OpenAI pricing guide details
Pricing Overview
OpenAI uses a pure usage-based pricing model for its API platform, charging per million tokens processed. There are no monthly subscriptions or seat licenses on the API side — you pay only for what you consume. GPT-5.4 is the flagship model for complex reasoning tasks, GPT-5.4 mini sits in the mid-range for everyday production workloads, and GPT-5.4 nano delivers a low cost for high-volume, latency-sensitive applications. OpenAI also offers enterprise plans with custom pricing for organizations that need dedicated support, data residency controls, and priority processing.
Plan Comparison
OpenAI’s official API pricing lists three GPT-5.6 models. Each has a 1.05M context length and 128K maximum output tokens.
| Model | Input Price (per 1M tokens) | Output Price (per 1M tokens) | Context Length | Max Output Tokens |
|---|---|---|---|---|
| GPT-5.6 Sol | $4.00 | $20.00 | 1.05M | 128K |
| GPT-5.6 Terra | $2.00 | $12.00 | 1.05M | 128K |
| GPT-5.6 Luna | $0.20 | $1.20 | 1.05M | 128K |
The listed prices are standard processing rates for context lengths under 270K. The public documentation does not state how to select among these models for a particular workload or provide comparative quality guidance; buyers should compare expected input and output token volumes with the published rates and confirm the context-length requirements of their intended use.
Hidden Costs and Considerations
Output tokens are the real cost driver — at 5-6x the input price, a chatbot generating lengthy responses will burn through budget fast. Context window usage also matters: every token of context is billed as input, so long prompts on GPT-5.6 Sol add up quickly at $4.00 per million input tokens. We flag that zero data retention and HIPAA BAA compliance require enterprise agreements, which carry undisclosed pricing. Fine-tuning, Realtime API access, and DALL-E/Whisper usage carry separate charges not reflected in the base token pricing above.
Cost Estimates by Team Size
OpenAI's API pricing page lists GPT-5.6 Terra at $2.00 per 1M input tokens and $12.00 per 1M output tokens. These are standard processing rates for context lengths under 270K.
| Pricing input | Officially listed value |
|---|---|
| Model | GPT-5.6 Terra |
| Input price | $2.00 per 1M tokens |
| Output price | $12.00 per 1M tokens |
| Context length | 1.05M |
| Max output tokens | 128K |
The public documentation does not provide team-size usage assumptions, monthly token volumes, or total monthly cost estimates. Buyers should confirm their expected input and output token volumes, context-length requirements, and whether their workloads fall within the stated standard-processing context-length condition before estimating spend.
How OpenAI Pricing Compares
OpenAI's usage-based model contrasts sharply with competitors that bundle AI capabilities into fixed monthly plans. We see OpenAI as the better fit for teams with variable or unpredictable workloads, while subscription-based alternatives suit predictable, bounded use cases.
| Platform | Pricing Model | Starting Price | Best For |
|---|---|---|---|
| OpenAI | Usage-based (per token) | $0.20 per 1M tokens (nano) | Variable API workloads |
| Anthropic | Freemium + usage-based | Pro $20/month, Team $25/user/month | Teams wanting fixed monthly costs |
| Fusedash | Usage-based (token packs) | $5 token pack | Budget-conscious prototyping |
| HypeScribe | Fixed subscription | — | Transcription-focused workflows |
OpenAI holds a clear advantage on model variety and context window size, but Anthropic offers a more predictable cost structure with its flat-rate plans. For pure cost-per-token, GPT-5.4 nano at $0.20 input / $1.25 output is competitive, though direct comparison depends on output quality for your specific use case.