What are the hardware requirements for Gemma 4 Waldwicht Sproessling?

Gemma 4 Waldwicht Sproessling requires approximately 3.1 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Gemma 4 Waldwicht Sproessling and how large is it?

Gemma 4 Waldwicht Sproessling is developed by kyr0, a model with 801m 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 4 Waldwicht Sproessling?

Gemma 4 Waldwicht Sproessling is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Gemma 4 Waldwicht Sproessling by kyr0 — VRAM 3.1GB

Name: Gemma 4 Waldwicht Sproessling
Author: kyr0

Gemma 4 Waldwicht Sproessling is an open-source language model by kyr0. Features: 801m LLM, VRAM: 3.1GB, License: apache-2.0, LLM Explorer Score: 0.23.

3-bit Base model:google/gemma-4-e2b-... Base model:quantized:google/ge... Conversational Gemma4 Mlx Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/kyr0/Gemma-4-Waldwicht-Sproessling

Gemma 4 Waldwicht Sproessling Parameters and Internals

LLM Name	Gemma 4 Waldwicht Sproessling
Repository 🤗	https://huggingface.co/kyr0/Gemma-4-Waldwicht-Sproessling
Base Model(s)	Gemma 4 E2B It google/gemma-4-E2B-it
Model Size	801m
Required VRAM	3.1 GB
Updated	2026-08-08
Maintainer	kyr0
Model Type	gemma4
Model Files	2.1 GB: 1-of-2 1.0 GB: 2-of-2
Model Architecture	ForCausalLM
License	apache-2.0
Transformers Version	5.5.0.dev0
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>

Rank the Gemma 4 Waldwicht Sproessling 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