What are the hardware requirements for Mistral Nemo Instruct 2407?

Mistral Nemo Instruct 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 Instruct 2407 and how large is it?

Mistral Nemo Instruct 2407 is developed by unsloth, 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 Instruct 2407?

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

Mistral Nemo Instruct 2407 by unsloth — VRAM 24.5GB, 128K context

Name: Mistral Nemo Instruct 2407
Author: unsloth

Mistral Nemo Instruct 2407 is an open-source language model by unsloth. Features: 12.2b LLM, VRAM: 24.5GB, Context: 128K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.15.

Conversational Deploy:azure En Endpoints compatible Instruct Mistral Region:us Safetensors Sharded Tensorflow Unsloth

Model Card on HF 🤗: https://huggingface.co/unsloth/Mistral-Nemo-Instruct-2407

Mistral Nemo Instruct 2407 Parameters and Internals

LLM Name	Mistral Nemo Instruct 2407
Repository 🤗	https://huggingface.co/unsloth/Mistral-Nemo-Instruct-2407
Model Size	12.2b
Required VRAM	24.5 GB
Updated	2026-07-23
Maintainer	unsloth
Model Type	mistral
Instruction-Based	Yes
Model Files	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
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	131072
Model Max Length	131072
Transformers Version	4.49.0.dev0
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<pad>
Vocabulary Size	131072
Torch Data Type	bfloat16

Rank the Mistral Nemo Instruct 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

Best Alternatives to Mistral Nemo Instruct 2407

Best Alternatives	Context / RAM	Downloads	Likes
...istral Nemo Instruct 2407 MPOA	1000K / 24.5 GB	37	3
...ish Mistral Nemo Instruct 2407	1000K / 24.5 GB	77	2
Mistral Nemo Kurdish	1000K / 24.5 GB	37	3
Violet Twilight V0.2	1000K / 24.5 GB	66	49
Kalypso	1000K / 24.5 GB	45	24
Crimson Dawn V0.2	1000K / 24.5 GB	17	13
Azure Dusk V0.2	1000K / 24.5 GB	43	10
...al Nemo Japanese Instruct 2408	1000K / 24.5 GB	2358	49
Mistral Nemo Instruct 2407 FP8	1000K / 13.6 GB	4691	19
Educa Ai Nemo Sft	1000K / 49.3 GB	13	4

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