What are the hardware requirements for Boptruth Agatha 7B?

Boptruth Agatha 7B requires approximately 14.4 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 Boptruth Agatha 7B and how large is it?

Boptruth Agatha 7B is developed by theprint, 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 Boptruth Agatha 7B?

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

Boptruth Agatha 7B by theprint — VRAM 14.4GB, 32K context

Name: Boptruth Agatha 7B
Author: theprint

Boptruth Agatha 7B is an open-source language model by theprint. Features: 7b LLM, VRAM: 14.4GB, Context: 32K, Quantized, LLM Explorer Score: 0.19.

Boptruth Conversational Dataset:theprint/mysterywriter En Gguf Gpt H2o-llmstudio Mistral Model-index Quantized Region:us Safetensors Sharded Tensorflow Theprint

Model Card on HF 🤗: https://huggingface.co/theprint/Boptruth-Agatha-7B

Boptruth Agatha 7B Parameters and Internals

Model Type

large language model, gpt

Use Cases

Considerations:

Users are encouraged to use the model ethically and responsibly.

Training Details

Data Sources:

MysteryWriter data set

Model Architecture:

MistralForCausalLM

Responsible Ai Considerations

Fairness:

The model may generate biased, racist, or offensive content as it is trained on diverse internet text data.

Accountability:

Users assume full responsibility for use of the model.

Mitigation Strategies:

Feedback is encouraged to report biased or inappropriate content.

Input Output

Accepted Modalities:

text

LLM Name	Boptruth Agatha 7B
Repository 🤗	https://huggingface.co/theprint/Boptruth-Agatha-7B
Model Size	7b
Required VRAM	14.4 GB
Updated	2026-07-27
Maintainer	theprint
Model Type	mistral
Model Files	14.5 GB 2.7 GB 3.5 GB 3.2 GB 4.4 GB 4.1 GB 5.1 GB 5.9 GB 7.7 GB 4.9 GB: 1-of-3 5.0 GB: 2-of-3 4.5 GB: 3-of-3
Supported Languages	en
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	MistralForCausalLM
Context Length	32768
Model Max Length	32768
Transformers Version	4.38.0.dev0
Tokenizer Class	LlamaTokenizer
Padding Token	<unk>
Vocabulary Size	32768
Torch Data Type	float16

Rank the Boptruth Agatha 7B 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 Boptruth Agatha 7B

Best Alternatives	Context / RAM	Downloads	Likes
MegaBeam Mistral 7B 300K Gguf	282K / 5 GB	35	3
MegaBeam Mistral 7B 300K Gguf	282K / 5 GB	34	3
Backrooms Mistral 7B 10e	32K / 14.5 GB	128	0
Mistral 7B Instruct V0.2.gguf	32K / 14.5 GB	17	3
Mistral 7B Instruct V0.2 GGUF	32K / 4.4 GB	26	2
...andle Mistral 7B Instruct V0.2	32K / 14.4 GB	213	0
...andle Dolphin 2.2.1 Mistral 7B	32K / 14.4 GB	89	0
Mahou 1.2a Mistral 7B	32K / 14.4 GB	33	7
Tamil Mistral 7B Instruct V0.1	32K / 14.8 GB	350	14
... Noromaid NSFW Mistral 7B GGUF	32K / 4.1 GB	35298	124

Note: green Score (e.g. "73.2") means that the model is better than theprint/Boptruth-Agatha-7B.