“OpenAI has announced a substantial price cut on o3, its flagship reasoning large language model (LMM), slashing costs by a whopping 80% for both input and output tokens.”
“(Recall tokens are the individual numeric strings that LLMs use to represent words, phrases, mathematical and coding strings, and other content. They are representations of the semantic constructions the model has learned through training, and in essence, are the LLMs’ native language. Most LLM providers offer their models through application programming interfaces or APIs that developers can build apps atop of or plug their external apps into, and most LLM providers charge them for the privilege at a cost per million tokens).”
“The update positions the model as a more accessible option for developers seeking advanced reasoning capabilities, and places OpenAI in more direct pricing competition with rival models such as Gemini 2.5 Pro from Google DeepMind, Claude Opus 4 from Anthropic, and DeepSeek’s reasoning suite.”
It all shows rapid price and performance progress from its ChatGPT moment over two years ago at Level 1 AI chatbots, and racing through level 2 and 3 with AI Reasoning and Agents respectively.
This latest model has upgraded reasoning chops, across a range of noteworthy benchmarks.
“Just hours after announcing a big price cut for its o3 reasoning model, OpenAI made o3-pro, an even more powerful version, available to developers.”
“o3-pro is “designed to think longer and provide the most reliable responses,” and has access to many more software tool integrations than its predecessor, making it potentially appealing to enterprises and developers searching for high levels of detail and accuracy.”
The offset of course is waiting a bit longer for the ‘deeper reasoning’ results. The nodels in this mode are more compute intensive, and run a variable cost per prompt as we’ve discussed earlier.
“However, this model will also be slower than what many developers are accustomed to, having access to computer tools that OpenAI claims make the model more accurate.”
“Because 03-pro has access to tools, responses typically take longer than o1-pro to complete. We recommend using it for challenging questions where reliability matters more than speed, and waiting a few minutes is worth the tradeoff,” the company said in an email to reporters.”
It’s good progress from just a couple of months ago:
“OpenAI launched o3 and o4-mini in April, expanding its “o-series” of models that rely on reasoning and can “think with images.” The new model, o3-pro, uses the same underlying model as o3.”
OpenAI’s peers are not sitting still, both here and in China.
“Reasoning models have become a new battleground for model providers, with competitors like Google, Anthropic, and xAI, as well as rivals from China, such as DeepSeek, coming out with their own models designed to think through responses.”
And some additional features have yet to be released:
“Currently, o3-pro is not able to generate images, and OpenAI has disabled temporary chats to resolve a technical issue. ChatGPT’s expanded workspace feature Canvas is also not yet accessible using o3-pro.”
“Some early users claim that o3-pro has been working remarkably, but it is still early days, and the high cost of running it may deter some developers from experimenting with it.”
Additional reviews of the new release are also notable for those seeking more metrics and details. All this new reasoning capabilities at Scale mean a lot more reinforcement learning loops on the AI Tech Stack chart below, especially on the inference legs:
But the overall takeaway is that OpenAI goes into this summer with a pole position this AI Tech Wave in AI Reasoning models. And we’ve got half the year to go. Stay tuned.
(NOTE: The discussions here are for information purposes only, and not meant as investment advice at any time. Thanks for joining us here)
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