GPT-5.2-Codex

Use a scoped task with version control and acceptance tests. The current description notes adjustable reasoning effort and support for tool-using engineering workflows.

Use representative tasks and compare quality, latency, token use, and relevant tool behavior with your current model. Start with reviewable changes in a controlled repository, then assess instruction adherence, code quality, and test results before expanding usage.

For gpt-5.2-codex, set the max_tokens or max_completion_tokens parameter to control spending per call. Start with a budget aligned to your typical response length and increase only when longer outputs are genuinely needed. Monitor token usage in the API response headers to tune your budget over time.

Set task boundaries, review requirements, failure handling, and monitoring that match the consequences of the workload. Do not rely on an unevaluated model response for irreversible actions.

Start with reviewable changes in a controlled repository, then assess instruction adherence, code quality, and test results before expanding usage.

gpt-5.2-codex supports prompt caching, which can significantly reduce costs for repeated prompts with shared prefixes. The cache read price is substantially lower than the standard input price. Check the current pricing page for the exact cache hit discount ratio for gpt-5.2-codex.

GPT-5.2-Codex is billed per use and the record publishes no free-tier allowance. The current published rates are input $1.7500 per 1M tokens and output $14.0000 per 1M tokens. Trial credit or promotional quota is tied to your account rather than to the model, so check the console before planning around a free tier.