for developers Mete Atamel Developer Advocate @ Google @meteatamel atamel.dev speakerdeck.com/meteatamel

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Features across models

gemini-2.0-flash A GA model on: ● Gemini Developer API, on Google AI Studio ● Gemini API, on Vertex AI Studio

gemini-2.0-flash-thinking-exp-01-21 An experimental model trained to generate the thinking process for stronger reasoning across math and science

Performance Multimodal Live API Unified SDK Native Tool Use Native Image & Audio Output (preview) Spatial Understanding

Enterprise Vertex AI Studio Google Cloud APIs cloud.google.com/vertex-ai Consumers Gemini gemini.google.com Developers Google AI Studio Google APIs aistudio.google.com ai.google.dev/gemini-api

Performance

Gemini Flash 2.0 offers 2x the speed of Gemini 1.5 Pro Stronger performance on multimodal, text, code, video, spatial understanding and reasoning

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Unified SDK

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Unified interface to Gemini 2.0 (and 1.5) ● Gemini Developer API on Google AI Studio ● Gemini API on Vertex AI The new Google Gen AI SDK

Gemini Developer API on Google AI Studio client = genai.Client( api_key=your-gemini-api-key) response = client.models.generate_content( model="gemini-2.0-flash-001", contents="Why is the sky blue?")

Gemini Developer API on Vertex AI client = genai.Client( vertexai=True, project=your-google-cloud-project, location="us-central1") response = client.models.generate_content( model="gemini-2.0-flash-001", contents="Why is the sky blue?")

Native Tool Use

Google Search Tool Ground model responses in Google Search results For more accurate, up-to-date, and relevant responses

Google Search Tool google_search_tool = Tool(google_search=GoogleSearch()) response = client.models.generate_content( model="gemini-2.0-flash-001", contents="How’s the weather like today in London?", config=GenerateContentConfig(tools=[google_search_tool]) )

Code Execution Tool Model generates and runs Python code Useful for applications that benefit from code-based reasoning (e.g. solving equations)

Code Execution Tool code_execution_tool = Tool(code_execution=ToolCodeExecution()) response = client.models.generate_content( model="gemini-2.0-flash-001", contents="What is the sum of the first 50 prime numbers?", config=GenerateContentConfig( tools=[code_execution_tool], temperature=0))

Automatic Function Calling Submit a Python function for automatic function calling (instead of submitting an OpenAPI specification of the function)

Function Calling–before

Automatic Function Calling def get_current_weather(location: str) -> str: """Example method. Returns the current weather. Args: location: The city and state, e.g. San Francisco, CA """ weather_map: dict[str, str] = { "Boston, MA": "snowing", "San Francisco, CA": "foggy", "Seattle, WA": "raining", "Austin, TX": "hot", "London, UK": "rainy and dark", } return weather_map.get(location, "unknown")

Automatic Function Calling response = client.models.generate_content( model="gemini-2.0-flash-001", contents="What is the weather like in Austin?", config=GenerateContentConfig( tools=[get_current_weather], temperature=0))

Spatial Understanding

Improved accuracy on 2D and 3D spatial understanding Spatial Understanding

Multimodal Live API

Enables low-latency, two-way interactions → Input: text, audio, and video ← Output: audio and text Multimodal Live API

● Multimodality – model can see, hear, speak ● Low-latency – for realtime interaction ● Memory – model remembers the session ● Tools – Function calling, code execution, and Google search Multimodal Live API–key capabilities

Native Image & Audio Output (preview)

Gemini 2.0 introduces native image generation and text-to-speech capabilities Enables image generation / editing and expressive storytelling Native Image & Audio Output (preview)

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Thank you! Mete Atamel Developer Advocate at Google @meteatamel atamel.dev speakerdeck.com/meteatamel