Kimi K3
Kimi K3 — это ведущий инструмент искусственного интеллекта для оптимизации задач в категории LLM models.
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Kimi K3's full model weights are released under the Kimi K3 License, making frontier intelligence openly available for research, deployment, and further innovation.
The model understands and processes text, images, and video within the same unified architecture, powered by its native multimodal design.
Kimi K3 supports an extensive context window of 1,048,576 tokens, enabling it to handle and reason over very long inputs and complex tasks.
The model is built on Kimi Delta Attention (KDA) and Attention Residuals (AttnRes), which are key components of its new architectural design.
Utilizes a Mixture-of-Experts (MoE) architecture with a Stable LatentMoE framework, activating 16 out of 896 experts, yielding a 2.5x improvement in scaling efficiency.
Kimi K3 is a large-scale model with a total of 2.8 trillion parameters, making it a 3T-class model, with 104 billion parameters activated per token.
The model employs MXFP4 weights and MXFP8 activations, utilizing quantization-aware training for optimized performance and efficiency.
Подробная информация о ценах
- Open-weight model, promoting accessibility for research and innovation.
- Native multimodal capabilities (text, images, video) within a single model.
- Exceptional 1-million-token context window for handling extensive inputs and complex tasks.
- Advanced architecture (KDA, AttnRes, Stable LatentMoE) provides significant scaling efficiency.
- High performance across various benchmarks for reasoning, knowledge, coding, and agentic tasks.
- Designed for frontier intelligence in long-horizon coding, knowledge work, and reasoning.
- No explicit limitations or drawbacks are mentioned in the provided official documentation.
What is Kimi K3?
What are the key architectural innovations in Kimi K3?
What modalities does Kimi K3 support?
Is Kimi K3 an open-source model?
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