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Compare these two on your own workload

Published rates rank differently once prompt caching, batch discounts and your own input-to-output ratio are applied. Run both against your numbers.

Gemini 3.8 Flash vs Gemini 2.5 Flash

Whether the newer Flash is worth 2.5x the input price, before that price doubles in January 2027.

Prices verified 12 Oct 2026
Input / 1M$0.750
Output / 1M$3.75
Cached input / 1M$0.075
Batch50% off
Context1.0M tokens
Blended (3:1)$1.50
Input / 1M$0.300
Output / 1M$2.50
Cached input / 1M$0.030
Batch50% off
Context1.0M tokens
Blended (3:1)$0.850

Monthly cost by workload shape

The same volume costs very different amounts depending on the shape of the traffic. No caching or batch applied.

WorkloadGemini 3.8 FlashGemini 2.5 FlashDifference
Customer support chatbot
50K/day · 800 in / 300 out
$2,625.45$1,506.78Gemini 2.5 Flashsaves $1,118.67Model it →
RAG / search answers
20K/day · 3000 in / 400 out
$2,283.00$1,156.72Gemini 2.5 Flashsaves $1,126.28Model it →
Agent / tool-use loop
8.0K/day · 2500 in / 600 out
$1,004.52$547.92Gemini 2.5 Flashsaves $456.60Model it →
Batch summarization
100K/day · 5000 in / 500 out
$17.1K$8,371.00Gemini 2.5 Flashsaves $8,751.50Model it →
Code assistant
15K/day · 2000 in / 800 out
$2,054.70$1,187.16Gemini 2.5 Flashsaves $867.54Model it →

Frequently asked questions

Which is cheaper, Gemini 3.8 Flash or Gemini 2.5 Flash?

At a typical 3:1 input-to-output ratio, Gemini 2.5 Flash is cheaper: $0.850 blended per 1M tokens against $1.50. That holds at every input:output ratio, one model is cheaper on both rates.

What is the price difference between Gemini 3.8 Flash and Gemini 2.5 Flash?

Gemini 3.8 Flash: $0.750 input, $3.75 output per 1M tokens. Gemini 2.5 Flash: $0.300 input, $2.50 output. That is 2.5x on input and 1.5x on output.

Does prompt caching change the answer?

Gemini 3.8 Flash caches input at $0.075/1M and Gemini 2.5 Flash caches at $0.030/1M. For input-heavy workloads with repeated context, caching can matter more than the base rate difference, model both in the calculator rather than comparing rate cards.

This page compares published prices only. It makes no claim about which model performs better on any task; that depends entirely on your evaluations.

Rate cards decide nothing on their own.

Most teams run several models at once. Finitizer Tokenomics shows what each one actually costs you, read from your own bills and exports, which workloads could test a smaller model, what they would cost on an open-weight model, and, for models you serve yourself, the cost per token beside the API price. A routing decision starts from your spend rather than a price page.

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