What are the hardware requirements for Mossez 100M Base?

Mossez 100M Base requires approximately 0.4 GB of VRAM and supports a context window of 1K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Mossez 100M Base and how large is it?

Mossez 100M Base is developed by mossez-systems, a model with 100m 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 Mossez 100M Base?

Mossez 100M Base is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Mossez 100M Base by mossez-systems — VRAM 0.4GB, 1K context

Name: Mossez 100M Base
Author: mossez-systems

Mossez 100M Base is an open-source language model by mossez-systems. Features: 100m LLM, VRAM: 0.4GB, Context: 1K, License: apache-2.0, LLM Explorer Score: 0.26.

Dataset:huggingfacefw/fineweb Dataset:huggingfacefw/fineweb-... Dataset:wikimedia/wikipedia En Endpoints compatible Gqa Llama Mossez Region:us Research Ru Safetensors

Model Card on HF 🤗: https://huggingface.co/mossez-systems/Mossez-100M-Base

Mossez 100M Base Parameters and Internals

LLM Name	Mossez 100M Base
Repository 🤗	https://huggingface.co/mossez-systems/Mossez-100M-Base
Model Size	100m
Required VRAM	0.4 GB
Updated	2026-08-08
Maintainer	mossez-systems
Model Type	llama
Model Files	0.4 GB
Supported Languages	ru en
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	1024
Model Max Length	1024
Transformers Version	4.56.2
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<pad>
Vocabulary Size	32000

Rank the Mossez 100M Base 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 Mossez 100M Base

Best Alternatives	Context / RAM	Downloads	Likes
SmollerLM2 100M Instruct Sft	8K / 0.3 GB	9	1
SmollerLM2 100M	8K / 0.2 GB	5	0
Stockmark 2 100B Instruct Beta	4K / 192.9 GB	13	12
Stockmark 100B	4K / 191.9 GB	9	34
Saily 100b	4K / 235.5 GB	60	7
Plankton 100M	4K / 0.4 GB	8	0
Webcoder 100M Html Css Js	2K / 0.4 GB	487	0
...Climbmix Dolmino Midtrain 100B	2K / 1.5 GB	450	0
...lisLM 100M Layer Hidden Pruned	2K / 0.2 GB	820	0
Reglu 100B	2K / 2.6 GB	7	1

Note: green Score (e.g. "73.2") means that the model is better than mossez-systems/Mossez-100M-Base.