Using a native PowerShell script is the absolute quickest way to install this model.
Please follow the instructions listed below to get started.
The loader auto-caches the model archive (several GBs included).
The script runs a quick hardware check to dynamically adjust parameters for elite speed.
🔐 Hash sum: 1defc38fcdc4c47efd663d0c707576f5 | 📅 Last update: 2026-06-29
CPU: modern architecture (Zen 3 / Alder Lake minimum)
RAM: minimum 16 GB for stable 8B model loading
Storage: extra room for future model updates and datasets
Graphics: CUDA Compute Capability 8.0+ required for flash-attention
The gemma-4-E2B-it-litert-lm model represents a significant advancement in open‑source language models, combining the efficiency of the Gemma architecture with enhanced instruction following capabilities. Built on a transformer base with E2B (Efficient Extra Block) optimization, it achieves superior performance while maintaining a compact footprint. The model features 8 billion parameters, a 4096 token context window, and specialized fine‑tuning for literature and technical domains. In benchmark evaluations, it consistently outperforms comparable models on reasoning, coding, and factual retrieval tasks. Its integration with the LiteRT inference engine ensures low‑latency deployment across mobile and edge devices. Developers can leverage the provided API and open‑weight licensing to customize and deploy the model for a wide range of applications.
Parameters
8 billion
Context Length
4096 tokens
Architecture
Transformer with E2B optimization
Primary Focus
Instruction following, literature & technical text
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🔍 Hash-sum: b1646ce484c3c075d4d02bf437df4cbf | 🕓 Last update: 2026-06-23
Processor: 1 GHz dual-core required
RAM: At least 4 GB
Disk space: 64 GB for patching
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Expand Office capabilities by connecting with popular external services and add-ins.
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Microsoft OneNote is a digital note management app built for quick and convenient collection, storage, and organization of ideas, notes, and thoughts. It fuses the ease of a standard notebook with the functionalities of advanced software: here, you can write, insert images, audio, links, and tables. OneNote is perfect for personal notes, learning, work tasks, and collaborative efforts. Thanks to the Microsoft 365 cloud service, all data is synchronized automatically between devices, facilitating data access anywhere and at any moment, whether on a computer, tablet, or smartphone.
The gemma-4-E4B-it-GGUF model represents a significant advancement in open‑source language models, combining efficient inference with strong reasoning capabilities. Built on the Gemma architecture, it leverages a 4‑billion parameter configuration that balances speed and accuracy for a wide range of tasks. Its context window extends to 8K tokens, enabling the model to understand longer prompts and maintain coherence across complex dialogues. In benchmark evaluations, the model achieves state‑of‑the‑art performance on reasoning, coding, and multilingual tasks while consuming minimal GPU resources. The accompanying GGUF quantization format ensures seamless integration with popular inference frameworks, reducing memory footprint and accelerating deployment. Developers and researchers can fine‑tune the model for specialized applications, benefiting from its robust tokenization and extensive community support.
Parameters
4 B
Context length
8K tokens
Quantization
GGUF (Q4_K_M)
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The fastest way to get this model running locally is via Optional Features.
Make sure to follow the instructions below.
The setup auto-downloads all needed files (several GBs).
The configuration wizard runs silently to set up the model for peak performance.
📡 Hash Check: fc3ebb60741c926586af2f85285edc3b | 📅 Last Update: 2026-06-22
Processor: next-gen chip for heavy context processing
RAM: minimum 16 GB for stable 8B model loading
Disk Space: required: fast PCIe 4.0 drive for instant boots
GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats
The LTX-2 model introduces a refined transformer architecture that significantly boosts contextual understanding across text and image inputs. Its training pipeline leverages a diverse dataset comprising billions of paired examples, enabling multimodal coherence that outperforms previous models. By incorporating efficient attention mechanisms, LTX-2 achieves real-time inference with minimal latency, making it suitable for production environments. The model also features an advanced reasoning layer that enhances logical consistency and reduces hallucination rates. These capabilities are summarized in the table below, which compares key performance metrics against earlier versions. Overall, LTX-2 sets a new benchmark for scalable and robust AI systems.
Specification
Value
Parameters
12B
Training Data
2.5TB multimodal
Inference Latency
<0.5s
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📡 Hash Check: a7e87a12b1ee986c123143235996ffa5 | 📅 Last Update: 2026-06-23
Processor: 1 GHz dual-core required
RAM: Needed: 4 GB
Disk space: Required: 64 GB
Microsoft 365 enables Office apps and services via a cloud subscription. It offers Word, Excel, PowerPoint, Outlook, and Teams along with regular updates. It allows real-time collaboration, file sharing, and OneDrive storage. Microsoft 365 accommodates use across PCs, Macs, tablets, and smartphones. Distinguished by flexibility and integration in productivity tools.
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Graphic Processor: RTX 3060 or RX 6600 for minimum settings
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A cute assistant for the users who need to use their computer for technical presentations, demonstrations and explaining workflows. Presentation Assistant Pro is a handy application designed to transform your computer into a powerful presentation tool. It allows you to make notes directly on your desktop and magnify certain screen areas in order to emphasize windows or icons.
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📡 Hash Check: 28ba4525e141586d8691461d84c206d2 | 📅 Last Update: 2026-06-25
Processor: 6-core 3.5 GHz minimum required
RAM: at least 16 GB in dual-channel mode
Disk Space:70 GB free space for full installation
Graphic Processor: RTX 3060 or RX 6600 for minimum settings
The legendary survival horror franchise from Capcom returns with a massive new entry. The game is being built on an upgraded version of the next-generation RE Engine. The storyline will push players to confront unprecedented biological horrors in a genuinely claustrophobic environment. This title promises to perfectly blend classic exploration, resource management, and terrifying combat sequences.
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To get this model running locally in no time, utilize the built-in WSL tools.
Please follow the instructions listed below to get started.
The tool automatically synchronizes and downloads the model database.
The engine benchmarks your hardware to apply the most effective operational mode.
🔒 Hash checksum: ede83880f6cc2eadee44416c7faf79f3 • 📆 Last updated: 2026-06-22
Processor: Intel i5 or AMD Ryzen 5 for basic 7B models
RAM: enough space for background apps and OS overhead
Disk: 150+ GB for high-context vector database storage
GPU: modern architecture (Ada Lovelace / Ampere minimum)
The Llama-3_3-Nemotron-Super-49B-v1_5 is a large language model designed for both research and commercial applications, featuring a massive 49‑billion parameter architecture. It delivers state‑of‑the‑art performance on reasoning, coding, and multilingual tasks, achieving top scores on standard benchmarks such as MMLU and HumanEval. Thanks to optimized transformer layers and a sparse attention mechanism, the model maintains low inference latency while preserving high accuracy. The model is optimized for deployment on modern GPU clusters, offering scalable throughput and reduced memory footprint through quantization support. These characteristics make it a compelling choice for enterprises seeking high‑performance AI solutions without compromising on cost or speed.
Parameters
49 B
Context length
8 K tokens
Training data
≈1.5 TB text
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