o3-mini: token counter & pricing
OpenAI · exact (uses official tokenizer) · pricing as of 2026-05-31.
- Provider
- OpenAI
- API model ID
o3-mini- Context window
- 200,000 tokens
- Input price
- $1.10 per 1M tokens
- Output price
- $4.40 per 1M tokens
- Tokenizer accuracy
- exact (uses official tokenizer)
- Pricing as of
- 2026-05-31
Open the counter to count tokens for o3-mini in real time.
What is o3-mini?
o3-mini is the smaller, cheaper member of OpenAI's o-series reasoning models. Same approach as o3 (extended internal reasoning before responding) at roughly half the price: $1.10 input / $4.40 output per 1M tokens.
For most reasoning workloads where you don't need o3's full capacity, o3-mini is the rational default.
How tokens are counted here
OpenAI's o200k_base tokenizer. Browser-side via js-tiktoken. Exact.
But: o-series produces a lot of "reasoning tokens", internal chain-of-thought tokens that count toward your output bill but don't appear in the final response. A 200-token reply might consume 1,500-3,000 output tokens of internal reasoning. The calculator above shows the visible output count; actual billed output is typically 5-15× higher.
Pricing notes
$1.10 input / $4.40 output per 1M. Cached input $0.55/M.
For 1,000 input + 200 output visible tokens (real billed output likely 1k-3k tokens with reasoning):
- Visible-only estimate: $0.0019 per call
- Realistic with reasoning overhead (10× output): $0.013 per call
200k context window, same as the rest of the o-series.
When to use o3-mini
- Cost-sensitive reasoning workloads that don't need o3's full capacity.
- Multi-step math / logic / code where o3-mini measurably beats GPT-5.2 ($1.75/$14) for your task.
- Eval-set work where you're testing reasoning capability at lower cost than o3.
When not to use it:
- Real-time chat, o-series latency is too high.
- Routine classification or extraction, wildly overspec'd, and reasoning tokens balloon the bill.
- Hardest reasoning, escalate to o3 ($2/$8) or o3-pro ($20/$80).
Common questions
o3-mini vs o4-mini?
Both priced at $1.10/$4.40. o4-mini is the newer generation with broader reasoning improvements; o3-mini stays on the API for production workloads pinned to its behavior profile. For new work, default to o4-mini.
o3-mini vs GPT-5.2 for reasoning?
GPT-5.2 ($1.75/$14) doesn't generate the invisible reasoning tokens that inflate o-series costs. On many tasks GPT-5.2 is the cheaper effective choice; on hardest reasoning o3-mini still wins. Run your own evals.
Caching savings?
$0.55/M cached input is 50% off standard. Lower discount than the GPT-5 family (typically 90% off), this is structurally the case for o-series caching today.
Compare o3-mini 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-pro (OpenAI, $20.00/$80.00)
- 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 Haiku 4.5 (Anthropic, $1.00/$5.00)
- Gemini 2.5 Pro (Google, $1.25/$10.00)
- Qwen 2.5 72B (Alibaba, $0.90/$0.90)