What are the hardware requirements for Gemma 4 E4B It NVFP4A16?

Gemma 4 E4B It NVFP4A16 requires approximately 10.3 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Gemma 4 E4B It NVFP4A16 and how large is it?

Gemma 4 E4B It NVFP4A16 is developed by axteam, a model with 7.9b 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 E4B It NVFP4A16?

Gemma 4 E4B It NVFP4A16 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Gemma 4 E4B It NVFP4A16 by axteam — VRAM 10.3GB

Name: Gemma 4 E4B It NVFP4A16
Author: axteam

Gemma 4 E4B It NVFP4A16 is an open-source language model by axteam. Features: 7.9b LLM, VRAM: 10.3GB, License: apache-2.0, LLM Explorer Score: 0.28.

Base model:google/gemma-4-e4b-... Base model:quantized:google/ge... Compressed-tensors Conversational Endpoints compatible Fp4 Gemma Gemma4 Image-text-to-text Nvfp4 Quantized Region:us Safetensors Vllm W4a16

Model Card on HF 🤗: https://huggingface.co/axteam/gemma-4-E4B-it-NVFP4A16

Gemma 4 E4B It NVFP4A16 Parameters and Internals

LLM Name	Gemma 4 E4B It NVFP4A16
Repository 🤗	https://huggingface.co/axteam/gemma-4-E4B-it-NVFP4A16
Base Model(s)	Gemma 4 E4B It google/gemma-4-E4B-it
Model Size	7.9b
Required VRAM	10.3 GB
Updated	2026-10-15
Maintainer	axteam
Model Type	gemma4
Model Files	10.3 GB
Model Architecture	Gemma4ForConditionalGeneration
License	apache-2.0
Transformers Version	5.5.0.dev0
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>

Rank the Gemma 4 E4B It NVFP4A16 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

Best Alternatives to Gemma 4 E4B It NVFP4A16

Best Alternatives	Context / RAM	Downloads	Likes
Baihua Gemma4 E4B	0K / 15.9 GB	135	3
Kitsune Tales E4B EN	0K / 15.9 GB	298	1
Kitsune Tales E4B JP	0K / 15.9 GB	289	1
Gemma 4 E4B It NVFP4	0K / 10.3 GB	31	1
ContextPilot E4B	0K / 15.9 GB	404	5
Firehouse Cactus 1.0	0K / 15.9 GB	736	0
Gemma4 Merged K8s	0K / 15.9 GB	212	0
Quatfit Mini	0K / 31.8 GB	1074	7
Gemma 4 E4B It Qat Bf16	0K / 15.9 GB	77	1
... 4 E4B It Qat Q4 0 Unquantized	0K / 15.9 GB	10950	27

Note: green Score (e.g. "73.2") means that the model is better than axteam/gemma-4-E4B-it-NVFP4A16.