Text model
gpt-5.4-nano pricing
OpenAI charges $0.20 per million input tokens and $1.25 per million output tokens for gpt-5.4-nano, and $0.02 for cached input. Below: every rate that applies, what common workloads cost, and cheaper options.
- Input
- $0.20/ 1M
- Output
- $1.25/ 1M
- Cached input
- $0.02/ 1M
- Context
- 272Ktokens
Retires 2027-04-01. Move to a current GPT model. npx @veqen/sdk scan finds every place your code uses it.
All rates
| Tier | Input | Output | Cache read | Cache write |
|---|---|---|---|---|
| Standard | $0.20 | $1.25 | $0.02 | — |
| Batch | $0.10 | $0.625 | $0.01 | — |
| Flex | $0.10 | $0.625 | $0.01 | — |
USD per million tokens. Long-context tiers apply when the whole prompt, cached tokens included, passes the threshold.
Work it out
What common workloads cost
| Workload | Per call | Cost per call | Calls a month | Per month |
|---|---|---|---|---|
| Chat reply | 1,500 input and 400 output tokens | $0.0008 | 100,000 | $80.00 |
| RAG answer, cached context | 2,000 fresh + 4,000 cached input, 500 output | $0.00111 | 100,000 | $110.50 |
| Agent step | 4,000 fresh + 8,000 cached input, 800 output | $0.00196 | 250,000 | $490.00 |
| Batch summary | 3,000 input and 300 output tokens via the Batch API | $0.000487 | 1,000,000 | $487.50 |
Planning a mix of models? Simulate a workload with gpt-5.4-nano, alongside anything else you run.
Cheaper options
Current models that cost at least 15% less for a typical chat reply. Cheaper isn't always equivalent: test quality on your own prompts, then use veqen diff to see the impact at your volume.
| Model | Chat reply | Saving |
|---|---|---|
| openai/gpt-4o-mini-search-preview | $0.000465 | 42% |
| openai/gpt-6-luna | $0.00035 | 56% |
| nebius/deepseek-ai/DeepSeek-R1-Distill-Llama-70B | $0.000675 | 16% |
| watsonx/meta-llama/llama-3-2-11b-vision-instruct | $0.000665 | 17% |
Price history
No price changes since Veqen started tracking this model.
Also billed under: gpt-5.4-nano-2026-03-17.
Compare
Last verified with price book 2026-10-22. Sources: OpenAI pricing and LiteLLM's MIT-licensed price file. Track every call to this model, per customer or project: install the SDK.