What are the hardware requirements for Sealglazer 1.9M?

Sealglazer 1.9M requires a context window of 0.3K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Sealglazer 1.9M and how large is it?

Sealglazer 1.9M is developed by Compactbot, a model with 1.9m 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 Sealglazer 1.9M?

Sealglazer 1.9M is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Sealglazer 1.9M by Compactbot — 0.3K context

Name: Sealglazer 1.9M
Author: Compactbot

Sealglazer 1.9M is an open-source language model by Compactbot. Features: 1.9m LLM, Context: 0.3K, License: apache-2.0, LLM Explorer Score: 0.32.

En From-scratch Pinniped Region:us Safetensors Sealglazer Slm Small-language-model Tiny Tiny-lm Tiny-model

Model Card on HF 🤗: https://huggingface.co/Compactbot/sealglazer-1.9m

Sealglazer 1.9M Parameters and Internals

LLM Name	Sealglazer 1.9M
Repository 🤗	https://huggingface.co/Compactbot/sealglazer-1.9m
Model Size	1.9m
Required VRAM	0 GB
Updated	2026-09-25
Maintainer	Compactbot
Model Type	sealglazer
Model Files	0.0 GB
Supported Languages	en
Model Architecture	SealGlazerLM
License	apache-2.0
Context Length	256
Model Max Length	256
Vocabulary Size	8192

Rank the Sealglazer 1.9M 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