What are the hardware requirements for Mistral Nemo Instruct 2407 GGUF?

Mistral Nemo Instruct 2407 GGUF requires approximately 4.8 GB of VRAM and supports a context window of 1000K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Mistral Nemo Instruct 2407 GGUF and how large is it?

Mistral Nemo Instruct 2407 GGUF is developed by second-state. 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 GGUF?

Mistral Nemo Instruct 2407 GGUF 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 GGUF by second-state — VRAM 4.8GB, 1000K context

Name: Mistral Nemo Instruct 2407 GGUF
Rating: 3.86 (7 reviews)
Author: second-state

Mistral Nemo Instruct 2407 GGUF is an open-source language model by second-state. Features: LLM, VRAM: 4.8GB, Context: 1000K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.14.

Base model:mistralai/mistral-n... Base model:quantized:mistralai... Conversational De En Es Fr Gguf Instruct It Ja Mistral Pt Q2 Quantized Region:us Ru Zh

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

Mistral Nemo Instruct 2407 GGUF Parameters and Internals

LLM Name	Mistral Nemo Instruct 2407 GGUF
Repository 🤗	https://huggingface.co/second-state/Mistral-Nemo-Instruct-2407-GGUF
Model Name	Mistral-Nemo-Instruct-2407
Model Creator	mistralai
Base Model(s)	Mistral Nemo Instruct 2407 mistralai/Mistral-Nemo-Instruct-2407
Required VRAM	4.8 GB
Updated	2026-08-03
Maintainer	second-state
Model Type	mistral
Instruction-Based	Yes
Model Files	4.8 GB 6.6 GB 6.1 GB 5.5 GB 7.1 GB 7.5 GB 7.1 GB 8.5 GB 8.7 GB 8.5 GB 10.1 GB 13.0 GB 24.5 GB
Supported Languages	en fr de es it pt ru zh ja
GGUF Quantization	Yes
Quantization Type	gguf\|q2\|q4_k\|q5_k
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	1024000
Model Max Length	1024000
Transformers Version	4.43.0.dev0
Vocabulary Size	131072
Torch Data Type	bfloat16

Rank the Mistral Nemo Instruct 2407 GGUF 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

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...istral Nemo Instruct 2407 GGUF	1000K / 4.8 GB	1293	11
...istral C64Wizard Instruct GGUF	32K / 4.4 GB	19	0
Equall Saul Instruct V1	32K / 5.1 GB	30	0
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...eZephir Sft Instruct Ead 16bit	32K / 14.4 GB	56	0
... Instruct Unsloth Merged 16bit	4K / 7.6 GB	6	1
... Mini 4K Instruct Bnb 4bit Ita	4K / 7.6 GB	1181	0
... Mini 4K Instruct Bnb 4bit Ita	4K / 7.6 GB	1527	0
...ini New Model With Lora Merged	4K / 7.6 GB	16	0
Phired	4K / 7.6 GB	12	0

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