Kategorie-Archive: Safetensors

🔍 Hash-sum: 70e3dbb9f67fac70fa1f72dae171d6bd | 🕓 Last update: 2026-07-18 Verify Processor: Intel i5 or AMD Ryzen 5 for basic 7B models RAM: required: 16 GB absolute minimum for small models Storage: extra room for future model updates and datasets Graphics: 12 GB VRAM minimum required for basic quantization The Qwen3-VL-2B-Instruct-GGUF Model: A Game-Changer in AI Research […]

🔍 Hash-sum: cf41ea0fd87f2b0058bab94d05a8fa42 | 🕓 Last update: 2026-07-18 Verify Processor: Intel i5 or AMD Ryzen 5 for basic 7B models RAM: required: 16 GB absolute minimum for small models Storage: extra room for future model updates and datasets Graphics: 12 GB VRAM minimum required for basic quantization Unveiling the Power of Moss-TTS: Revolutionizing Text-to-Speech Synthesis […]

🔐 Hash sum: a509f7de98244d12c8700c71ea857fba | 📅 Last update: 2026-07-20 Verify CPU: 8-core / 16-thread recommended for orchestration RAM: 32 GB or higher for smooth 32k context lengths Disk Space:70 GB free space for full FP16 weights storage Graphics: TensorRT-LLM / vLLM inference engine compatible chip The Flashy Benefits of GLM-4.7-Flash The GLM-4.7-Flash model is a […]

🔒 Hash checksum: c09b8b2b622cdfc20ff8f2112ff80228 • 📆 Last updated: 2026-07-15 Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: 48 GB needed to prevent memory swapping to disk Disk Space: required: fast PCIe 4.0 drive for instant boots GPU: high memory bandwidth GPU for next-gen local AI pipeline Unlocking the Power of Z-Image-Turbo: Revolutionizing AI Image […]

🖹 HASH-SUM: fc10c9a3054cced8dc23f2b76ba4f15c | 📅 Updated on: 2026-07-18 Verify Processor: 4.0 GHz+ boost clock recommended for CPU inference RAM: required: 16 GB absolute minimum for small models Storage:100 GB free space for HuggingFace cache folder Graphic Processor: RTX 3060 or RX 6600 for minimum 8B VRAM offloading The Benefits of TRELLIS.2-4B: Unlocking Advanced AI Capabilities […]

🔒 Hash checksum: 8eab4662e1331d6e511ec9e7c2204e4e • 📆 Last updated: 2026-07-17 Verify CPU: 8-core / 16-thread recommended for orchestration RAM: high-speed DDR5 memory preferred for CPU offloading Disk Space: at least 100 GB for multiple local LLM variants GPU: high memory bandwidth GPU for next-gen local AI pipeline Unlocking the Potential of Kimi-K2.5: A Revolutionary Language Model […]

🛠 Hash code: e903f66dc4fd5367d9acc4e9dc6e7e72 — Last modification: 2026-07-19 Verify Processor: high single-core performance needed for token latency RAM: high-speed DDR5 memory preferred for CPU offloading Disk Space: 80 GB NVMe SSD required for fast model weights loading Graphics: stable 30+ tk/s at 4-bit quantization on medium setup Unveiling the Power of sam3: A Next-Generation AI […]

💾 File hash: 3edd3cfe37180bef91267be29b9b2397 (Update date: 2026-07-13) Verify CPU: modern architecture (Zen 3 / Alder Lake minimum) RAM: 64 GB to avoid OOM crashes on large contexts Disk Space:70 GB free space for full FP16 weights storage GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference Unlocking the Full Potential of Qwen3.5-9B-AWQ: Performance […]