Google AI Studio records 112,620,020 monthly visits with +2% month-over-month growth and Freemium pricing. Intervu.dev records 551 monthly visits with -82.7% growth and Freemium pricing.
Google's rapid prototyping IDE and developer API workbench for building multimodal applications with Gemini models.
Practice FAANG-style mock coding interviews with AI feedback
| Dimension / Metric | | |
|---|---|---|
| Official Domain | aistudio.google.com | intervu.dev |
| Pricing Model | Freemium | Freemium |
| Monthly Visits | 112.62M (112,620,020) | 551 (551) |
| MoM Traffic Delta | +2.19M (+2%) | -2.64K (-82.7%) |
| Primary Market & Share | 🇺🇸 United States (11.3%) | 🇺🇸 United States (100%) |
| Direct Visits / mo | 60.81M | 218 |
| User Rating | 4.8 | 4.5 |
| Supported Platforms | Website | Website |
Google's rapid prototyping IDE and developer API workbench for building multimodal applications with Gemini models.
Allows developers to drop hours of video, multi-track audio files, high-resolution images, entire codebases, and multi-hundred-page PDFs directly into the prompt window with up to 1,000,000 tokens of shared context.
Provides direct access to Google's frontier reasoning and agentic models with granular controls over thinking tokens, temperature, function declarations, and strict JSON schema output validation.
Includes a dedicated `/live` studio interface for testing sub-second, bidirectional voice and screen/camera interactions powered by `gemini-3.8-live`, `gemini-3.8-live-extended-thinking`, and `gemini-3.5-live-translate-preview`.
Connects model responses to live Google Search results and Google Maps geospatial data with a single toggle, including 5,000 free grounded requests per month on Paid tiers before $14/1,000-query metering.
Practice FAANG-style mock coding interviews with AI feedback
The AI asks clarifying and follow-up questions the way a real interviewer would, testing how you think rather than only what you type.
Write, run, and debug code in the session while narrating your approach, mirroring the conditions of an actual technical interview.
Every session follows Clarify → Design → Code → Test so you internalize the rhythm top companies expect.
Feedback focuses on communication clarity, decision trade-offs, and code quality, not just pass/fail correctness.
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SpecialistRun, fine-tune, and deploy machine learning models with one line of code
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SpecialistOne API for fast, cost-predictable inference on LLMs and multimodal models
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