Knowledge Base
Artificial Intelligence & Machine Learning
Wan 2.6 (Alibaba)
Wan 2.6 by Alibaba is a frontier multimodal AI model that generates cinematic 1080p videos with synchronized audio, text rendering, and consistent characters from a single prompt.
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Mercury 2
Mercury 2 is a reasoning-first AI model by Inception Labs with a 2M token context window, designed for deep logical reasoning, engineering analysis, and large-scale research across massive datasets.
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Kimi K2.5
Kimi K2.5 is a 1T-parameter open-weight multimodal AI model by Moonshot AI, built for coding, agent orchestration, and long-horizon reasoning across text, images, video, and complex documents.
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MiMo-V2 Pro
Xiaomi MiMo-V2 Pro is a trillion-parameter AI model built for autonomous agents, offering a 1M token context window, high-speed inference, and advanced reasoning for coding, research, and enterprise AI.
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DeerFlow
DeerFlow by ByteDance is an open-source AI agent framework that turns LLMs into autonomous systems capable of deep research, coding, and complex multi-step workflows with sandbox execution.
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Whisper.cpp
Whisper.cpp is a high-performance C++ port of OpenAI Whisper. Enable private, real-time, and offline speech-to-text on any device with minimal memory footprint and hardware acceleration.
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Qwen 3.5 SLM (Small Model Series)
Qwen 3.5 SLMs bring frontier AI to the edge. With 0.8B to 9B parameters, these native multimodal models offer 262K context and 201-language support for private, low-latency AI agents.
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Hybrid Search
Hybrid Search combines Keyword and Vector retrieval to maximize AI accuracy. Match exact terms while understanding semantic intent to power the most reliable RAG systems and AI agents.
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GraphRAG (Graph Retrieval-Augmented Generation)
GraphRAG combines Knowledge Graphs with Vector Search to enable global reasoning. Map relationships across datasets to answer complex, multi-hop questions with unparalleled AI accuracy.
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Top Open-Source Models (2026)
Open-source models like Llama 4 and Qwen 3.5 offer frontier AI performance with total privacy. Run high-performance LLMs on your own hardware to enable secure, cost-effective AI agents.
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Parameter-Efficient Fine-Tuning (PEFT)
PEFT allows you to fine-tune massive AI models at a fraction of the cost. Update <1% of parameters to adapt LLMs to your brand voice or niche data without the need for massive GPU clusters.
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Small Language Models (SLMs)
Small Language Models (SLMs) provide high-efficiency AI for niche tasks. Run powerful, private, and low-latency models on edge devices while reducing cloud costs and energy consumption.
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