o3-pro: token counter & pricing
OpenAI · exact (uses official tokenizer) · pricing as of 2026-05-31.
- Provider
- OpenAI
- API model ID
o3-pro- Context window
- 200,000 tokens
- Input price
- $20.00 per 1M tokens
- Output price
- $80.00 per 1M tokens
- Tokenizer accuracy
- exact (uses official tokenizer)
- Pricing as of
- 2026-05-31
Open the counter to count tokens for o3-pro in real time.
What is o3-pro?
o3-pro is the premium tier of OpenAI's o3 reasoning model, extended internal reasoning before responding, designed for the hardest logic / math / code problems. $20 input / $80 output per 1M tokens, 10× base o3 prices, no cached-input discount.
This is the model you reach for when you've measured o3 falling short and the cost of a wrong answer dwarfs the per-call premium.
How tokens are counted here
OpenAI's o200k_base tokenizer. Browser-side via js-tiktoken. Exact.
But: o3-pro generates substantially more reasoning tokens than o3, typical 10-25× output overhead vs the visible reply. A 200-token visible reply might consume 3,000-5,000 output tokens of internal reasoning. The calculator's per-call cost is visible-tokens only; budget 10-20× the output line for real-world spend.
Pricing notes
$20 input / $80 output per 1M. No cached-input rate, Pro tier doesn't qualify for caching.
For 1,000 input + 200 output visible tokens (realistic billed output 2k-5k with reasoning):
- Visible-only estimate: $0.036 per call
- Realistic with 15× reasoning overhead: $0.116 per call
- At 1M calls: somewhere between $36k and $116k depending on reasoning depth
200K context window.
When to use o3-pro
- Hardest reasoning tasks, multi-step logic, complex math, algorithmic problems where errors compound badly.
- High-stakes single-shot answers, legal arguments, research analysis, complex code architecture.
- Eval ceiling testing, what's the best the o-series can do on this specific problem.
When not to use it:
- Anywhere o3 ($2/$8) is good enough, measure first.
- Real-time chat, latency is high (often 30+ seconds for hard problems).
- Workloads not designed around explicit reasoning. GPT-5.5 Pro ($30/$180) is different positioning.
Common questions
o3-pro vs GPT-5.5 Pro?
GPT-5.5 Pro: $30/$180. o3-pro: $20/$80. o3-pro is 33% cheaper on input, 55% cheaper on output. o3-pro generates more invisible reasoning tokens which narrows the real-world gap. On most reasoning benchmarks they're competitive, test both on your evals.
o3-pro vs Claude Opus 4.8?
Opus 4.8: $5/$25. Opus is 4× cheaper on input, 3.2× cheaper on output, even before considering o3-pro's reasoning-token overhead. For most premium-reasoning workloads, Opus is the rational default; reach for o3-pro only when you've measured it winning on your specific task.
When does the Pro premium pay back?
When a single wrong answer costs you more than ~$100 of downstream rework, o3-pro's per-call premium is paid by avoiding one wrong answer per ~1,000 calls.
Compare o3-pro to other models
- GPT-5.5 (OpenAI, $5.00/$30.00)
- GPT-5.5 Pro (OpenAI, $30.00/$180.00)
- GPT-5.4 (OpenAI, $2.50/$15.00)
- GPT-5.4 Mini (OpenAI, $0.75/$4.50)
- GPT-5.4 Nano (OpenAI, $0.20/$1.25)
- GPT-5.4 Pro (OpenAI, $30.00/$180.00)
- GPT-5.3 (OpenAI, $1.75/$14.00)
- GPT-5.2 (OpenAI, $1.75/$14.00)
- GPT-5.2 Pro (OpenAI, $21.00/$168.00)
- GPT-5.1 (OpenAI, $1.25/$10.00)
- GPT-5 (OpenAI, $1.25/$10.00)
- GPT-5 Mini (OpenAI, $0.25/$2.00)
- GPT-5 Nano (OpenAI, $0.05/$0.40)
- GPT-5 Pro (OpenAI, $15.00/$120.00)
- GPT-4.1 (OpenAI, $2.00/$8.00)
- GPT-4.1 Mini (OpenAI, $0.40/$1.60)
- GPT-4.1 Nano (OpenAI, $0.10/$0.40)
- o3 (OpenAI, $2.00/$8.00)
- o3-mini (OpenAI, $1.10/$4.40)
- o4-mini (OpenAI, $1.10/$4.40)
- GPT-4o (OpenAI, $2.50/$10.00)
- GPT-4o mini (OpenAI, $0.15/$0.60)
- GPT-4 Turbo (OpenAI, $10.00/$30.00)
- Claude Opus 4.8 (Fast Mode) (Anthropic, $10.00/$50.00)
- Claude Opus 4.8 (Anthropic, $5.00/$25.00)
- Llama 3.1 405B (Meta, $3.50/$3.50)