Made with these models
The 6 models this integration runs.
gemini-2.5-flash on gemini
gemini-2.5-flashtext-to-text
gemini-2.5-flash-lite on gemini
gemini-2.5-flash-litetext-to-text
gemini-2.5-pro on gemini
gemini-2.5-protext-to-text
gemini-3.5-flash on gemini
gemini-3.5-flashtext-to-text
gemini-3.5-flash-lite on gemini
gemini-3.5-flash-litetext-to-text
gemini-3.6-flash on gemini
gemini-3.6-flashtext-to-text
gemini-2.5-flash on gemini
gemini-2.5-flashtext-to-text
gemini-2.5-flash-lite on gemini
gemini-2.5-flash-litetext-to-text
gemini-2.5-pro on gemini
gemini-2.5-protext-to-text
gemini-3.5-flash on gemini
gemini-3.5-flashtext-to-text
gemini-3.5-flash-lite on gemini
gemini-3.5-flash-litetext-to-text
gemini-3.6-flash on gemini
gemini-3.6-flashtext-to-text
Huge context windows and the cheapest high-volume classification on the marketplace.
- From $0.10 per million input tokens (Flash-Lite)
- Very large context windows — fewer chunking workarounds
- Flash, Flash-Lite and 2.5 Pro selectable per node
- Charged on Google-reported token usage
- Bring your own key, or run on the platform key
Gemini's advantage in a pipeline is context and unit cost. Flash-Lite at $0.10 per million input tokens is the cheapest way to classify, tag or triage a large batch of anything, and the context windows are large enough to put an entire document in a single prompt rather than chunking it.
Use it where volume is the problem: labelling every asset a pipeline produces, filtering a feed before an expensive model sees it, or summarising long source material in one pass.
Sushibelt talks to Gemini through its OpenAI-compatible endpoint, so it behaves like every other LLM Worker on the canvas. Charged on reported tokens; note that Gemini prices audio input differently from text, and this node sends text.
llmcheaphigh-volumelong-contextgeminigoogleclassification