AI / Google Antigravity Gemini Fundamentals Interview Questions
What is the Gemini API pricing model and how do you estimate costs?
The Gemini API uses a pay-per-token model. All Gemini 3 models currently in preview have billing enabled; free tiers exist for Gemini 2.5 models. Pricing differs between input tokens, output tokens, and cached tokens.
| Model | Input price | Output price | Best for |
|---|---|---|---|
| Gemini 3.5 Flash | Flash-tier pricing | Flash-tier pricing | Frontier intelligence at Flash cost |
| Gemini 3.1 Pro Preview | Pro-tier pricing | Pro-tier pricing | Highest capability (preview) |
| Gemini 2.5 Flash-Lite | ~$0.10/1M tokens | Higher | Cheapest paid option |
| Gemini 2.5 Flash | Standard Flash pricing | Standard | Good balance, stable |
| Batch API (all models) | ~50% discount | ~50% discount | Bulk non-real-time |
# Cost estimation: # Scenario: Process 10,000 support tickets # Average: 500 input tokens + 200 output tokens each docs = 10_000 per_doc_input = 500 per_doc_output = 200 # Gemini 2.5 Flash (illustrative: $0.30/1M input, $1.20/1M output) input_cost = (docs * per_doc_input / 1_000_000) * 0.30 # $1.50 output_cost = (docs * per_doc_output / 1_000_000) * 1.20 # $2.40 total_sync = input_cost + output_cost # $3.90 # With Batch API (~50% discount): total_batch = total_sync * 0.5 # $1.95 print(f"Synchronous: ${total_sync:.2f}") print(f"Batch API: ${total_batch:.2f}") # Always check current prices at: # ai.google.dev/gemini-api/docs/pricing # Prices change frequently with new model releases
Key cost levers: right-sizing the model (Flash-Lite for classification, Pro for complex reasoning); context caching for repeated prompts; Batch API for bulk; and choosing stable models to avoid unexpected billing changes from preview deprecations.
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