Octopus-V2

Octopus-V2-2B is a 2B LLM running on mobile devices with performance exceeding GPT-4.

CommonProductProductivityLarge Language ModelMobile Device Optimized

Developed by Stanford University's NexaAI, Octopus-V2-2B is an open-source large language model with 2 billion parameters, specifically tailored for Android API function calls. It utilizes a unique functional tokenization strategy for both training and inference, achieving performance comparable to GPT-4 while improving inference speed. Octopus-V2-2B is particularly suited for edge computing devices, allowing for direct on-device execution and supporting a wide range of applications.

2B LLM running on mobile devices
Performance exceeding GPT-4
Support for Android API function calls
Functional tokenization strategy enhances inference speed and accuracy

Suitable for scenarios requiring efficient language processing on mobile devices
such as smart home control and mobile app development.

Developers leverage Octopus-V2-2B to create localized voice control functionalities for smart home devices.
Automotive systems utilize Octopus-V2-2B for faster voice interaction response times.
Mobile app developers use Octopus-V2-2B to optimize their application's natural language understanding capabilities.

Visit

Octopus-V2 Visit Over Time

Monthly Visits

20899836

Bounce Rate

46.04%

Page per Visit

5.2

Visit Duration

00:04:57

Octopus-V2 Visit Trend

Octopus-V2 Visit Geography

Octopus-V2 Traffic Sources

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Octopus-V2

Octopus-V2 Visit Over Time

Octopus-V2 Visit Trend

Octopus-V2 Visit Geography

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