OpenAI o1-Pro API: Everything Developers Need to Know

Yusuf Ishola· March 21, 2025

OpenAI has just released its o1-Pro model to its API, bringing its most powerful reasoning model to developers. Previously only available to ChatGPT Pro subscribers, this model comes with remarkable capabilities—and a price tag to match.

At $150 per million input tokens and $600 per million output tokens, it's now officially OpenAI's most expensive model, eclipsing GPT-4.5 by a factor of 2x for input and 4x for output costs.

But is it worth the premium? Let's examine what this model offers, how it performs, and whether it justifies its steep price for your development needs.

What's New in o1-Pro: The Quick Rundown

o1-Pro's Technical Capabilities

o1-Pro is OpenAI's next step in reasoning models. Unlike standard o1, which already excels at mathematical and logical reasoning, o1-Pro allocates additional computational resources to the reasoning process.

This means it "thinks harder" about problems, potentially leading to more reliable solutions for complex tasks.

Basic example of using o1-Pro:

// Using the newer Responses API required for o1-Pro
const response = await openai.responses.create({
  model: "o1-pro",
  input: "Explain the implications of Gödel's Incompleteness Theorems for modern mathematics.",
  reasoning: { effort: "high" } // Optional parameter for o1-pro
});

console.log(response.content);

The reasoning parameter with effort set to "high" instructs the model to allocate even more computational resources to its answer—at an increased token cost, of course.

from openai import OpenAI

client = OpenAI(
    api_key="your-api-key",
    base_url="https://oai.helicone.ai/v1",
    default_headers= {
      "Helicone-Auth": f"Bearer {HELICONE_API_KEY}",
    }
)

response = client.responses.create(
    model="o1-pro",
    input="Explain the implications of Gödel's Incompleteness Theorems for modern mathematics."
)
print(response.content)

o1-Pro Pricing: Premium Costs for Premium Results

o1-Pro's pricing makes it OpenAI's most expensive model by a significant margin:

OpenAI o1-Pro Benchmarks and Real-World Performance

o1-Pro's real-world performance has been met with mixed reviews. For some tasks, it shows remarkable capabilities that justify its premium pricing:

• Coding: o1-Pro has remarkable coding abilities, especially when it comes to large codebases and higher-level instructions. Developers report that o1-Pro can analyze massive codebases and identify subtle bugs that were previously overlooked by themselves and other models.
• Mathematical Reasoning: The model shows improved mathematical reasoning capabilities compared to o1, which is already one of the best available models for math.
• Step-by-Step Problem Solving: For multi-step logical reasoning tasks, o1-Pro maintains coherence better than other models.

If you're in the habit of breaking down problems to Sonnet-sized pieces you won't see a benefit. The win is that o1pro lets you stop breaking down one level up from what you're used to

— A Hacker News user

OpenAI o1-Pro Limitations

• Vision Capabilities: Despite handling image inputs, early testing has shown that o1-Pro struggles with basic vision tasks like counting fingers, identifying unusual body postures, and reading analog clocks.
• Processing Speed: Many users report that o1-Pro is significantly slower than other models, making it less suitable for interactive applications requiring quick responses.
• Cost Prohibitive: The extreme pricing creates significant barriers to experimentation and iterative development. One user reported spending $10 on just five simple vision task prompts, with three tests failing.
• Unpredictable Costs: Users report that large context windows can sometimes cause the model to error out, requiring multiple attempts and increasing costs unexpectedly.

Models Comparison: o1-Pro, GPT-4.5, o3-Mini, o1, and GPT-4

o1-Pro Use Cases: When to Pay the Premium

Given its price point, o1-Pro is best suited for specific high-value use cases:

1. Complex Code Refactoring: When dealing with large, complex codebases that could take a human engineer a while to fully comprehend by themselves.
2. Scientific Research: For generating hypotheses or analyzing complex research data where deeper reasoning is valuable.
3. Synthetic Data Generation: Creating high-quality training examples for fine-tuning smaller, specialized models.
4. Legal or Financial Document Analysis: When accuracy and thorough reasoning are worth the premium cost.

For general purposes, models like GPT-4o or o3-mini likely provide better value. Many developers report using o1-Pro selectively as a "final check" or for particularly difficult problems rather than as their primary model.

You might also be interested in:

• GPT-5: Release Date, Features & Everything You Need to Know
• Claude 3.5 Sonnet vs OpenAI o1: A Comprehensive Comparison
• OpenAI o3 Released: Benchmarks and Comparison to o1

Final Thoughts

o1-Pro represents a significant advancement in OpenAI's reasoning capabilities, but its pricing puts it firmly in the "specialty tool" category rather than an everyday solution. For developers working on highly complex problems where accuracy and reliability are paramount, o1-Pro may be worth the premium cost.

For most applications, however, models like o3-mini offer a more economical choice with comparable performance on many tasks.

The release of o1-Pro to the API also signals OpenAI's continued push toward specialized models optimized for specific types of tasks, rather than a one-size-fits-all approach.