Condor Opus 14B Exp
Condor-Opus-14B-Exp is a large language model based on the Qwen 2.5 14B modal architecture, focusing on enhanced reasoning capabilities, supporting multilingual and long-context processing.
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Release Time : 3/2/2025
Model Overview
This model is optimized for general reasoning and answering, excelling in context understanding, logical reasoning, and multi-step problem-solving. Through long-chain reasoning models and fine-tuning with specialized datasets, it improves comprehension, structured responses, and conversational intelligence.
Model Features
Enhanced general knowledge
Provides extensive cross-domain knowledge, improving the ability to answer questions accurately and generate coherent responses.
Improved instruction following
Significant progress in understanding and following complex instructions, generating structured responses, and maintaining coherence in long-term interactions.
Versatile adaptability
More resilient to diverse prompts, enhancing the ability to handle a wide range of topics and conversational styles, including open-ended and structured queries.
Long-context support
Supports up to 128K input context tokens and can generate single outputs of up to 8K tokens, suitable for detailed responses.
Multilingual capabilities
Supports over 29 languages, including English, Chinese, French, Spanish, and more.
Model Capabilities
Text generation
Logical reasoning
Multi-step problem-solving
Multilingual support
Long-text generation
Structured response generation
Use Cases
General reasoning
Logical reasoning
Suitable for a wide range of logical reasoning, answering diverse questions, and solving general knowledge problems.
Education and information assistance
Educational assistance
Ideal for providing explanations, summaries, and research-based answers to students, educators, and general users.
Conversational AI and chatbots
Intelligent dialogue agents
Suitable for building intelligent dialogue agents that require context understanding and dynamic response generation.
Multilingual applications
Multilingual content generation
Supports global communication, translation, and multilingual content generation.
Structured data processing
Structured output generation
Capable of analyzing and generating structured outputs such as tables and JSON, suitable for data science and automation.
Long-text content generation
Article generation
Can generate extended responses, including articles, reports, and guides, maintaining coherence in large-scale text outputs.
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