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1Fix the driver behind crashes, sound loss and screen glitches2Repair Windows errors before they cause bigger problems3Scan for outdated or missing drivers - takes under a minuteJetBrains announced in June 2024 that it would use Google Cloud Vertex AI to bring Gemini models into JetBrains AI Assistant. The initial plan named Gemini 1.5 Pro and Gemini 1.5 Flash; a November 2024 update said both were available and selectable in AI Chat with AI Assistant 2024.3. Current JetBrains documentation describes a broader set of provider options, so those launch models and dates should be read as part of the rollout history, not as a statement of what is available today.
What JetBrains announced in June 2024
JetBrains said it planned to integrate Google’s Gemini 1.5 Pro and Gemini 1.5 Flash into AI Assistant through Google Cloud Vertex AI. The June announcement described a staged approach: AI Enterprise teams could choose which large language model to use, while AI Assistant would automatically choose a model for each task for other users. JetBrains said the changes would roll out in the coming weeks. Read JetBrains’ June 2024 announcement.
The announcement framed AI Assistant as a coding companion for tasks including code generation, suggesting fixes, refactoring, answering questions about code, and creating tests, documentation, and commit messages. These are vendor-described capabilities, not independent performance findings. JetBrains CEO Kirill Skrygan said, “With the rapid advancement of generative AI, it was crucial for JetBrains to find partners who could not only keep pace with the evolution of the technology but also innovate and create the most capable models.” Warren Barkley, Senior Director of Product Management for Vertex AI at Google Cloud, said, “We are excited to expand our collaboration with JetBrains, now with the family of Gemini models being supported in JetBrains AI.”
When Gemini became available in AI Assistant
JetBrains’ November 2024 follow-up said Gemini 1.5 Pro and Gemini 1.5 Flash had joined the AI Assistant lineup. It also said a model picker in AI Chat was available starting with AI Assistant 2024.3, letting users select a model there. The update separately described connecting local models through Ollama. See the November 2024 rollout update.
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That release-era detail answers whether users could choose Gemini, but it should not be mistaken for a guarantee about the current interface, available model versions, or plan controls. JetBrains’ current help documentation is the better reference for supported provider routes.
How to use Gemini in JetBrains AI Assistant now
JetBrains’ AI Assistant 2026.2 Help documents two ways to connect Gemini: through the Gemini API with an API key, or through Google Vertex AI. It also lists Anthropic, OpenAI, OpenAI-compatible endpoints, and locally hosted models as other model options. The precise setup steps and availability can depend on the IDE version and configuration; use the current JetBrains instructions for third-party and local models rather than relying on screenshots or controls from a 2024 release.
| Route | What the current documentation says | What to consider |
|---|---|---|
| JetBrains AI service | AI Assistant can use JetBrains-managed model selection. JetBrains’ current help also documents custom provider routes; exact controls can vary by version and configuration. JetBrains AI Assistant Help | Check the current product interface and plan terms to see which model controls are available to your account. |
| Gemini API | Connect Gemini using an API key. JetBrains AI Assistant Help | This is a direct provider route, distinct from the Vertex AI route in the original partnership announcement. |
| Google Vertex AI | JetBrains documents connecting through Google Vertex AI. JetBrains AI Assistant Help | Follow current JetBrains and Google Cloud setup requirements for your account and project. |
| Other third-party or local models | The help lists Anthropic, OpenAI, OpenAI-compatible endpoints, and locally hosted models. Ollama was specifically described in JetBrains’ November 2024 update. JetBrains AI Assistant Help; November 2024 update | Provider setup, model choice, and any associated costs depend on the selected service and its terms. |
How the Gemini model story changed
Gemini 1.5 Pro and Flash were the versions named in the June 2024 partnership announcement and November rollout update. In April 2025, JetBrains separately announced Gemini 2.5 Pro support and called it experimental at that time. That historical label does not establish the model’s status today; current availability should be confirmed in the current JetBrains documentation or AI Assistant interface. Read JetBrains’ April 2025 Gemini 2.5 Pro announcement.
Likewise, JetBrains’ April 2025 update discussed a redesigned subscription arrangement and additional cloud models. Those terms are time-sensitive; this announcement history alone does not establish today’s pricing, quotas, privacy terms, or plan entitlements. Check current JetBrains terms and the chosen provider’s terms before enabling a route. See the April 2025 AI Assistant update.
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What the partnership does—and does not—establish
The announcement documents JetBrains’ plan to route Gemini 1.5 models through Vertex AI, and the later rollout update records availability in AI Assistant 2024.3 with model selection in AI Chat. Current documentation broadens the picture by listing both Gemini API and Vertex AI, as well as additional hosted and local providers. It does not, by itself, establish that one route is faster, more accurate, cheaper, or more private than another.
JetBrains’ June 2024 post also reported that developers saved “up to eight hours per week” using AI Assistant, but did not provide a study, sample, or methodology for that figure. Treat it as a vendor-reported claim, not a verified expected saving for an individual user. The post also quoted a Google Cloud executive referring to a “1M context window”; that statement is not a guarantee for every Gemini model or every current AI Assistant configuration.
For a personal-finance reader, the practical distinction is that using a custom API key or Vertex AI may involve provider-specific account and billing arrangements, whereas using JetBrains’ own service follows JetBrains’ current plan and usage terms. The available sources do not establish current prices or quotas for either route, so verify those terms directly before choosing a setup.
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