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o1

Model ● Covered in 17 stories Compare ⇄ + Follow

o1 is an OpenAI reasoning model that uses reinforcement learning and chain-of-thought techniques to solve complex problems by allocating additional computation during inference. Since its release, o1 has become a benchmark for reasoning capabilities in tasks like mathematics and coding, with companies like Rogo and Endex integrating it into financial analysis applications, while competitors including DeepSeek and Alibaba have released models matching or exceeding its performance at lower costs.

Updated 3 August 2026

Specifications

No specifications recorded yet.

Latest developments

Controlling Reasoning Effort in LLMs Ahead of AI · 2 weeks ago · 26

Reinforcement Learning Heats Up, White House Orders Muscular AI Policy, and more... The Batch · 28

Why We Think Lilian Weng · 1 year ago · 4

Qwen3: Think Deeper, Act Faster Qwen · 1 year ago · 1

The State of Reinforcement Learning for LLM Reasoning Ahead of AI · 1 year ago · 50

Introducing OpenAI o3 and o4-mini OpenAI Blog · 1 year ago · 7

Building an autonomous financial analyst with o1 and o3-mini OpenAI Blog · 1 year ago · 4

Using OpenAI o1 for financial analysis OpenAI Blog · 1 year ago · 40

Timeline

Month Quarter Year

July 2026

May 2025

1 May Why We Think

April 2025

OpenAI releases o3 and o4-mini models with advanced reasoning and integrated tool access Model release

28 Apr Qwen3: Think Deeper, Act Faster
19 Apr The State of Reinforcement Learning for LLM Reasoning
16 Apr Introducing OpenAI o3 and o4-mini

February 2025

January 2025

December 2024

20 Dec Deliberative alignment: reasoning enables safer language models
17 Dec OpenAI o1 and new tools for developers
5 Dec OpenAI o1 System Card

September 2024

OpenAI releases o1-mini and demonstrates o1 reasoning model applications across genetics, economics, physics, and coding Model release

12 Sep OpenAI o1-mini
12 Sep OpenAI o1 Contributions
12 Sep Coding with OpenAI o1
12 Sep Economics and reasoning with OpenAI o1

Relationships

Products & technology

OpenAI develops this model · 11 sources
o1-mini derived from this model · 1 source
Endex deploys this model · 1 source
Rogo integrated with this model · 1 source
U.S. National Laboratories deploys this model · 1 source

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TLDRocket 3 August 2026

The story of AI in August 2026 is one of consolidation meeting enforcement. Alibaba's Qwen3.8-Max, a 2.4-trillion-parameter mixture-of-experts model with a million-token context window, arrives as a direct challenge to OpenAI and Anthropic's frontier offerings—priced at $2 per million input tokens, it's positioning itself as the capable-and-cheaper alternative that China's AI push has long promised. But the more consequential development is structural: enterprises are finally getting the plumbing to actually deploy these models. June, backed by Salesforce's Marc Benioff, raised $20 million to automate AI integration into legacy systems, scanning corporate infrastructure and generating deployment workflows without expensive consultant fees. This solves what's become clear as the real bottleneck—not model capability, but implementation friction in messy, heterogeneous corporate environments.

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