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For a decade, knowledge graphs were an academic idea with few real use cases, held back by the cost of building and maintaining the schema. LLMs have changed that equation: they now extract entities automatically and help anchor answers, audit reasoning, and support agents without hallucinating.
Choosing an open LLM for enterprise in 2024 is no longer just Llama 2: Mistral, Mixtral, Qwen, Yi, DeepSeek, and Phi-2 all compete with different licences and sizes. The criteria that actually decide are commercial licence, available hardware, language support, and your own evaluation on real use cases, not just the trendy benchmark.
Cohere Embed v3 is an embedding model that distinguishes queries from documents via the input_type parameter and scores intrinsic text quality, with multilingual support for over 100 languages at 1024 dimensions. It costs $0.10 per million tokens versus OpenAI's $0.02, and delivers better recall in multilingual RAG.
