Google has reduced the price of its Gemini 1.5 Flash model by around 80% from its original price of $0.35 per million input tokens and $1.05 per million output tokens.
Gemini 1.5 Flash will now cost $0.075 per million input tokens and $0.3 per million output tokens, almost half the price of OpenAI’s GPT-4o mini.
The announcement follows research and analysis company GlobalData ranking Google’s Gemini LLM the most competitive against seven other competing LLMs including OpenAI GPT, IBM Granite and Microsoft Phi.
GlobalData’s Large Language Models Competitive Landscape Assessment published in July named Google the “leader” in large language models due to “a combination of highly developed model capabilities in the Gemini family and sophisticated enterprise tooling to build and scale GenAI applications.”
While OpenAI ranked second and was scored very highly amongst competitors, the company’s lack of AI Guardrails cost OpenAI the top spot.
AI Guardrails were one of six measures used in the competitive landscape report to determine how businesses can make the best buying choice.
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Guardrails include transparency in how data is managed and secured, as well as ethical considerations such as avoiding biases and respecting the privacy of content creators.
OpenAI had originally undercut Google by pricing their GPT-4o model at $0.15 per million input tokens and $0.6 per million output tokens – in a bid to remain an affordable and accessible option.
The LLM Competitive Landscape Assessment points to a possible explanation for pricing strategies at Google stating: “Google has a competitive advantage in creating and maintaining LLMs at a low cost and in real time because it has a vast repository of content that is updated frequently. This edge is enhanced through Google Gemini 1.5 Pro’s one-million token context window.”
Meta is also able to offer a low-cost LLM with its Llama model offered free of charge.
Meta was ranked seventh in the report due partly to their issues with privacy – such as plans to use data from European users’ social media posts to train its AI models.
The company’s Llama LLM did score highly for its platform availability and large ecosystem with downloads for the model currently surpassing 170 million.
Other models ranked in the report were Amazon Titan, Anthropic Claude, and Cohere Command with Cohere ranking the lowest due to their lack of readiness to adapt to the changing and specialised needs of users.
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