What are the hardware requirements for Philosophy Mistral?

Philosophy Mistral requires approximately 7.7 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Philosophy Mistral and how large is it?

Philosophy Mistral is developed by Heralax, a model with 7.2b 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 Philosophy Mistral?

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

Philosophy Mistral by Heralax — VRAM 7.7GB, 32K context

Name: Philosophy Mistral
Author: Heralax

Philosophy Mistral is an open-source language model by Heralax. Features: 7.2b LLM, VRAM: 7.7GB, Context: 32K, License: apache-2.0, Quantized, LLM Explorer Score: 0.14.

Conversational Endpoints compatible Generated from trainer Ggml Gguf Mistral Pytorch Q8 Quantized Region:us

Model Card on HF 🤗: https://huggingface.co/Heralax/philosophy-mistral

Philosophy Mistral Parameters and Internals

Additional Notes

This model has been trained on a narrow domain, focusing on philosophical texts from the Gutenberg project. It's very knowledgeable in this area due to memorization and uses a new dataset setting which may make it less detailed but more concise in responses. Known limitations include lack of generalist instruct data, limiting it primarily to QA.

Training Details

Data Sources:

The Problems of Philosophy (Bertrand Russell), Beyond Good and Evil (Nietzsche), Thus Spake Zarathustra: A Book for All and None (Nietzsche), The Prince (Machiavelli), Second Treatise of Government

Methodology:

training on top 5 books on Gutenberg, new dataset setting lacking generalist instruct data

Hardware Used:

multi-GPU with 6 devices

LLM Name	Philosophy Mistral
Repository 🤗	https://huggingface.co/Heralax/philosophy-mistral
Base Model(s)	Heralax/philosophy-llm-mistral-pretrain Heralax/philosophy-llm-mistral-pretrain
Model Size	7.2b
Required VRAM	7.7 GB
Updated	2026-08-05
Maintainer	Heralax
Model Type	mistral
Model Files	14.5 GB 7.7 GB 14.5 GB
GGML Quantization	Yes
GGUF Quantization	Yes
Quantization Type	ggml\|q8\|gguf
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.45.0.dev0
Tokenizer Class	LlamaTokenizer
Padding Token	<\|end_of_text\|>
Vocabulary Size	32001
Torch Data Type	bfloat16

Rank the Philosophy Mistral 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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Note: green Score (e.g. "73.2") means that the model is better than Heralax/philosophy-mistral.