What are the hardware requirements for Mistral Trismegistus 7B AWQ?

Mistral Trismegistus 7B AWQ requires approximately 4.2 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 Mistral Trismegistus 7B AWQ and how large is it?

Mistral Trismegistus 7B AWQ is developed by TheBloke, a model with 7b 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 Trismegistus 7B AWQ?

Mistral Trismegistus 7B AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Mistral Trismegistus 7B AWQ by TheBloke — VRAM 4.2GB, 32K context

Name: Mistral Trismegistus 7B AWQ
Author: TheBloke

Mistral Trismegistus 7B AWQ is an open-source language model by TheBloke. Features: 7b LLM, VRAM: 4.2GB, Context: 32K, License: apache-2.0, Quantized, LLM Explorer Score: 0.09.

4-bit Awq Base model:quantized:teknium/m... Base model:teknium/mistral-tri... Distillation En Finetuned Gpt4 Instruct Mistral Mistral-7b Quantized Region:us Safetensors Synthetic data

Model Card on HF 🤗: https://huggingface.co/TheBloke/Mistral-Trismegistus-7B-AWQ

Mistral Trismegistus 7B AWQ Parameters and Internals

Model Type

mistral

Use Cases

Areas:

Research, Personal exploration of esoteric, occult, and spiritual topics

Applications:

Educational tools, Content creation in niche topics

Limitations:

Not a replacement for professional spiritual guidance

Additional Notes

This model is intended for those interested in non-mainstream topics, emphasizing creative and esoteric knowledge.

Supported Languages

en (high)

Training Details

Data Sources:

100% synthetic, gpt-4 generated dataset

Data Volume:

35,000 examples

Methodology:

Training on a diverse set of tasks related to esoteric, occult, and spiritual topics

Input Output

Input Format:

USER: {prompt}

Accepted Modalities:

text

Output Format:

ASSISTANT: {response}

LLM Name	Mistral Trismegistus 7B AWQ
Repository 🤗	https://huggingface.co/TheBloke/Mistral-Trismegistus-7B-AWQ
Model Name	Mistral Trismegistus 7B
Model Creator	Teknium
Base Model(s)	Mistral Trismegistus 7B teknium/Mistral-Trismegistus-7B
Model Size	7b
Required VRAM	4.2 GB
Updated	2026-07-11
Maintainer	TheBloke
Model Type	mistral
Model Files	4.2 GB
Supported Languages	en
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.34.0
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	float16

Rank the Mistral Trismegistus 7B AWQ 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 Trismegistus 7B AWQ

Best Alternatives	Context / RAM	Downloads	Likes
Mistral 7B Instruct V0.2 AWQ	32K / 4.2 GB	6	0
Mistral 7B Instruct V0.2 AWQ	32K / 4.2 GB	298182	52
Mistral 7B Instruct V0.3 AWQ	32K / 4.2 GB	5633	10
Mistral 7B Instruct V0.1 AWQ	32K / 4.2 GB	15461	2
Ghost 7B Alpha AWQ	32K / 4.2 GB	14	0
Tess 7B V2.0 AWQ	32K / 4.2 GB	1	1
...reeze 7B 32K Instruct V1.0 AWQ	32K / 4.7 GB	9	0
Breeze 7B Instruct V1.0 AWQ	32K / 4.6 GB	5	0
OpenHermes 2.5 Mistral 7B AWQ	32K / 4.2 GB	23691	21
NSFW DPO Noromaid 7B AWQ	32K / 4.2 GB	206	2

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Mistral-Trismegistus-7B-AWQ.