OpenAI's O3‑Pro Model: Deep Reasoning, Pricing, Benchmarks, and Access Guide

Model Overview

OpenAI released O3‑Pro, a multimodal deep‑reasoning model that builds on the O3 series. O3‑Pro allocates roughly ten‑fold more compute during training and inference, extending the same scaling law observed for GPT models: more compute and longer inference time improve performance.

Model Naming

GPT‑4.x – basic multimodal model, no deep reasoning.

GPT‑4o (“omni”) – handles text, images, audio.

O3 – reasoning‑oriented multimodal model (text‑centric, limited image support).

O3‑Pro – enhanced O3 with additional compute for deeper step‑by‑step reasoning.

Training and Scaling

In addition to standard internet‑text pre‑training, the O3 series used large‑scale reinforcement learning (RL). OpenAI reported that RL exhibited the same “more compute = stronger performance” scaling as GPT pre‑training. O3‑Pro applied about ten times the compute budget in both training and inference, resulting in higher answer quality.

Benchmark Performance

Across writing, coding, and data‑analysis benchmarks, O3‑Pro consistently outperformed O3, GPT‑4o and GPT‑4.1. Example: when constructing a task‑planning agent, GPT‑4o produced a vague list, whereas O3‑Pro generated a detailed, logically sound plan.

Core Capabilities

Context window ≈ 200 k tokens

Maximum output ≈ 100 k tokens

Knowledge cutoff 1 June 2024

Supports reasoning‑only tokens

API‑only tools: file retrieval, image‑input reasoning, MCP (multimodal conversation programming)

Limitations

Deep‑reasoning requests typically require 1–3 minutes; background mode is recommended.

Output token limit (100 k) is lower than Google’s 1 M limit.

Network search, code interpreter, and computer control are not supported.

Pricing

Per 1 M tokens: $20 for input, $80 for output – an 87 % reduction compared with the retired O1‑Pro, but still about ten times higher than the base O3 model.

Pricing reference: https://platform.openai.com/docs/pricing

Access

ChatGPT Pro users can select “o3‑pro‑2025‑06‑10” in the Playground or the ChatGPT app (replacing O1‑Pro). Developers can call O3‑Pro via the OpenAI API. Enterprise and education accounts will receive access shortly.

To enable in Playground: log in at platform.openai.com, open the Playground, expand the Model dropdown under Prompts, and choose o3‑pro‑2025‑06‑10.

Performance Tests

Word‑count query: O3‑Pro took >34 seconds, while GPT‑4o answered in <2 seconds, illustrating the latency cost of deep reasoning for trivial tasks.

Visual counting test (hand emoji): O3‑Pro reported 5 fingers instead of the actual 6. The error is attributed to bias from training on predominantly five‑finger hands and loss of fine detail in the image encoder.

Cost‑Benefit Considerations

For high‑throughput or latency‑sensitive applications, O3‑Pro’s higher cost and slower response may be prohibitive. For agents that require multi‑step logical reasoning, the model’s deeper reasoning can provide higher quality outputs.

Competing models such as Google Gemini Ultra are rumored to launch soon, potentially offering lower price, faster speed, and stronger programming performance.

Conclusion

The price cut makes O3‑Pro’s advanced reasoning more accessible, though it remains expensive relative to O3. Its value is greatest for applications that truly benefit from deep, multi‑step reasoning.