Loaders
📡 Hash Check: 2b876371472982ae0dd680487fbad875 | 📅 Last Update: 2026-07-19 Verify Processor: high single-core performance needed for token latency RAM: required: 16 GB absolute minimum for small models Disk Space: 80 GB NVMe SSD required for fast model weights loading Graphics: stable 30+ tk/s at 4-bit quantization on medium setup Unlocking the Potential of Open-Source Language […]
Quick Run gemma-4-E2B-it-GGUF Offline on PC Read More »
📘 Build Hash: d67179f46b4116f4d10cffc52c5f4e74 • 🗓 2026-07-16 Verify Processor: Intel i7 / Ryzen 7 for heavy Quantized models RAM: enough space for background apps and OS overhead Disk Space: 100 GB for multi-modal model vision components GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference Unlocking the Power of PaddleOCR-VL-1.6-GGUF: Revolutionizing Vision-Language Recognition
📦 Hash-sum → acfe9d0e1371fbf7edfeb877e1077f76 | 📌 Updated on 2026-07-20 Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: 32 GB or higher for smooth 32k context lengths Disk Space: at least 100 GB for multiple local LLM variants Graphics: CUDA Compute Capability 8.0+ required for flash-attention This framework has been extensively tested on a variety
How to Deploy GLM-OCR Locally via LM Studio For Beginners Read More »