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 supplied official API-platform evidence 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 supplied evidence 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: stuffing 1.05M tokens of context into GPT-5.4 adds up quickly at $2.50 per million. 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
The supplied official pricing evidence 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 supplied evidence 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 | $6.99/month (Starter) | 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.