What are the hardware requirements for Mistral Nemo InstructContinuedFine?

Mistral Nemo InstructContinuedFine requires approximately 24.5 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 InstructContinuedFine and how large is it?

Mistral Nemo InstructContinuedFine is developed by AlSamCur123, 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 InstructContinuedFine?

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

Mistral Nemo InstructContinuedFine by AlSamCur123 — VRAM 24.5GB, 1000K context

Name: Mistral Nemo InstructContinuedFine
Author: AlSamCur123

Mistral Nemo InstructContinuedFine is an open-source language model by AlSamCur123. Features: 12.2b LLM, VRAM: 24.5GB, Context: 1000K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.15.

4bit Base model:quantized:unsloth/m... Base model:unsloth/mistral-nem... Conversational En Endpoints compatible Gguf Instruct Mistral Quantized Region:us Safetensors Sft Sharded Tensorflow Trl Unsloth

Model Card on HF 🤗: https://huggingface.co/AlSamCur123/Mistral-Nemo-InstructContinuedFine

Mistral Nemo InstructContinuedFine Parameters and Internals

LLM Name	Mistral Nemo InstructContinuedFine
Repository 🤗	https://huggingface.co/AlSamCur123/Mistral-Nemo-InstructContinuedFine
Base Model(s)	...al Nemo Instruct 2407 Bnb 4bit unsloth/Mistral-Nemo-Instruct-2407-bnb-4bit
Model Size	12.2b
Required VRAM	24.5 GB
Updated	2026-09-06
Maintainer	AlSamCur123
Model Type	mistral
Instruction-Based	Yes
Model Files	7.1 GB 7.5 GB 8.7 GB 10.1 GB 13.0 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
GGUF Quantization	Yes
Quantization Type	4bit\|gguf
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	1024000
Model Max Length	1024000
Transformers Version	4.47.1
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<pad>
Vocabulary Size	131072
Torch Data Type	float16

Rank the Mistral Nemo InstructContinuedFine 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

Best Alternatives to Mistral Nemo InstructContinuedFine

Best Alternatives	Context / RAM	Downloads	Likes
Mistral Nemo Kurdish Instruct	1000K / 24.5 GB	132	3
NemoR	1000K / 24.5 GB	24	0
RAISED Mistral Nemo SFT	128K / 24.5 GB	12	0
...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

Note: green Score (e.g. "73.2") means that the model is better than AlSamCur123/Mistral-Nemo-InstructContinuedFine.