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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.

Pricing overview (mid-2026 illustrative)
ModelInput priceOutput priceBest for
Gemini 3.5 FlashFlash-tier pricingFlash-tier pricingFrontier intelligence at Flash cost
Gemini 3.1 Pro PreviewPro-tier pricingPro-tier pricingHighest capability (preview)
Gemini 2.5 Flash-Lite~$0.10/1M tokensHigherCheapest paid option
Gemini 2.5 FlashStandard Flash pricingStandardGood balance, stable
Batch API (all models)~50% discount~50% discountBulk 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.

What is the approximate cost saving when using the Gemini Batch API for bulk processing?
Which Gemini model is the most cost-efficient option for high-volume, latency-sensitive classification tasks?

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