Standard
Seat + credits- Good fit for routine campus work with occasional advanced needs.
- Uses credits when you choose advanced capabilities.
Understand license tiers, credit pools, and when different ChatGPT capabilities may consume credits.
Effective July 1, 2026, OpenAI introduced a new billing model for Higher Education workspaces. In response, UMD has updated its ChatGPT licensing model to better align with these changes.
UMD ChatGPT licenses now use a credit-based billing model for advanced capabilities instead of a fixed pricing structure. Standard ChatGPT features remain included, while advanced capabilities draw from the monthly credit allocation associated with each licensing tier (see the attached overview of included and advanced capabilities).
Users may change their licensing tier at any time by submitting the ServiceNow ChatGPT License Request form. Please note that both the user and the designated financial reviewer must approve any upgrade request before it can be processed.
We understand that not everyone's usage patterns will fit neatly within these tiers. If your initiative requires credits beyond the Ultra allocation, please contact us at dit-ais@umd.edu. We can work with you to establish an allocation that aligns with your anticipated usage and funding requirements.
ImportantCore capabilities are always included with your seat. Advanced features draw from your monthly credit allocation. The matrix below shows what's included, what's limited, and what consumes credits.
NOTE: Feature availability, included usage, and credit rates may change. See the OpenAI Enterprise/Edu rate card for the latest information.
Credit usage for ChatGPT Work and Codex is based on input tokens, cached input tokens, and output tokens.
OpenAI updates model availability and pricing as models are introduced or retired. For the latest supported models and credit rates, refer to the official OpenAI rate card. DIT works to make newly supported models available to the UMD community as soon as practical after release, subject to workspace availability and administrative review.
View current OpenAI rate cardThe examples below are illustrative and may not reflect current model availability or rates:
If a GPT 5.5 Codex run uses 20,000 input tokens, 80,000 cached input tokens, and 5,000 output tokens, the run would consume about 7.25 credits:
(20,000 ÷ 1,000,000) × 125 = 2.5 credits(80,000 ÷ 1,000,000) × 12.5 = 1.0 credit(5,000 ÷ 1,000,000) × 750 = 3.75 credits2.5 + 1.0 + 3.75 = 7.25 creditsAfter your daily free limits are used, an afternoon session with 2 extra image generations, 1 extra Deep Research task, and 4 GPT 5.5 Thinking messages would consume 100 credits:
2 × 5 = 10 credits1 × 50 = 50 credits4 × 10 = 40 credits10 + 50 + 40 = 100 creditsRollout notes and official references.
Division of Information Technology
University of Maryland