What are the hardware requirements for Pebble 25M?

Pebble 25M requires approximately 0.1 GB of VRAM and supports a context window of 2K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Pebble 25M and how large is it?

Pebble 25M is developed by basically-ai, a model with 25m 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 Pebble 25M?

Pebble 25M is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Pebble 25M by basically-ai — VRAM 0.1GB, 2K context

Name: Pebble 25M
Author: basically-ai

Pebble 25M is an open-source language model by basically-ai. Features: 25m LLM, VRAM: 0.1GB, Context: 2K, License: apache-2.0, LLM Explorer Score: 0.36.

Base-model Custom-code Custom code En Hybrid Language-model Mamba2 Pebble Pebble 25m Pytorch Region:us Safetensors Small-language-model

Model Card on HF 🤗: https://huggingface.co/basically-ai/Pebble-25M

Pebble 25M Parameters and Internals

LLM Name	Pebble 25M
Repository 🤗	https://huggingface.co/basically-ai/Pebble-25M
Model Size	25m
Required VRAM	0.1 GB
Updated	2026-09-04
Maintainer	basically-ai
Model Type	pebble_25m
Model Files	0.1 GB
Supported Languages	en
Model Architecture	PebbleForCausalLM
License	apache-2.0
Context Length	2048
Model Max Length	2048
Tokenizer Class	PreTrainedTokenizerFast
Vocabulary Size	2048
Torch Data Type	float32

Rank the Pebble 25M capabilities

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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 Pebble 25M

Best Alternatives	Context / RAM	Downloads	Likes
Pebble 25M Chat	2K / 0.1 GB	349	6