Maxilicious20/Aether-2.5-Pro-GGUF overview
Aether 2.5 Pro GGUF Pre quantized GGUF binaries for Aether 2.5 Pro . Aether 2.5 Pro is a fine tuned version of Qwen2.5 3B Instruct SFT + LoRA . It offers impro…
Runs locally from ~1.80 GB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
Model Details
| Model ID | Maxilicious20/Aether-2.5-Pro-GGUF |
|---|---|
| Author | Maxilicious20 |
| Pipeline | text-generation |
| License | apache-2.0 |
| Base model | — |
| Last modified | 2026-08-15T00:41:23.000Z |
Model README
---
library_name: gguf
tags:
- gguf
- llama.cpp
- lm-studio
- aether
- aether-2.5
- german
- english
- text-generation
license: apache-2.0
language:
- de
- en
---
Aether 2.5 Pro - GGUF
Pre-quantized GGUF binaries for Aether 2.5 Pro.
Aether 2.5 Pro is a fine-tuned version of Qwen2.5-3B-Instruct (SFT + LoRA). It offers improved reasoning, stronger instruction following, and better multilingual performance in German and English.
> 🖥️ Easiest way to run the model:
> Download MonoAIStudio – our local chat application.
> It comes pre-installed with Aether 2.5, Aether 2.5 Pro and Aether 2.5 Coder.
> 🔗 Looking for the LoRA Adapter?
> 👉 Maxilicious20/Aether-2.5-Pro
---
📦 Available Quantizations
| Filename | Quantization | Quality | Size | Recommendation |
| :--- | :--- | :--- | :--- | :--- |
| aether-2.5-pro-f16.gguf | F16 | Maximum | ~6.0 GB | Best quality |
| aether-2.5-pro-q8_0.gguf | Q8_0 | Very High | ~3.2 GB | Excellent quality |
| aether-2.5-pro-q4_k_m.gguf | Q4_K_M | Balanced | ~1.9 GB | Recommended |
---
🚀 How to Run
1. MonoAIStudio (Recommended)
- Download
MonoAIStudio.zip - Extract it
- Run
MonoAIStudio.exe - All Aether 2.5 models are already included
2. LM Studio
- Open LM Studio
- Search for
Maxilicious20/Aether-2.5-Pro-GGUF - Download
aether-2.5-pro-q4_k_m.gguf - Load the model
3. llama.cpp
./llama-cli -m aether-2.5-pro-q4_k_m.gguf -p "Hello!" -n 256Run Maxilicious20/Aether-2.5-Pro-GGUF with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models