What are the hardware requirements for NeXGen Small?

NeXGen Small requires approximately 0.5 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed NeXGen Small and how large is it?

NeXGen Small is developed by CrabfishAI, a model with 124.4m 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 NeXGen Small?

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

NeXGen Small by CrabfishAI — VRAM 0.5GB

Name: NeXGen Small
Author: CrabfishAI

NeXGen Small is an open-source language model by CrabfishAI. Features: 124.4m LLM, VRAM: 0.5GB, License: mit, LLM Explorer Score: 0.1.

Autotrain En Endpoints compatible Gpt2 Lora Pytorch Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/CrabfishAI/NeXGen-small

NeXGen Small Parameters and Internals

Model Type

text generation

Use Cases

Areas:

Content Creation, Writing Assistance, Chatbot Development, Prototyping, Social Media, Personal Assistance

Applications:

Marketing, Authoring, Interactive Media, Product Development, Social Engagement

Primary Use Cases:

Email Drafting, Blog Posting, Code Commenting, Storyline Creation, Educational Content, Personal Journaling

Limitations:

Content Quality Irregularities, Bias and Sensitivity, Inappropriate Language, Prompt Dependent Output

Additional Notes

Note that this is the smallest version of the NeXGen series with promises of larger models in the future.

Supported Languages

en (English)

LLM Name	NeXGen Small
Repository 🤗	https://huggingface.co/CrabfishAI/NeXGen-small
Model Size	124.4m
Required VRAM	0.5 GB
Updated	2026-08-30
Maintainer	CrabfishAI
Model Type	gpt2
Model Files	0.5 GB 0.5 GB 0.0 GB
Supported Languages	en
Model Architecture	AutoModel
License	mit
Model Max Length	1024
Is Biased	none
Tokenizer Class	GPT2Tokenizer
Padding Token	<\|pad\|>
PEFT Type	LORA
LoRA Model	Yes
LoRA Alpha	32
LoRA Dropout	0.05
Errors	replace

Rank the NeXGen Small 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 NeXGen Small

Best Alternatives	Context / RAM	Downloads	Likes
A3ON	0K / 0.5 GB	5	2

Note: green Score (e.g. "73.2") means that the model is better than CrabfishAI/NeXGen-small.