What are the hardware requirements for Phillnet Mini Max?

Phillnet Mini Max requires approximately 1.8 GB of VRAM and supports a context window of 1024K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Phillnet Mini Max and how large is it?

Phillnet Mini Max is developed by ayjays132, a model with 0.8b 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 Phillnet Mini Max?

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

Phillnet Mini Max by ayjays132 — VRAM 1.8GB, 1024K context

Name: Phillnet Mini Max
Author: ayjays132

Phillnet Mini Max is an open-source language model by ayjays132. Features: 0.8b LLM, VRAM: 1.8GB, Context: 1024K, License: apache-2.0, LLM Explorer Score: 0.29.

Adaptive-reasoning Base model:finetune:qwen/qwen3... Base model:qwen/qwen3.5-0.8b Code-generation Conversational Custom-code Custom code Dendro Dendro omni En Image-text-to-text Long-context Multimodal Phillnet Phillnet-mini Region:us Safetensors Text-vision-only Vision Visual-question-answering

Model Card on HF 🤗: https://huggingface.co/ayjays132/Phillnet-Mini-Max

Phillnet Mini Max Parameters and Internals

LLM Name	Phillnet Mini Max
Repository 🤗	https://huggingface.co/ayjays132/Phillnet-Mini-Max
Model Name	Phillnet Mini Max
Base Model(s)	Qwen/Qwen3.5-0.8B Qwen/Qwen3.5-0.8B
Model Size	0.8b
Required VRAM	1.8 GB
Updated	2026-08-24
Maintainer	ayjays132
Model Type	dendro_omni
Model Files	1.8 GB
Supported Languages	en
Model Architecture	DendroForCausalLM
License	apache-2.0
Context Length	1048576
Model Max Length	1048576
Transformers Version	5.14.1
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	248320
Errors	replace

Rank the Phillnet Mini Max 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 Phillnet Mini Max

Best Alternatives	Context / RAM	Downloads	Likes
Phillnet Mini Omni Max	1024K / 1.8 GB	400	1

Note: green Score (e.g. "73.2") means that the model is better than ayjays132/Phillnet-Mini-Max.