Google AI Studio: All Models Available, Modality Coverage, Developer Access and Deployment Structure
- Graziano Stefanelli
- Dec 4
- 5 min read
Google AI Studio provides a unified interface for testing, comparing and integrating Google’s full ecosystem of generative-AI models, including the complete Gemini 2.5 family, preview variants, multimodal systems, speech and audio models, image and video generators, and lightweight open-model alternatives for research and on-device use.
The platform exposes all models through a consistent developer experience, supports programmatic discovery through the Gemini API, and allows real-time experimentation with text, images, audio and video inputs across stable and preview model classes.
Google AI Studio therefore functions as the central hub through which developers, researchers, analysts and enterprise users can explore model capabilities, check token limits, test multimodal prompts and connect models to production environments using Google Cloud or direct API access.
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Google AI Studio provides access to the complete Gemini 2.5 family, including Pro, Flash, Flash-Lite and preview models.
The Gemini 2.5 line represents Google’s largest, most capable model suite available in AI Studio, organized into multiple tiers that balance reasoning depth, latency, context size and cost efficiency.
Gemini 2.5 Pro serves as the flagship reasoning model with advanced multimodal capabilities, large context depth, high-precision output and support for deeply structured tasks.
Gemini 2.5 Flash offers balanced performance for general-purpose workloads, maintaining strong multimodal processing and large context capacity with lower operational cost.
Gemini 2.5 Flash-Lite delivers cost-efficient, high-throughput inference suitable for real-time applications, automations, mobile integrations and large-scale backend processing.
AI Studio also exposes preview models such as Flash Live, TTS variants and native audio-dialogue models that support real-time streaming and experimental modalities under controlled access.
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Gemini 2.5 Model Availability
Model Tier | Identifier | Capability Profile |
2.5 Pro | gemini-2.5-pro | Deep reasoning + multimodal |
2.5 Flash | gemini-2.5-flash | Balanced performance |
2.5 Flash-Lite | gemini-2.5-flash-lite | High-throughput + low cost |
2.5 Flash Live | Preview ID | Streaming interactions |
2.5 TTS Variants | Preview | Speech synthesis |
2.5 Audio Dialog | Preview | Native audio workflows |
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AI Studio includes the full Gemini 2.0 series and Flash/Flash-Lite models for backward compatibility and cost-optimized deployments.
Developers requiring stable legacy behavior or backward-compatible pipelines can access the complete Gemini 2.0 model set, including Flash and Flash-Lite variants still supported across Google Cloud environments.
These models provide cost-efficient paths for migration or long-running applications that depend on consistent output patterns, predictable latency profiles and stable multimodal behavior across earlier generations.
Gemini 2.0 Flash supports multimodal reasoning across text, code and images, while 2.0 Flash-Lite offers even lower inference cost for lightweight workloads and high-frequency operations.
AI Studio maintains these models to ensure compatibility with existing applications and to support gradual upgrades toward the 2.5 generation when desired.
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Gemini 2.0 and Legacy Models
Model Name | Identifier | Primary Use Case |
2.0 Flash | gemini-2.0-flash | Multimodal baseline |
2.0 Flash-Lite | gemini-2.0-flash-lite | Low-latency workloads |
Other 2.0 Variants | Legacy IDs | Existing pipelines |
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Google AI Studio exposes multimodal generators for images, video and audio that extend the Gemini language models with creative and production workflows.
Alongside language models, AI Studio includes access to Google’s image-generation models such as Imagen, supporting high-fidelity image synthesis, multi-step visual transformations and structured visual control prompts.
The platform also provides access to Veo and other video-generation systems in supported regions, enabling developers to prototype short clips, animated sequences or video-based creative outputs within Studio’s experiment interface.
Audio and speech-related models, including TTS and audio-dialogue variants within the Gemini family, enable developers to build multimodal agents, real-time dialogues, voice-driven applications and speech enhancement workflows integrated with Google Cloud’s media stack.
This multimodal coverage allows developers to build unified applications that combine reasoning, vision, audio and generation under a single API ecosystem.
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Creative & Multimodal Model Availability
Model Type | Examples Available in AI Studio | Use Case |
Image Models | Imagen variants | Image synthesis |
Video Models | Veo (where available) | Video generation |
Audio/TTS Models | TTS Preview | Speech output |
Audio Dialog Models | Native audio dialog | Voice assistants |
Multimodal Fusion | Gemini 2.5 family | Vision + text reasoning |
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Open-model support through Gemma provides lighter-weight, research-friendly models for experimentation and local or hybrid deployment.
Google includes the Gemma model family in AI Studio, designed for research environments, edge-device experimentation, fine-tuning tasks and hybrid-cloud deployments.
Gemma models provide reduced parameter footprints suitable for classroom use, prototype systems, constrained environments or developers requiring substantial flexibility beyond large-model inference.
Gemma models can be used in AI Studio for experimentation and then exported or integrated into local systems or hybrid deployments using frameworks compatible with open-model architectures.
This dual support for proprietary Gemini models and open Gemma variants widens the platform’s accessibility across domains and technical requirements.
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Gemma Model Access
Gemma Variant | Profile | Developer Benefit |
Gemma 2 / 2B / 7B | Lightweight | Research and prototyping |
Gemma Code Variants | Code-optimized | Development workflows |
Fine-Tuned Gemma | Task-specific | Local deployment |
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The Gemini API provides a programmatic model listing endpoint, enabling real-time discovery and filtering of all models available through AI Studio.
Developers can retrieve Google’s full model catalog using the models.list endpoint, which returns metadata including model IDs, modality support, context windows, generation limits, preview or stable status and region availability.
This dynamic listing mechanism ensures production systems can check model availability, migrate workloads to newer variants or ensure compatibility across distributed deployments.
AI Studio mirrors this programmatic listing inside its interface, allowing developers to switch models directly in the experiment workspace and inspect documentation linked to each model type.
The unified listing system supports consistent model identification across AI Studio, Vertex AI, Cloud Console and direct API integrations.
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Model Listing Metadata
Metadata Field | Description | Developer Use |
Model ID | Unique identifier | API calls |
Modality Support | Text, vision, audio | Capability check |
Context Window | Max tokens accepted | Prompt design |
Output Limits | Generation ceilings | Response planning |
Model Status | Stable / Preview | Deployment decisions |
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Model selection in AI Studio depends on reasoning depth, latency tolerance, multimodal needs and cost considerations.
Developers can choose between model tiers by evaluating reasoning complexity, expected input size, response-time sensitivity, operational budget and pipeline design.
Pro models suit analytical, research-heavy, deep reasoning workflows that depend on long-context depth and complex multimodal chains.
Flash models balance accuracy with cost and latency, forming an ideal mid-tier for most applications that require both speed and capability.
Flash-Lite models provide the lowest inference cost and highest throughput, supporting microservice architectures, mobile applications, event-driven systems and agentic workflows.
Open models like Gemma serve experimental, edge-device and customizable deployments where developers require full control over inference environments.
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Model Selection Framework
Use Case Category | Best Model Tier | Rationale |
Deep Reasoning | Gemini 2.5 Pro | Highest capabilities |
Balanced Workloads | Gemini 2.5 Flash | Strong multimodality |
High-Throughput | Gemini 2.5 Flash-Lite | Cost-focused |
Real-Time Dialog | Flash Live / Audio Dialog | Streaming behavior |
On-Device / Research | Gemma | Open deployment |
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