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Google has officially announced the deprecation of its Gemini 2.0 Flash and Gemini 2.0 Flash Lite models, effective March 31, 2026
This change will impact all projects currently utilizing these models. To ensure uninterrupted service, developers and businesses must migrate to the supported Gemini 2.5 or Gemini 3 models before the deadline.
This guide provides a comprehensive overview of the deprecation and a step-by-step migration path.

As part of Google's continuous improvement of its AI ecosystem, older models are retired to make way for more efficient, powerful, and capable versions. The new Gemini 2.5 and Gemini 3 models offer significant advancements in reasoning, multimodal processing, and cost-efficiency. Deprecating older versions allows resources to be focused on maintaining and improving these state-of-the-art models.
Projects still using Gemini 2.0 Flash or Flash Lite after March 31, 2026, will experience service interruptions. It is critical to check your project dependencies and update them accordingly.
Migrating is a straightforward process, but it requires careful execution to avoid breaking changes.

Step 1 Audit Your Projects: Identify all applications and services using `gemini-2.0-flash` or `gemini-2.0-flash-lite`. Check your API keys and configuration files.
Step 2 Update Model References: Replace the model names in
your code.
Change model: "gemini-2.0-flash" to model: "gemini-2.5-flash" or
model: "gemini-3.0-pro" depending on your needs.
Step 3 Test Thoroughly: Run your unit and integration tests to ensure the new models perform as expected. Pay attention to any differences in prompt response structure or token limits.
Step 4 Monitor: After deploying the changes, monitor your application logs for any unexpected errors or latency issues.
API calls to the deprecated models will fail, returning errors. Your application features relying on these models will stop working.
Gemini 2.5 Flash is designed to be cost-competitive with the previous version, often offering better performance for the same price. Gemini 3 models may have different pricing tiers, so check the official pricing page.
You can consult the official Product Documentation or visit the Gemini AI Community for support.