73.2") means that the model is better than mistralai/Mistral-Nemo-Base-2407.