What are the hardware requirements for Mistral Nemo Instruct 12B Philosophy Math?

Mistral Nemo Instruct 12B Philosophy Math 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 Instruct 12B Philosophy Math and how large is it?

Mistral Nemo Instruct 12B Philosophy Math is developed by EpistemeAI, a model with 12b 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 12B Philosophy Math?

Mistral Nemo Instruct 12B Philosophy Math is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Mistral Nemo Instruct 12B Philosophy Math by EpistemeAI — VRAM 24.5GB, 1000K context

Name: Mistral Nemo Instruct 12B Philosophy Math
Author: EpistemeAI

Mistral Nemo Instruct 12B Philosophy Math is an open-source language model by EpistemeAI. Features: 12b LLM, VRAM: 24.5GB, Context: 1000K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.19.

4bit Base model:finetune:unsloth/mi... Base model:unsloth/mistral-nem... Conversational En Endpoints compatible Instruct Mistral Pytorch Quantized Region:us Safetensors Sharded Tensorflow Trl Unsloth

Model Card on HF 🤗: https://huggingface.co/EpistemeAI/Mistral-Nemo-Instruct-12B-Philosophy-Math

Mistral Nemo Instruct 12B Philosophy Math Parameters and Internals

Model Type

text-generation-inference

Additional Notes

This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.

Supported Languages

en ()

Training Details

Methodology:

Trained with Unsloth and Huggingface's TRL library

LLM Name	Mistral Nemo Instruct 12B Philosophy Math
Repository 🤗	https://huggingface.co/EpistemeAI/Mistral-Nemo-Instruct-12B-Philosophy-Math
Base Model(s)	...al Nemo Instruct 2407 Bnb 4bit unsloth/Mistral-Nemo-Instruct-2407-bnb-4bit
Model Size	12b
Required VRAM	24.5 GB
Updated	2026-07-28
Maintainer	EpistemeAI
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 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
Quantization Type	4bit
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	1024000
Model Max Length	1024000
Transformers Version	4.44.2
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<pad>
Vocabulary Size	131072
Torch Data Type	float16

Rank the Mistral Nemo Instruct 12B Philosophy Math 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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Geneva 12B GCv2 5M	1000K / 24.5 GB	29	13
ReWiz Nemo 12B Instruct	1000K / 24.5 GB	6	2
...omix Unleashed 12B V0.6.1 8bit	1000K / 12.9 GB	4	2
Ava 1.0 12B	1000K / 24.5 GB	34	4
Poemma 12B	1000K / 24.5 GB	24	2
...t RP Noodles 12B V1.4 EXL2 8.0	1000K / 12.5 GB	34	2
Lumimaid Magnum 12B EXL2 8.0	1000K / 12.6 GB	27	4
DeepOpus 1 12B Preview	128K / 24.5 GB	18	0
DeepNeo 1 12B Preview	128K / 24.5 GB	15	0
...r Nemo 12B Instruct R 21 09 24	1000K / 24.5 GB	396277	141

Note: green Score (e.g. "73.2") means that the model is better than EpistemeAI/Mistral-Nemo-Instruct-12B-Philosophy-Math.