Gemini last models: temperature, top_p, and top_k are deprecated and ignored

Gemini’s latest models now treat **temperature**, **top_p**, and **top_k** as deprecated. Those sampling controls are ignored when you send them, so requests that still pass the old knobs behave as if those fields were never set.

Those three parameters used to shape token selection at decode time. **Temperature** scaled how peaky or flat the next-token distribution was. **Top_p** (nucleus sampling) kept only the smallest set of tokens whose cumulative probability crossed a cutoff. **Top_k** limited choice to the k highest-probability tokens. On the new models, that client-side tuning path is gone; generation follows the model’s default sampling path regardless of what you put in those fields.

For builders, this breaks a common control surface. Teams that used low temperature for deterministic tools, structured extraction, or eval harnesses, or raised temperature for brainstorming and creative drafts, no longer get that lever on the latest Gemini models. Caching, retries, A/B tests, and “same prompt, different creativity” setups that depended on those fields need to be redesigned around prompt wording, system instructions, or other supported generation options instead of sampling hyperparameters.

In the wider API market, most competing chat and completion APIs still expose temperature and often top_p or top_k. Gemini’s choice removes a familiar OpenAI-style control and forces product and SDK code to special-case model families: older Gemini paths may still honor sampling params; the latest ones silently ignore them. Silent ignore is the sharp edge—clients can look correct while production behavior has already shifted.

Practical next step: audit every Gemini call site for **temperature**, **top_p**, and **top_k**, and treat them as no-ops on the latest models. Replace sampling-based determinism with stricter prompts, constrained formats, or post-processing where you need stability. Watch release notes and SDK defaults for any replacement controls, and pin model IDs so a “latest” upgrade does not quietly change generation behavior under the same client code.