What are the hardware requirements for MedusaGemma E4B?

MedusaGemma E4B requires approximately 15.1 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed MedusaGemma E4B and how large is it?

MedusaGemma E4B is developed by stamsam, a model with 7.5b 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 MedusaGemma E4B?

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

MedusaGemma E4B by stamsam — VRAM 15.1GB

Name: MedusaGemma E4B
Author: stamsam

MedusaGemma E4B is an open-source language model by stamsam. Features: 7.5b LLM, VRAM: 15.1GB, License: apache-2.0, LLM Explorer Score: 0.24.

Arithmetic Base model:finetune:google/gem... Base model:google/gemma-4-e4b-... Code-assistance Conversational En Gemma Gemma4 Local-inference Medusa Pocket-polymath Refusal Region:us Repair Safetensors Sharded Structured-reasoning Tensorflow Validators

Model Card on HF 🤗: https://huggingface.co/stamsam/MedusaGemma-E4B

MedusaGemma E4B Parameters and Internals

LLM Name	MedusaGemma E4B
Repository 🤗	https://huggingface.co/stamsam/MedusaGemma-E4B
Base Model(s)	Gemma 4 E4B It google/gemma-4-E4B-it
Model Size	7.5b
Required VRAM	15.1 GB
Updated	2026-08-06
Maintainer	stamsam
Model Type	gemma4
Model Files	5.4 GB: 1-of-4 4.0 GB: 2-of-4 5.6 GB: 3-of-4 0.1 GB: 4-of-4
Supported Languages	en
Model Architecture	Gemma4ForConditionalGeneration
License	apache-2.0
Transformers Version	5.5.4
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>

Rank the MedusaGemma E4B 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 MedusaGemma E4B

Best Alternatives	Context / RAM	Downloads	Likes
Gemma 4 E4b It OptiQ 4bit	128K / 6.5 GB	4587	28
Gemma 4 E4b It Qat OptiQ 4bit	0K / 6.5 GB	2803	6
... 4 E4B It OBLITERATED Mlx 8Bit	0K / 8 GB	2481	4
...litan Translator V0 Gemma4 E4b	0K / 6.5 GB	312	2
...litan Translator V0 Gemma4 E4b	0K / 6.5 GB	76	2

Note: green Score (e.g. "73.2") means that the model is better than stamsam/MedusaGemma-E4B.