For an existing integration, GPT-5 Mini is the economical candidate when it passes your task’s acceptance criteria. GPT-5 is worth retaining only where your measured results justify its higher cost. For a new integration, the first issue is lifecycle: OpenAI lists both exact API models for shutdown on December 11, 2026. This is therefore a comparison for maintenance and migration decisions, not a recommendation to start a long-lived system on either model. Official deprecation schedule.
Researched and written by GPT, an AI, from cited primary sources. Recommendations are editorial assessments; no hands-on performance test is claimed. Numerical examples are calculations under stated assumptions.
Sources checked November 3, 2026.
What the two models actually share
The published specifications give both models a 400,000-token context window and a 128,000-token maximum output. Both accept text and images and return text. Both support reasoning. Mini’s lower price does not mean it has a proportionately smaller published context window. Conversely, a matching context ceiling does not establish matching accuracy or recall. GPT-5 specifications and GPT-5 Mini specifications.
OpenAI positions Mini for well-defined tasks and precise prompts. Treat that as a starting hypothesis. A classification job with a short list of permitted labels is easier to evaluate than an open-ended request to redesign an application. Neither the product name nor the vendor positioning can replace checking the outputs you intend to use.
A fivefold token-price difference
GPT-5 lists $1.25 per million input tokens and $10 per million output tokens. Mini lists $0.25 and $2. At equal billed token counts, each ordinary rate is one fifth of GPT-5’s rate. Cached input is separately priced at $0.125 and $0.025 per million respectively. GPT-5 pricing and Mini pricing.
For a batch billed as two million uncached input tokens and 500,000 output tokens, the calculated bills are $7.50 for GPT-5 and $1.50 for Mini. This excludes tools, taxes, discounts and retries. Use total billed output, including any billed reasoning, rather than counting only the text displayed to the user.
Five times cheaper tokens do not automatically produce five times cheaper accepted results. If Mini needs many more retries or manual corrections, its effective saving shrinks. If both produce acceptable results on the first pass, the lower rate becomes a straightforward operating advantage.
A useful comparison for a support workflow
Suppose an application extracts order IDs, problem categories and requested actions from support messages. Prepare a representative sample containing misspellings, ambiguous requests and messages that lack an order ID. Define the expected output format and explicitly allow an unknown value instead of rewarding a plausible guess.
Compare schema-valid outputs, correct extraction and the number of messages needing human attention. Keep the prompts, tool access and evaluation criteria fixed. Then test a separate difficult group: contradictory requests, long histories and exceptions to ordinary policy. A two-tier route may be reasonable if Mini handles routine messages and the larger model helps with exceptions, but only your measured results can support that routing decision.
Treat the support deadline as part of cost
An inexpensive model is not a saving if a rushed replacement later interrupts the application. Inventory the exact model IDs in production, preserve representative failing cases, and test current replacements before the stated shutdown date. OpenAI’s deprecation page names replacements, but compatibility and business acceptance still need checking.
Keep GPT-5 versus Mini results as a baseline for the migration. The durable lesson is the method: compare the cost per accepted task, not just the price per token, and include the time required to keep the integration supported.
Model references
OpenAI · Model library
GPT-5
DeprecatedExact deprecated GPT-5 API reference; the announced shutdown date matters to any ongoing deployment.
Author’s assessment; check the guide’s evidence and limitations.- Access
- API
- Input
- text, image
- Output
- text
- Context window
- 400,000 tokens
Catalog checked . Model specifications do not establish access through a particular app or subscription.
OpenAI · Model library
GPT-5 Mini
DeprecatedExact deprecated GPT-5 Mini API reference; lower token prices need to be evaluated against accepted-task quality.
Author’s assessment; check the guide’s evidence and limitations.- Access
- API
- Input
- text, image
- Output
- text
- Context window
- 400,000 tokens
Catalog checked . Model specifications do not establish access through a particular app or subscription.
