Quantizations

🧩 Hash sum → 5e7a6390310f5e57eabc6e2a6b6f0367 — Update date: 2026-07-16 Verify Processor: 6-core 3.5 GHz minimum required RAM: required: 16 GB absolute minimum for small models Disk Space: 80 GB NVMe SSD required for fast model weights loading Graphics: 12 GB VRAM minimum required for basic quantization Performance Overview for WanVideo_comfy_fp8_scaled Model The WanVideo_comfy_fp8_scaled model is […]

📡 Hash Check: ef6b03448b25b14eb9c6be550090c773 | 📅 Last Update: 2026-07-14 Verify Processor: 6-core 3.5 GHz minimum required RAM: high-speed DDR5 memory preferred for CPU offloading Storage:100 GB free space for HuggingFace cache folder Graphics: TensorRT-LLM / vLLM inference engine compatible chip The Quantum Leap in Large Language Models The Qwen3.6-35B-A3B-MTP-GGUF model is at the forefront of […]

📎 HASH: fb1dd978ec049c61c88c3ba42738b669 | Updated: 2026-07-14 Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: required: 16 GB absolute minimum for small models Disk: 150+ GB for high-context vector database storage GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference Unlocking the Full Potential of Qwen3.5-122B-A10B Qwen3.5-122B-A10B is a revolutionary language model that […]

🔍 Hash-sum: e3e12e28995d74426d2231945babc677 | 🕓 Last update: 2026-07-13 Verify CPU: 8-core / 16-thread recommended for orchestration RAM: 64 GB to avoid OOM crashes on large contexts Disk Space: at least 100 GB for multiple local LLM variants Graphics: stable 30+ tk/s at 4-bit quantization on medium setup Unlocking the Power of Qwen3.6-35B-A3B-GGUF: A Revolutionary Language […]