Gemini 3 Flash - Kyma API

Overview

Gemini 3 Flash is the newest Gemini from Google, built for long-context work and reasoning. It sits in Kyma’s frontier-open quality tier and accepts text, images, audio, and video in a single request, returning text — with extended reasoning available when the problem calls for it. On Kyma, Python apps and the OpenClaw coding agent lead its traffic. Every call gets automatic failover if a serving path degrades, and prompt caching bills repeated prompt prefixes at this model’s cached input rate, which matters at this context size — resending a large cached prefix costs a fraction of the first pass. The 1,048,576-token context window comes with function calling and structured outputs, so the long context is usable inside agent pipelines, not just for one-off summarization.

Specs

Field	Value
Model ID	`gemini-3-flash`
Best for	Long context, reasoning
Context window	1.048576M
Max output tokens	8K
Input modalities	Text, Image, Audio, Video
Output modalities	Text
Tool calling	Yes
Structured outputs	Yes
Prompt caching	Yes
Speed	Fast
Cost band	Premium
Release stage	Preview

Pricing

	Per 1M tokens
Input	$0.68
Output	$4.05

Use this when

Whole-corpus analysis — The 1M-token window fits entire codebases, document sets, or transcript archives in one request instead of a retrieval pipeline.
Video and audio understanding — Send recordings, screen captures, or audio directly — no separate transcription step — and ask questions about what’s in them.
Vision tasks — Screenshots, diagrams, charts, and scanned documents go in as images alongside your text prompt.
Reasoning over long inputs — Extended reasoning plus the huge context handles analysis that requires holding a lot of material in view at once.
Long-context agents — Function calling and structured outputs keep multi-step agents reliable even as the working context grows toward the 1M-token window.

Not ideal for

Single responses that need to run very long — output is capped at 8K tokens per request, so generating a book-length draft means chunking; and it sits in the premium cost tier, so high-volume simple tasks are cheaper on a lighter model.

Pick something else when

You want the safer long-context default: use gemini-2.5-flash.
You want the best overall default: use qwen-3.6-plus.
You need the strongest coding agent behavior: use kimi-k2.6.

Example

from openai import OpenAI

client = OpenAI(base_url="https://kymaapi.com/v1", api_key="ky-...")

response = client.chat.completions.create(
    model="gemini-3-flash",
    messages=[{"role": "user", "content": "..."}],
    tools=[...],  # function calling supported
)

Agent query example

Ask the API which models fit, instead of hardcoding an id:

curl "https://kymaapi.com/v1/models?recommended_for=chat&tools=true&quality_tier=frontier-open"

FAQ

Can Gemini 3 Flash understand video and audio, or just images? All three. It accepts text, image, audio, and video inputs in the same request, which makes it the model to pick on Kyma when your input isn’t just text — meeting recordings, screen captures, and multimedia documents can go straight in without a separate transcription or frame-extraction step. How does prompt caching change the cost of working with large prompts? The first pass over a large input bills at the full input rate, but repeated prompt prefixes — the common pattern for agents and multi-turn analysis over the same corpus — bill at this model’s cached input rate. Responses include the exact cost in usage.cost, so you can verify what each request actually cost. Why use Gemini 3 Flash through Kyma? One API key and one OpenAI-compatible endpoint covers this and every other model on the platform. You get automatic failover when a serving path degrades, plus prompt caching and $0.50 of free credit to start, no card required.

Alias	Resolves to
`long-context`	`gemini-3-flash`

​Overview

​Specs

​Pricing

​Use this when

​Not ideal for

​Pick something else when

​Example

​Agent query example

​FAQ

​Related aliases