OpenAI vs Anthropic Claude vs Google Gemini — Java Backend Integration Comparison
Fast recall
Quick revision
Core answer
spring-ai-openai, spring-ai-anthropic, spring-ai-vertex-ai-gemini. The ChatClient interface is identical across providers — swap the starter and properties to switch. Key differences: OpenAI uses OpenAiChatModel, Anthropic uses AnthropicChatModel, Google uses VertexAiGeminiChatModel. Auth differs — OpenAI and Anthropic use API keys, Gemini on Vertex AI uses service account credentials. Token context windows and pricing vary significantly.Whether the candidate understands that Spring AI abstracts the vendor differences, knows the auth model for each, and can articulate when to pick one over another
Thinking you need separate client code for each provider — Spring AI's ChatClient abstraction means the service layer doesn't change when you switch. Forgetting that Vertex AI uses GCP IAM instead of a simple API key.
Mention context window differences (Gemini 1.5 Pro has 1M tokens), Claude's system prompt handling, function calling support differences, and how to run model A/B tests by routing to different providers
Interview-ready guide
Interview answer
All three are supported by Spring AI starters: spring-ai-openai, spring-ai-anthropic, spring-ai-vertex-ai-gemini. The ChatClient interface is identical across providers — swap the starter and properties to switch. Key differences: OpenAI uses OpenAiChatModel, Anthropic uses AnthropicChatModel, Google uses VertexAiGeminiChatModel. Auth differs — OpenAI and Anthropic use API keys, Gemini on Vertex AI uses service account credentials. Token context windows and pricing vary significantly.
OpenAI vs Anthropic Claude vs Google Gemini — Java Backend Integration Comparison
Direct Answer
All three are supported by Spring AI starters: spring-ai-openai, spring-ai-anthropic, spring-ai-vertex-ai-gemini. The ChatClient interface is identical across providers — swap the starter and properties to switch. Key differences: OpenAI uses OpenAiChatModel, Anthropic uses AnthropicChatModel, Google uses VertexAiGeminiChatModel. Auth differs — OpenAI and Anthropic use API keys, Gemini on Vertex AI uses service account credentials. Token context windows and pricing vary significantly.
Deep Dive & Architecture
All three are supported by Spring AI starters: spring-ai-openai, spring-ai-anthropic, spring-ai-vertex-ai-gemini.
The ChatClient interface is identical across providers — swap the starter and properties to switch.
Spring AI's ChatClient is the same regardless of provider. You swap the starter dependency and the properties file — the service code stays identical. The differences that matter are auth model, context window size, and pricing.
Manually wiring HTTP clients when Spring AI's auto-configuration handles it; not using the ChatClient builder pattern and going straight to the lower-level model
Common Mistakes & Pitfalls
Thinking you need separate client code for each provider — Spring AI's ChatClient abstraction means the service layer doesn't change when you switch. Forgetting that Vertex AI uses GCP IAM instead of a simple API key.
Check your understanding
Answer these without looking back at the article.
- How do you integrate the OpenAI API into a Spring Boot application using Spring AI?
- How do you handle LLM API rate limits and implement retry logic in a Spring Boot service?
- What is function calling in LLM APIs and how do you implement it with Spring AI?
Looking for a structured roadmap?
Every module on this page is also part of the full Java backend interview track.