Gemini 3.5 Flash pricing for rag pipeline

Quick start

Call Gemini 3.5 Flash with the Google Generative AI SDK:

import google.generativeai as genai

model = genai.GenerativeModel("gemini-3.5-flash")
response = model.generate_content("Your prompt here")
# Cost: ~$0.0225 per call at standard rates
# Input:  $1.50/MTok
# Output: $9.00/MTok

How Gemini 3.5 Flash compares on cost

Per-call cost for all models scoring 50+ on rag pipeline benchmarks. Hover for details.

Cheapest viable option: GPT 5.6 Luna at $0.003000/call (87% less, 85/100 quality).

What drives rag pipeline cost

Retrieval-augmented calls are dominated by the retrieved passages, not the question. Retrieving eight chunks instead of three roughly triples input cost for an answer that is often no better, so retrieval tuning is cost tuning. The system prompt and instructions are identical on every call, which makes cache reads the first thing to enable.

For Gemini 3.5 Flash specifically, that means output tokens cost 6.0x more than input, at $9.00 vs $1.50 per MTok. At this use case’s 6,000/1,500 token split, output accounts for 60% of the $0.0225 per-call cost.

Gemini 3.5 Flash quality benchmarks for rag pipeline

Performance across all task types

Gemini 3.5 Flash scores by task type. RAG Pipeline highlighted.

Confidence scores are a third-party benchmark snapshot from week 29 of 2026. This snapshot is 8 weeks old, so treat the scores as directional and validate against your own evals.

About Gemini 3.5 Flash

Other models from Gemini

You can compare Gemini 3.5 Flash head-to-head against any other model on our model comparison pages, or track how pricing has changed over time on the pricing history tracker.

Frequently asked questions