Anima via WebGPU (Browser) Quantized GGUF

Anima via WebGPU (Browser) Quantized GGUF

To get this model running locally in no time, utilize the built-in WSL tools.

Use the instructions provided below to complete the setup.

1-click setup: the app automatically fetches the large weight files.

There is no manual tuning required; the builder deploys the best matching configuration.

🔍 Hash-sum: 36aae4116c1dcc8aa17c49edd3df7307 | 🕓 Last update: 2026-07-01



  • Processor: Intel i5 or AMD Ryzen 5 for basic 7B models
  • RAM: 32 GB or higher for smooth 32k context lengths
  • Disk Space: 100 GB for multi-modal model vision components
  • GPU: high memory bandwidth GPU for next-gen local AI pipeline

Anima is a next‑generation AI model designed to deliver ultra‑low latency inference across a wide range of applications. Built on a scalable neural architecture, it combines deep contextual understanding with real‑time processing capabilities. The model excels in multimodal tasks, seamlessly handling text, images, and audio with a unified representation space. Its training pipeline leverages massive curated datasets and advanced optimization techniques to achieve state‑of‑the‑art performance while maintaining energy efficiency. Anima’s modular design enables developers to fine‑tune and deploy the system on diverse hardware platforms, from edge devices to cloud infrastructures.

Technical specifications
Parameter Value
Model size 12 B parameters
Training data 1.5 trillion tokens
Inference latency <5 ms
Supported modalities Text, Image, Audio
  1. Script fetching custom model merges directly into KoboldCPP directory
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