The core strengths of the framework are reflected in three areas:
- cost controlThe reasoning cost for Qwen3-8B-CK-Pro can be reduced by 90%+ compared to closed-source APIs such as GPT-4 (Tencent's actual test data).
- data sovereigntyAll data processing is done locally, which is suitable for sensitive areas such as healthcare and finance, and avoids data outflow through APIs.
- scalability: The modular architecture allows for customization, such as adding a LaTeX paper parser or integrating Stable Diffusion for image generation.
In terms of performance, its accuracy (82.1%) exceeds that of Claude 2 (80.3%) and is close to that of GPT-4 (85.7%) in the 200 tasks of the GAIA benchmark. The open source nature also allows the community to continuously optimize the model, for example, developers have already contributed an adaptation module for Llama3-70B.
This answer comes from the articleCognitive Kernel-Pro: a framework for building open source deep research intelligencesThe
May not be reproduced without permission:AI productivity tools " What are the advantages of Cognitive Kernel-Pro over closed source systems?
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