# Gemini 2.5 made thinking mode a configuration question

Google introduced Gemini 2.5 Pro Experimental in March 2025 with thinking mode on by default. The release illustrates why model behavior must be tied to a dated configuration.

Canonical: https://rangoon.ai/insights/archive-gemini-2-5-thinking-configuration/
Author: Rangoon Editorial (https://rangoon.ai/insights/editorial/)
Published: 2026-10-23
Updated: 2026-10-23
Event date: 2025-03-25
Tags: [Google](https://rangoon.ai/insights/tags/google/), [Gemini 2.5](https://rangoon.ai/insights/tags/gemini-2-5/), [thinking models](https://rangoon.ai/insights/tags/thinking-models/), [configuration management](https://rangoon.ai/insights/tags/configuration-management/)
Source note: Historical retrospective: Google published the Gemini 2.5 announcement on March 25, 2025, and its Gemini API changelog recorded the experimental model that day. This article makes no current model, API or availability claim.

Image: Gemini 2.5: compare configurations. Original Rangoon explanatory diagram; conceptual relationships, not an event photograph, vendor interface, or measured result.

## Key takeaways
- Reasoning behavior can be part of a model configuration, not an invisible quality attribute.
- A product announcement and an API changelog identify complementary product and identifier evidence.
- Comparisons need the exact model ID, surface and settings alongside their fixtures.

## Google introduced a thinking-model family [source 1](https://blog.google/innovation-and-ai/models-and-research/google-deepmind/gemini-model-thinking-updates-march-2025/) [source 2](https://ai.google.dev/gemini-api/docs/changelog)

On March 25, 2025, Google announced Gemini 2.5 and introduced Gemini 2.5 Pro Experimental as the first release in that family. The announcement characterized the family as thinking models designed for complex problems, and said it combined an enhanced base model with improved post-training. Google's Gemini API changelog separately recorded the identifier gemini-2.5-pro-exp-03-25 and stated that thinking mode was on by default for that public experimental model.
Those two primary records establish more than a marketing name. They show that an announced family and an API-facing identifier were both part of the release moment. They do not establish a current endpoint, price, product tier or behavioral result. This article treats the release as a dated reference for configuration discipline, not as a present-tense recommendation.


## Thinking behavior belongs in the run record

When a model has a stated reasoning or thinking mode, an evaluator should not compress that setting into a model-family label. The record needs the exact identifier, surface, region where relevant, request parameters, system instructions, tool definitions and time of execution. A response may change because of any of these inputs. Omitting them turns a comparison into a vague claim that a named model was better or worse.
This is especially important for workflows that parse structured output or propose actions. A different reasoning configuration can affect latency, output ordering, tool selection or the completeness of a required field. None of those variations automatically make a configuration unsuitable. They do make it necessary to test the contracts the application actually depends on. The fixture set should include normal cases, malformed inputs, requested refusal paths and tool failures, not only prompts designed to showcase an answer.


## Historical lesson: compare named configurations, not impressions

A useful migration sheet pins a baseline and candidate configuration side by side. For each run, it records model identifier, endpoint or product surface, prompt revision, tool schema revision, test-data class, start time and outcome. Reviewers can then inspect whether a difference came from the model candidate or from an unrelated change in a wrapper, tool policy or prompt. This is a small amount of metadata with a large effect on later debugging.
The decision can remain bounded. Promote a candidate for one low-consequence workflow only after its expected contracts pass, retain rollback details, and keep unknown cases unresolved. A release announcement can explain why a team opens that evaluation. It cannot substitute for a compatibility record, authorize a new data flow or prove that the experimental configuration was appropriate for another application's conditions. The March 2025 documentation is most useful when it stays attached to those limits.


## Sources
1. [Google: Gemini 2.5, our most intelligent AI model](https://blog.google/innovation-and-ai/models-and-research/google-deepmind/gemini-model-thinking-updates-march-2025/)
2. [Google AI for Developers: Gemini API release notes](https://ai.google.dev/gemini-api/docs/changelog)

## Related reading
- [MedGemma 1.5 expanded a 4B model toward volumes, slides and longitudinal imaging inputs](https://rangoon.ai/insights/archive-google-medgemma-1-5-imaging-january-2026/)
- [Google released TxGemma as a Gemma 2 family for therapeutic-property research tasks](https://rangoon.ai/insights/archive-google-txgemma-therapeutics-march-2025/)
- [Google released MedASR as a 105M medical-dictation speech-to-text foundation model](https://rangoon.ai/insights/archive-google-medasr-medical-speech-december-2025/)

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