Octopus V2

On-device 0.5B LLMs, voice/text in, action out, outperform GPT-4.

Octopus V2 Highlights

On-device model

A 0.5 billion-parameter language model developed for high-performance function calling on edge devices.

Functional tokens

Uses a novel 'functional token' strategy to reduce context length by 95%.

Blazing fast

Demonstrates a 35x faster inference speed compared to the RAG solution, and is 4x faster than GPT-4o.

Highly accurate

Achieves 98%+ function call accuracy, surpassing previous models and matching the performance of GPT-4.

Octopus V2 Demo Video

Mac OS

Windows OS

Demo by Community Member Ishwar

On-device language model for super agent

On-device language model for super agent: Octopus-V2-2B, an advanced open-source language model with 2 billion parameters, represents Nexa AI's research breakthrough in applying large language models (LLMs) for function calling. Octopus-V2-2B introduces a unique functional token strategy for both its training and inference stages. This approach not only allows it to achieve performance levels comparable to GPT-4 but also significantly boosts its inference speed beyond that of RAG-based methods.

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