High-speed reasoning model specialized for STEM, competitive code, and analytical pipelines
| Scenario | Input Tokens | Output Tokens | Uncached Cost | With Prompt Caching |
|---|---|---|---|---|
| Short Chat Query | 1,000 | 500 | $0.00330 | $0.00275 |
| Document Summarization | 10,000 | 2,000 | $0.0198 | $0.0143 |
| Codebase & Context Analysis | 100,000 | 20,000 | $0.1980 | $0.1430 |
| Batch Corpus Processing | 1,000,000 | 100,000 | $1.54 | $0.9900 |
Ideal for production workloads demanding reasoning capabilities, deep context depth (128k 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 o4-mini, 1 million input tokens costs $1.10, while 1 million output tokens costs $4.40. If using prompt caching, repetitive input prefixes are discounted to $0.55 per million.
OpenAI o4-mini features a maximum context window of 128,000 tokens (~96,000 words), with a maximum output limit of 65,536 tokens per completion.
OpenAI o4-mini utilizes the OpenAI o200k_base (200k vocabulary). Token counting on TokenMath runs client-side to ensure maximum privacy.
Yes. OpenAI o4-mini supports prompt caching with a cached input rate of $0.55/1M (saving up to 50% on repeated input context).