What are the hardware requirements for IceNalyvkaRP 7B?

IceNalyvkaRP 7B requires approximately 14.5 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 IceNalyvkaRP 7B and how large is it?

IceNalyvkaRP 7B is developed by icefog72, 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 IceNalyvkaRP 7B?

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

IceNalyvkaRP 7B by icefog72 — VRAM 14.5GB, 32K context

Name: IceNalyvkaRP 7B
Author: icefog72

IceNalyvkaRP 7B is an open-source language model by icefog72. Features: 7b LLM, VRAM: 14.5GB, Context: 32K, License: cc-by-nc-4.0, Merged, LLM Explorer Score: 0.23.

Merged Model Alpaca Autotrain compatible Endpoints compatible Mistral Model-index Not-for-all-audiences Nsfw Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/icefog72/IceNalyvkaRP-7b

IceNalyvkaRP 7B Parameters and Internals

LLM Name	IceNalyvkaRP 7B
Repository 🤗	https://huggingface.co/icefog72/IceNalyvkaRP-7b
Merged Model	Yes
Model Size	7b
Required VRAM	14.5 GB
Updated	2025-09-23
Maintainer	icefog72
Model Type	mistral
Model Files	4.9 GB: 1-of-3 4.9 GB: 2-of-3 4.7 GB: 3-of-3
Model Architecture	MistralForCausalLM
License	cc-by-nc-4.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.46.2
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the IceNalyvkaRP 7B 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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