DeepSeek V4 Flash 0731
DeepSeek introduced V4 Flash 0731, a variant of its model featuring three reasoning levels. The model achieves 89.0% on ARC-AGI-1 Semi-Private at $0.02 per task and 61.4% on ARC-AGI-2 Semi-Private at $0.04 per task.
It's great and at the same time unsettling to see how Chinese free AI models compete with the top American ones. Having quality AI models that we can run locally is important, especially so that the metaphorical AI keys aren't held solely by a few select companies worldwide. Plus, it extremely accelerates global AI development.
What is the ARC-AGI benchmark and what is it used for?
ARC-AGI (Abstraction and Reasoning Corpus for General Intelligence) is a benchmark designed to test the general intelligence of AI models. It consists of tasks focused on abstract thinking and logical reasoning that require the ability to recognize patterns and apply them to new situations.
What is the difference between Max, High, and Low reasoning variants?
The variants represent three levels of intensive reasoning effort by the model. The Max variant uses the highest computational effort, High uses medium effort, and Low uses minimal effort. Performance typically varies with the amount of computational resources allocated.
Why is the cost per task higher in ARC-AGI-2 than in ARC-AGI-1?
ARC-AGI-2 contains more difficult tasks that require more computational time and complex reasoning. The higher cost reflects greater complexity and the longer processing time needed to solve these tasks.
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- DeepSeek5
- DeepSeek V4 Flash 0731
- ARC-AGI
- Hugging Face12
- arXiv