Who developed Gemma 4 E2B It Qat Q4 0 W4a16 Ct and how large is it?

Gemma 4 E2B It Qat Q4 0 W4a16 Ct is developed by xbill9, a model with 5.1b 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 E2B It Qat Q4 0 W4a16 Ct?

Gemma 4 E2B It Qat Q4 0 W4a16 Ct is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Gemma 4 E2B It Qat Q4 0 W4a16 Ct by xbill9

Name: Gemma 4 E2B It Qat Q4 0 W4a16 Ct
Author: xbill9

Gemma 4 E2B It Qat Q4 0 W4a16 Ct is an open-source language model by xbill9. Features: 5.1b LLM, License: apache-2.0, Quantized, LLM Explorer Score: 0.27.

Base model:google/gemma-4-e2b-... Base model:quantized:google/ge... Compressed-tensors Conversational Gemma4 Image-text-to-text Int4 Q4 Q4 0 Qat Quantized Region:us Safetensors Tpu Vllm W4a16

Model Card on HF 🤗: https://huggingface.co/xbill9/gemma-4-E2B-it-qat-q4_0-w4a16-ct

Gemma 4 E2B It Qat Q4 0 W4a16 Ct Parameters and Internals

LLM Name	Gemma 4 E2B It Qat Q4 0 W4a16 Ct
Repository 🤗	https://huggingface.co/xbill9/gemma-4-E2B-it-qat-q4_0-w4a16-ct
Base Model(s)	... 4 E2B It Qat Q4 0 Unquantized google/gemma-4-E2B-it-qat-q4_0-unquantized
Model Size	5.1b
Required VRAM	0 GB
Updated	2026-10-01
Maintainer	xbill9
Model Type	gemma4
Model Files	0.0 GB 0.0 GB 0.0 GB 0.0 GB 0.0 GB 0.0 GB 0.0 GB 0.0 GB 0.0 GB 0.0 GB 0.0 GB 0.0 GB 0.0 GB 0.0 GB 0.0 GB 0.0 GB 0.0 GB 0.0 GB 0.0 GB 0.0 GB 0.0 GB 0.0 GB 0.0 GB 0.0 GB 0.0 GB 0.0 GB 0.0 GB 0.0 GB 0.0 GB 0.0 GB 0.0 GB 0.0 GB 0.0 GB 0.0 GB 0.0 GB 1.4 GB 4.7 GB 0.3 GB
Quantization Type	q4\|q4_0
Model Architecture	Gemma4ForConditionalGeneration
License	apache-2.0
Transformers Version	5.6.2
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>

Rank the Gemma 4 E2B It Qat Q4 0 W4a16 Ct 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

Quantized Models of the Gemma 4 E2B It Qat Q4 0 W4a16 Ct

Model	Likes	Downloads	VRAM
... E2B It Qat Q4 0 W4a16 Ct Text	0	208	0 GB

Best Alternatives to Gemma 4 E2B It Qat Q4 0 W4a16 Ct

Best Alternatives	Context / RAM	Downloads	Likes
...emma 4 E2B It Unsloth Bnb 4bit	0K / 8.1 GB	78250	11
... 4 E2B It Qat Q4 0 Unquantized	0K / 10.2 GB	13412	32
Sdam Gemma4 E2B Merged Bf16	0K / 10.2 GB	424	1
Dama Aibrain	0K / 10.3 GB	38	1
... 4 E2B It Qat Q4 0 Unquantized	0K / 10.2 GB	3007	4
Dama Aibrain	0K / 10.3 GB	323	0
My Brain V1	0K / 10.3 GB	35	0
...emma4 E2B MIXED NO TAG E3 BF16	0K / 10.2 GB	27	1
Gemma 4 E2B Unsloth Bnb 4bit	0K / 9 GB	1837	5
Awgs Vision V0.3	0K / 10.3 GB	17	3

Note: green Score (e.g. "73.2") means that the model is better than xbill9/gemma-4-E2B-it-qat-q4_0-w4a16-ct.