What are the hardware requirements for Byrne 86M?

Byrne 86M requires approximately 0.4 GB of VRAM and supports a context window of 4K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Byrne 86M and how large is it?

Byrne 86M is developed by Quazim0t0, a model with 86m 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 Byrne 86M?

Byrne 86M is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Byrne 86M by Quazim0t0 — VRAM 0.4GB, 4K context

Name: Byrne 86M
Author: Quazim0t0

Byrne 86M is an open-source language model by Quazim0t0. Features: 86m LLM, VRAM: 0.4GB, Context: 4K, License: apache-2.0, LLM Explorer Score: 0.24.

Custom code En Experimental Feature-extraction Jepa Mla Region:us Safetensors Small-models Spike whale

Model Card on HF 🤗: https://huggingface.co/Quazim0t0/Byrne-86M

Byrne 86M Parameters and Internals

LLM Name	Byrne 86M
Repository 🤗	https://huggingface.co/Quazim0t0/Byrne-86M
Model Size	86m
Required VRAM	0.4 GB
Updated	2026-08-05
Maintainer	Quazim0t0
Model Type	spike_whale
Model Files	0.4 GB
Supported Languages	en
Model Architecture	SpikeWhaleLM
License	apache-2.0
Context Length	4096
Model Max Length	4096
Transformers Version	5.8.0
Tokenizer Class	SpikeTokenizer
Padding Token	<pad>
Vocabulary Size	16512

Rank the Byrne 86M 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 Byrne 86M

Best Alternatives	Context / RAM	Downloads	Likes
Escarda 86M Base	4K / 0.4 GB	3227	3
Escarda 86M Identity	4K / 0.4 GB	416	1

Note: green Score (e.g. "73.2") means that the model is better than Quazim0t0/Byrne-86M.