What are the hardware requirements for Gemma Introspection 20250821 Merged?

Gemma Introspection 20250821 Merged requires approximately 18.6 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Gemma Introspection 20250821 Merged and how large is it?

Gemma Introspection 20250821 Merged is developed by thejaminator, a model with 9.2b 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 Gemma Introspection 20250821 Merged?

Gemma Introspection 20250821 Merged is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Gemma Introspection 20250821 Merged by thejaminator — VRAM 18.6GB, 8K context

Name: Gemma Introspection 20250821 Merged
Author: thejaminator

Gemma Introspection 20250821 Merged is an open-source language model by thejaminator. Features: 9.2b LLM, VRAM: 18.6GB, Context: 8K, LLM Explorer Score: 0.19.

Arxiv:1910.09700 Conversational Endpoints compatible Gemma2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/thejaminator/gemma-introspection-20250821-merged

Gemma Introspection 20250821 Merged Parameters and Internals

LLM Name	Gemma Introspection 20250821 Merged
Repository 🤗	https://huggingface.co/thejaminator/gemma-introspection-20250821-merged
Model Size	9.2b
Required VRAM	18.6 GB
Updated	2026-07-10
Maintainer	thejaminator
Model Type	gemma2
Model Files	4.9 GB: 1-of-4 5.0 GB: 2-of-4 5.0 GB: 3-of-4 3.7 GB: 4-of-4
Model Architecture	Gemma2ForCausalLM
Context Length	8192
Model Max Length	8192
Transformers Version	4.55.4
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
Vocabulary Size	256000
Torch Data Type	bfloat16

Rank the Gemma Introspection 20250821 Merged 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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