The O1 Pro model from OpenAI boasts impressive reasoning capabilities, making it a powerful tool for complex tasks. While the model's pricing is significantly higher compared to previous models like GPT-4.5 and GPT-4 Mini, its performance on challenging problems like the hexagon problem suggests it may be well-suited for serious scientific work and advanced applications.

The O1 Pro model excels at read reasoning, outperforming GPT-4.5 and GPT-4 in this area. However, it is notably slower than the other two models. Like GPT-4.5 and GPT-4, the O1 Pro can process both text and images, but its output is limited to text.

One of the key features of the O1 Pro is its large context window of 200,000 tokens and the ability to generate up to 100,000 tokens. This allows the model to engage in more in-depth reasoning and generate more comprehensive outputs. However, the model's high pricing, lack of support for the chat completion endpoint, and absence of real-time capabilities may present challenges for some developers.

Despite these limitations, the O1 Pro could be a valuable tool for organizations and researchers working on complex, high-stakes problems that require advanced reasoning capabilities. The model's potential for generating structured output and supporting agentive workflows makes it a promising candidate for specialized applications.

The newly released O1 Pro model from OpenAI comes with a whopping price tag of $150 per million token input and $600 per million output tokens. This makes it twice as expensive as GPT-4.5 and a staggering 1,000 times more expensive than GPT-4 mini. It is now the most expensive model to date.

This pricing structure is clearly not aimed at regular developers, although the model does show impressive performance on complex tasks like the hexagon problem. The high cost could make it prohibitive for many use cases, with the output of a simple task like generating an image of a pelican riding a bicycle costing nearly a dollar.

The O1 Pro model has some unique features, such as a context limit of 200,000 tokens and the ability to generate up to 100,000 tokens. However, it lacks support for the chat completion endpoint, real-time capabilities, and streaming. It is primarily designed for batch processing and serious scientific work, rather than everyday chatbots.

Compared to other models like GPT-4.5 and GPT-4 mini, the O1 Pro is significantly more expensive, with a price that is 10 times higher than O1 and 150 times more than GPT-4 mini. This high cost may limit its accessibility to smaller developers and organizations, while catering to larger institutions and companies willing to pay the premium for its advanced reasoning capabilities.

The O1 Pro model from OpenAI comes with several limitations that developers should be aware of:

1. Pricing: The model is extremely expensive, costing $150 per million token input and $600 per million output tokens. This makes it the most expensive model released by OpenAI to date, being 4 times more expensive than GPT-4.5 and 1000 times more expensive than GPT-4 Mini.

2. Lack of Chat Completion Endpoint: The model does not currently support the chat completion endpoint, which means developers will need to implement their own custom solution if they want to use it for chatbot applications.

3. No Real-Time Capabilities: The model is not available through the Streaming API and can only be accessed through the Responses API, which means it is not suitable for real-time applications.

4. Lack of Access to Reasoning Tokens: While the model performs well on complex reasoning tasks, users do not have access to the underlying reasoning tokens or the chain of thought, which could be valuable for understanding the model's decision-making process.

5. Batch Processing Only: The model is primarily designed for batch processing and is not optimized for interactive or real-time use cases.

6. Rate Limits: The rate limits for the model vary across different pricing tiers, with Tier 1 users getting only 30,000 tokens per minute.

Overall, the O1 Pro model is a powerful but highly specialized tool that is primarily geared towards large institutions and research organizations that can afford the high costs and are willing to work within the model's limitations. Developers looking for more affordable and flexible language models may need to consider alternative options.

The 01 Pro model from OpenAI is significantly more expensive compared to other language models like GPT-4.5 and GPT-4 Mini. The pricing for 01 Pro is $150 per million token input and $600 per million output tokens, which is twice as expensive as GPT-4.5 and a staggering 1,000 times more expensive than GPT-4 Mini.

Despite the high cost, the 01 Pro model does offer some notable capabilities. It is the best model for reasoning tasks compared to the other models mentioned. However, it is also significantly slower in processing text and images compared to GPT-4.5 and GPT-4.

One key difference is that the 01 Pro model does not support the chat completion endpoint, which means developers will need to implement their own solution if they want to use it for chatbots. Additionally, the model does not have real-time capabilities and is only available through the Responses API, making it more suitable for batch processing and serious scientific work rather than everyday chatbot applications.

The 01 Pro model has a context limit of 200,000 tokens and can generate a maximum of 100,000 tokens, which is the same as the other models. It also supports function calling and can generate structured output, making it a potential candidate for agentive workflows.

Overall, the 01 Pro model is a high-performance, reasoning-focused language model, but its extremely high cost may limit its accessibility to most developers. The trend of decreasing prices over time observed with previous OpenAI models may apply to the 01 Pro as well, but for now, it remains the most expensive model on the market.

The O1 Pro model from OpenAI is a high-performance language model designed for advanced reasoning and complex tasks. While the pricing of $150 per million token input and $600 per million output tokens makes it prohibitively expensive for most developers, it does cater to specific market segments and use cases.

One key target market for O1 Pro is large institutions and enterprises that require powerful reasoning capabilities for their internal applications or research purposes. The model's ability to handle complex prompts and generate structured outputs makes it a valuable tool for tasks such as data analysis, decision-making, and scientific exploration. Companies like Grab, as mentioned in the tweet, have seen significant improvements in the accuracy of their in-house applications by leveraging the O1 Pro model.

On the other hand, the high cost and limited feature set (e.g., lack of chat completion endpoint, no real-time capabilities) make it less suitable for everyday developer use cases, such as building chatbots or general-purpose language applications. For these use cases, more affordable models like GPT-3.5 or GPT-4 Mini may be more appropriate.

The pricing trend observed with previous OpenAI models suggests that the cost of O1 Pro may decrease over time, potentially making it more accessible to a wider range of users. However, for now, it remains a specialized tool primarily targeted at large organizations and research institutions that can justify the significant investment required to utilize its advanced reasoning capabilities.

The introduction of OpenAI's 01 Pro model has certainly stirred up the AI landscape. While the model boasts impressive reasoning capabilities, its astronomical pricing of $150 per million token input and $600 per million output tokens makes it prohibitively expensive for most developers.

The model's strengths lie in its superior reasoning performance compared to GPT-4.5 and GPT-4 Mini, but it lacks key features like chat completion support and real-time capabilities. This suggests that 01 Pro is primarily targeted at large institutions and research organizations willing to pay the premium for advanced reasoning abilities.

The pricing trend observed with previous OpenAI models, where a 10x reduction in cost occurs over a year, provides hope that 01 Pro's pricing may become more accessible over time. However, the current pricing structure poses a significant barrier for widespread adoption, especially among individual developers and smaller businesses.

Ultimately, the success of 01 Pro will depend on whether the benefits of its advanced reasoning capabilities can justify the substantial financial investment required. As the AI landscape continues to evolve, it will be interesting to see how OpenAI navigates the balance between pricing and accessibility for its cutting-edge models.