OpenAI announces 80% price drop for o3, it’s most powerful reasoning model
- OpenAI is reducing the price of o3, its leading reasoning large language model, by 80% starting in June 2025.
- The price drop follows feedback about o3's earlier high rates, which limited adoption despite state-of-the-art performance.
- The new pricing reduces input tokens from $10 to $2 per million and output tokens proportionally, with additional discounts on cached inputs.
- CEO Sam Altman confirmed on X, “we dropped the price of o3 by 80%,” signaling more affordable premium AI options for developers.
- This price adjustment expands access to high-performance AI, encouraging broader usage and placing competitive pressure on other premium models.
16 Articles
16 Articles
How Much Does OpenAI’s o3 API Cost Now? (As of June 2025)
The o3 API—OpenAI’s premier reasoning model—has recently undergone a significant price revision, marking one of the most substantial adjustments in LLM pricing. This article delves into the latest pricing structure of the o3 API, explores the motivations behind the change, and provides actionable insights for developers aiming to optimize their usage costs. What is the o3 API and why does its cost matter? Defining the o3 API The o3 API represen…
OpenAI Slashes ChatGPT o3 API Prices by 80% Without Hurting Performance - THE iBULLETIN
OpenAI is making waves again, but this time it’s not a new model or feature. It’s a major price drop—one that could shift how developers build and scale AI apps overnight. On Wednesday, OpenAI announced it’s reducing prices for its most capable reasoning model, o3, by a staggering 80%. And here’s the kicker: the model’s performance hasn’t changed one bit. That’s not just a marketing line. Independent testers backed it up. What’s Actually Changed…
OpenAI's o3 model gets a massive price cut to compete with Google's AI model
Just ahead of its o3-pro rollout, the company has dramatically cut the price of its o3 model by nearly 80%. o3 delivered top-tier performance on AI benchmarks like Codeforces, SWE-bench, and MMMU. It also came with built-in tool support for web browsing, Python, and more. But despite its capabilities, the model saw slower developer adoption. […]
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