OpenAI and Google LLM comparison

OpenAI and Google – the two leading large language model (LLM) developers – have different strengths. LLM technology is being developed in a direction toward differentiation. At the technical level, OpenAI focuses on multi-modal large language models (MLLM) with large numbers of parameters, while Google attaches great importance to the development of LLMs with different parameter counts.

For expanding the application, OpenAI’s strategy is to actively cooperate with companies such as Microsoft and Apple, while Google prioritizes the introduction of its own ecosystem products and services. In addition, it is a common goal for both companies to reduce inference latency.

OpenAI’s and Google's latest LLMs have their own unique features. OpenAI GPT-4o has the advantages of fast response, good understanding, and low computing cost, and is free for paid subscribers. Google Gemini 1.5 Pro has the advantage of strong contextual analysis capabilities. It is multi-lingual and can perform complex reasoning tasks, but currently requires a fee (US$7 per one million tokens).

• Introduction

• Demonstration

• Table 1: OpenAI's and Google's LLM demonstration in May 2024

• Comparison breakdown

• Development focus

• Table 2: OpenAI and Google Gen AI LLMs' development and key information

• Latency issues

• Table 3: Details on how OpenAI and Google LLMs reduce inference latency

• Development direction

• Table 4: Demonstration of Google AI Overview functions

• Table 5: Demonstration of Google Ask Photos functions

• Table 6: Development directions of OpenAI and Google LLM

• Application expansion

• Table 7: Application expansion methods of OpenAI and Google LLM

• Summary

• Table 8: Summary of OpenAI and Google LLM development strategy