What are the hardware requirements for Silicon Natsuki 7B V0.5 Gguf?

Silicon Natsuki 7B V0.5 Gguf requires approximately 7.7 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Silicon Natsuki 7B V0.5 Gguf and how large is it?

Silicon Natsuki 7B V0.5 Gguf is developed by 922CA, 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 Silicon Natsuki 7B V0.5 Gguf?

Silicon Natsuki 7B V0.5 Gguf is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Silicon Natsuki 7B V0.5 Gguf by 922CA — VRAM 7.7GB

Name: Silicon Natsuki 7B V0.5 Gguf
Author: 922CA

Silicon Natsuki 7B V0.5 Gguf is an open-source language model by 922CA. Features: 7b LLM, VRAM: 7.7GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.11.

Base model:quantized:sanjiwats... Base model:sanjiwatsuki/silico... En Endpoints compatible Gguf Mistral Quantized Region:us Unsloth

Model Card on HF 🤗: https://huggingface.co/922CA/Silicon-Natsuki-7b-v0.5-gguf

Silicon Natsuki 7B V0.5 Gguf Parameters and Internals

Model Type

text-generation-inference, transformers, mistral

Additional Notes

The model was trained 2x faster using the Unsloth method and the Huggingface TRL library.

Supported Languages

English (unknown)

Training Details

Model Architecture:

Mistral

LLM Name	Silicon Natsuki 7B V0.5 Gguf
Repository 🤗	https://huggingface.co/922CA/Silicon-Natsuki-7b-v0.5-gguf
Base Model(s)	Silicon Maid 7B SanjiWatsuki/Silicon-Maid-7B
Model Size	7b
Required VRAM	7.7 GB
Updated	2026-08-25
Maintainer	922CA
Model Type	mistral
Model Files	7.7 GB
Supported Languages	en
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	AutoModel
License	apache-2.0

Rank the Silicon Natsuki 7B V0.5 Gguf 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

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Note: green Score (e.g. "73.2") means that the model is better than 922CA/Silicon-Natsuki-7b-v0.5-gguf.