ZTE-AIM/EmbodiedBrain-7B
VISIONPricing:Input $0.4 / Output $0.8Concurrent Unit Cost:1Model Size:7BQuant:FP8Context Size:32kPublished:Oct 30, 2025License:apache-2.0Architecture:Transformer0.0K Open Weights Featherless Exclusive Cold
EmbodiedBrain-7B is a 7 billion parameter language model developed by ZTE-AIM, designed for general language understanding and generation tasks. With a context length of 32768 tokens, it offers robust performance for applications requiring extensive contextual awareness. This model is suitable for a wide range of NLP use cases, including text summarization, question answering, and content creation.
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Overview
EmbodiedBrain-7B, developed by ZTE-AIM, is a 7 billion parameter language model with a substantial context window of 32768 tokens. This model is engineered for broad applicability across various natural language processing tasks, providing a solid foundation for developers.
Key Capabilities
- General Language Understanding: Proficient in comprehending complex text structures and nuances.
- Text Generation: Capable of producing coherent and contextually relevant text for diverse applications.
- Extended Context Handling: Benefits from its 32768-token context length, allowing for processing and generating longer passages of text while maintaining consistency.
Good for
- Content Creation: Generating articles, summaries, and creative writing pieces.
- Question Answering Systems: Developing systems that can answer queries based on large documents or datasets.
- Conversational AI: Building chatbots and virtual assistants that require understanding and generating natural dialogue over extended interactions.