Maximum compute reasoning model for PhD-level research and formal theorem proving Need a token count first? Use the GPT token counter.
o3-pro-2026-06-01| Scenario | Input Tokens | Output Tokens | Uncached Cost | With Prompt Caching |
|---|---|---|---|---|
| Short Chat Query | 1,000 | 500 | $0.0600 | N/A |
| Document Summarization | 10,000 | 2,000 | $0.3600 | N/A |
| Codebase & Context Analysis | 100,000 | 20,000 | $3.60 | N/A |
| Batch Corpus Processing | 1,000,000 | 100,000 | $28.00 | N/A |
Tier 1 (free tier) reference limits — your account's actual quota may be higher.
Ideal for production workloads demanding reasoning capabilities, deep context depth (256k tokens), and reliability from OpenAI. Excellent when predictable tokenomics and prompt caching support are paramount.
If your use-case requires sub-second streaming latency or ultra-high frequency classification at micro-cent pricing, consider lighter budget options such as Gemini Flash-Lite or Claude Haiku. For deep formal logic, consider dedicated reasoning models like o3.
For OpenAI o3-pro, 1 million input tokens costs $20.00, while 1 million output tokens costs $80.00. If using prompt caching, repetitive input prefixes are discounted to $10.00 per million.
OpenAI o3-pro features a maximum context window of 256,000 tokens (~192,000 words), with a maximum output limit of 100,000 tokens per completion.
OpenAI o3-pro utilizes the OpenAI o200k_base (200k vocabulary). Token counting on TokenMath runs client-side to ensure maximum privacy.
No, OpenAI o3-pro does not currently advertise prompt caching discounts on its standard API tier.