OpenAI · GPT-4o
GPT-4o pricing calculator for API teams
GPT-4o is the workhorse multimodal tier many teams choose when they need strong quality without always jumping to the largest legacy GPT-4 price points. This guide explains GPT-4o token pricing with scenarios you can paste into stakeholder decks.
The calculator section is pre-filled for a typical “smart assistant” mix: a dense prompt with moderate-length answers. Toggle comparisons to GPT-4o mini, Claude Sonnet, or DeepSeek to see relative savings on identical token counts.
Throughout, remember that official OpenAI invoices win over any third-party estimate—treat this page as engineering-grade planning, not a quote.
What makes GPT-4o different for budgeting
GPT-4o balances latency and quality for production assistants that blend text with occasional vision or audio depending on your integration. From a finance perspective, the important part is the published dollars-per-thousand-token curve for input and output.
Because GPT-4o often replaces older GPT-4 Turbo paths, compare both on the same logged traffic before migrating—sometimes output length habits shift when prompts are tuned for a new model personality.
Input vs output tokens on GPT-4o
Input tokens accumulate from every character the tokenizer sees in your request payload. Output tokens accumulate from the model’s completion, including hidden formatting characters in JSON.
If your product lets users ask for “detailed” answers, add a completion token ceiling in product logic—not just in prompts—so spend stays aligned with UX expectations.
Context window and retrieval cost
RAG pipelines love large contexts, but finance should price retrieval per chunk. If you embed five chunks of 900 tokens each, you pay for those tokens every turn unless you cache or compress.
Summarize stable reference material offline and inject short bullet summaries into the system message to buy back headroom for user-specific data.
GPT-4o token usage examples
Numbers below are illustrative; plug in your own medians in the calculator.
| Scenario | Prompt tokens | Output tokens | Model (est.) | Cost / request |
|---|---|---|---|---|
| Product marketing draft | 1100 | 950 | GPT-4o | $0.0123 |
| Vision captioning (text side) | 1800 | 220 | GPT-4o | $0.0067 |
| Customer chat reply | 650 | 180 | GPT-4o | $0.0034 |
Figures use rates from config/models.php; confirm against your provider before billing decisions.
Monthly GPT-4o API cost sketches
Daily requests × per-request cost × working days per month.
-
SaaS assistant
2,500 user-visible replies per weekday.
- Per request
- $0.0066
- Monthly (2500 req/day × 22 days)
- $361.62
-
Batch enrichment job
600 jobs per night with longer outputs.
- Per request
- $0.0180
- Monthly (600 req/day × 22 days)
- $237.60
Developer use cases
GPT-4o is a strong default for customer-facing assistants, multi-step copilots, and medium-length content workflows where mini models would require heavy guardrails. Pair it with GPT-4o mini for intent detection to keep blended cost low.
Quick comparison with nearby tiers
Seeing GPT-4o beside mini and Claude rows makes trade-offs obvious for the same workload.
| Model | Provider | Input | Output |
|---|---|---|---|
| GPT-4o | OpenAI | $0.0025 / 1K in | $0.0100 / 1K out |
| GPT-4o mini | OpenAI | $0.0002 / 1K in | $0.0006 / 1K out |
| GPT-4 Turbo | OpenAI | $0.0100 / 1K in | $0.0300 / 1K out |
| Claude 3.5 Sonnet | Anthropic | $0.0030 / 1K in | $0.0150 / 1K out |
FAQ: GPT-4o API costs
Short answers mirror the structured data on this page for search engines and readers.
- When should I downgrade from GPT-4o to GPT-4o mini?
- When error rates stay acceptable on simpler prompts—especially classification, extraction, or templated replies—mini wins on unit economics. Keep GPT-4o on high-risk paths.
- Does multimodal inputs change token counting?
- Yes. Images and audio are represented as tokens according to the provider’s rules. Treat media-heavy features as separate budget lines and measure them in staging.
- How do I explain GPT-4o pricing to non-technical stakeholders?
- Describe an average conversation as “prompt size + answer size,” show the per-thousand-token price, multiply by expected conversations, then add a growth buffer.
- Can I trust these estimates for contractual planning?
- Use them for internal planning only. Sign contracts based on vendor quotes and observed usage from a pilot.