Quantizations
🗂 Hash: 4668991a3d10035006e8ea7a89ec268f • Last Updated: 2026-07-21 Verify Processor: Intel i5 or AMD Ryzen 5 for basic 7B models RAM: fast 5600MHz+ required to avoid memory bottlenecks Disk: 150+ GB for high-context vector database storage Graphics: 12 GB VRAM minimum…
📤 Release Hash: 473e0e09ece4dbb3be05a439a9540c55 • 📅 Date: 2026-07-22 Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: enough space for background apps and OS overhead Disk Space:70 GB free space for full FP16 weights storage Graphics: CUDA Compute Capability 8.0+…
📦 Hash-sum → 497215f8aab12c21a635db80122aafc5 | 📌 Updated on 2026-07-18 Verify CPU: 8-core / 16-thread recommended for orchestration RAM: minimum 16 GB for stable 8B model loading Disk Space: required: fast PCIe 4.0 drive for instant boots Graphic Processor: hardware Tensor…
📦 Hash-sum → 3066f0baff6db4f39e60f435e6c98c35 | 📌 Updated on 2026-07-13 Verify CPU: multi-threading optimized for fast prompt processing RAM: at least 32 GB in dual-channel mode for bandwidth Disk Space: free: 80 GB on system drive for scratch space Graphic Processor:…
🛡️ Checksum: 929e156b73a2792a12e3d52168a6f76c — ⏰ Updated on: 2026-07-14 Verify Processor: Intel i7 / Ryzen 7 for heavy Quantized models RAM: 48 GB needed to prevent memory swapping to disk Disk Space:70 GB free space for full FP16 weights storage GPU:…
📄 Hash Value: 279f55dc0998ba3c332dd808eb87d45e | 📆 Update: 2026-07-11 Verify Processor: Intel i5 or AMD Ryzen 5 for basic 7B models RAM: fast 5600MHz+ required to avoid memory bottlenecks Disk Space: free: 80 GB on system drive for scratch space Graphics:…
📤 Release Hash: 8d79cbada5d6c4d73efd26803695a1ac • 📅 Date: 2026-07-14 Verify Processor: high single-core performance needed for token latency RAM: fast 5600MHz+ required to avoid memory bottlenecks Disk Space: 100 GB for multi-modal model vision components Graphics: 12 GB VRAM minimum required…
Running this model locally is fastest when deployed through a PowerShell script. Review and follow the instructions below. The loader auto-caches the model archive (several GBs included). The deployment tool scans your environment and chooses the ideal parameters. 📎 HASH:…
