AI models directory for capability-aware discovery

Llama 3.3 70B is a large language model from Meta, designed for general assistant and reasoning tasks. It is part of the Llama family and is known for its strong performance, open weights, and extensive ecosystem support. The model is suitable for self-hosted or customizable AI stacks, making it a popular choice for teams that need a capable open model with fine-tuning and inference flexibility.

Mixtral 8x22B Instruct is a sparse mixture-of-experts (MoE) large language model developed by Mistral AI, designed for self-hosted deployment and fine-tuning. It balances high performance with open availability, making it a strong candidate for teams seeking control over their AI stack without relying on closed APIs.

Qwen2.5 72B Instruct is an open-weight large language model developed by Alibaba Cloud, optimized for instruction-following tasks with strong bilingual support in Chinese and English. It is designed for self-hosted or customizable AI stacks, general assistant and reasoning workloads, and coding assistants. The model offers practical deployment flexibility through open-weight or partner stacks, balancing control, cost, and compliance.

Qwen is a family of large language models developed by Alibaba Cloud, covering chat, code, and multimodal variants. Designed for enterprise deployment, Qwen models are available in various sizes (1.8B to 72B parameters) and support both open-source and commercial use under the Qwen License. They excel in natural language understanding, code generation, mathematical reasoning, and multimodal tasks, with options for local deployment, cloud API, and fine-tuning.

GLM-4 is the latest generation of the General Language Model (GLM) series developed by Zhipu AI. It is a bilingual (Chinese and English) large language model with 130 billion parameters, supporting both API access and open-source releases. The model excels in long-context understanding, multimodal tasks, and agent-based applications, with a context window of up to 128K tokens. It is designed for a wide range of NLP tasks including text generation, reasoning, and code synthesis.

Gemma 2 27B is an open-weight language model from Google, designed for self-hosted and customizable AI stacks. It offers strong performance for general assistant and reasoning tasks, backed by Google's ecosystem and available under a permissive license.