Gemini Omni Flash Preview API Pricing

Google · released Jun 30, 2026 · 131K context · API model ID gemini-omni-flash-preview

Gemini Omni Flash Preview by Google API pricing: $1.50 per 1M input tokens and $17.50 per 1M output tokens (provider list price via models.dev, Oct 10, 2026).

Prices

Gemini Omni Flash Preview prices, USD per 1M tokens
PriceUSD per 1M tokens
Input$1.50
Output$17.50
Cache readNot published
Cache writeNot published

Google's list price for its own API, as compiled by models.dev and checked Oct 10, 2026, 09:00 UTC. Prices on cloud platforms and resellers can differ. Provider documentation

Estimated monthly cost

$3,075

per month

per day
$102.50
per request
$0.0103

Cost = input tokens × input price + output tokens × output price, 30 days a month. Cached input uses the cache read price. Cache write fees are not included.

Compare this workload across models

Monthly cost by workload

WorkloadPer month
Chatbot1,000 in / 500 out tokens, 10,000 requests a day$3,075/mo
RAG8,000 in / 500 out tokens, 5,000 requests a day$3,113/mo
Coding agent50,000 in / 2,000 out tokens, 1,000 requests a day, 80% cached input$3,300/mo

Context and capabilities

Context
131,072 tokens
Max output
65,536 tokens
Input
text, image, video
Output
video
Knowledge cutoff
Not published
Open weights
No
Tool calling
No
Reasoning
Yes
Structured outputs
No

Capabilities and limits as listed by models.dev.

Similarly priced models

Price history

No price changes since we started tracking on Oct 8, 2026.

Questions

How much does Gemini Omni Flash Preview cost per month?
For a chatbot handling 10,000 requests a day with 1,000 input and 500 output tokens each, Gemini Omni Flash Preview costs about $3,075 per month at Google's list prices ($1.50 per 1M input tokens, $17.50 per 1M output tokens).
Does Gemini Omni Flash Preview support prompt caching?
No cache read price is published for Gemini Omni Flash Preview.
How long is Gemini Omni Flash Preview's context window?
Gemini Omni Flash Preview accepts up to 131,072 tokens (131K) of context and returns up to 65,536 tokens per response.