Gemini 3.5 Flash

LLM
Google
New

Gemini 3.5 Flash is a natively multimodal reasoning model for agentic and coding tasks. It accepts text, image, audio, and video inputs with a 1M token context and adjustable thinking levels to balance quality and latency.

Context tokens

1,000,000

Output tokens

64,000

Released

May 19, 2026

Schema

Supports adjustable thinking levels to balance quality, cost, and latency. Thinking is available and can be controlled for this model.

Schema documentation

Capabilities

Tool use
Structured output
Thinking
Multilingual
Multimodal

Supported languages

ar
bn
cs
da
de
el
en
es
fi
fr
hi
id
it
ja
ko
nl
pl
pt
ru
sv
th
tr
uk
vi
zh

Supported input media

audio
image
pdf
text
video

Supported tools

  • Google Maps

    Grounding with Google Maps connects the generative capabilities of Gemini with the rich, factual, and up-to-date data of Google Maps. This feature enables developers to easily incorporate location-aware functionality into their applications. When a user query has a context related to Maps data, the Gemini model leverages Google Maps to provide factually accurate and fresh answers that are relevant to the user's specified location or general area.

  • Google Search

    Grounding with Google Search connects the Gemini model to real-time web content and works with all available languages. This allows Gemini to provide more accurate answers and cite verifiable sources beyond its knowledge cutoff.

  • Seclai Content Tools

    Inspect source documents connected to your account. Includes tools for loading full content, reading character ranges, searching within documents, viewing stats, and listing available content sources. When a source_connection_content_version_id is provided in agent run metadata it is used as the default. Otherwise the model can discover content via list_content_sources.

  • Seclai Knowledge Base

    Search your knowledge bases using semantic similarity. Includes search_knowledge_base and list_knowledge_bases. When a knowledge_base_id is provided in the prompt or agent run metadata it is used as the default. Otherwise the model can discover available knowledge bases at runtime.

  • Seclai Memory Banks

    Manage persistent memory across agent runs. Includes tools for listing memory banks, writing entries, searching memory via semantic similarity, and loading entries in chronological order. Supports two memory types: 'conversation' (speaker-attributed turns) and 'general' (freeform text). Use key to organize entries by topic, session, or user.

  • Seclai Web Tools

    Fetch web pages and search the web from within agent prompt calls. Includes seclai_web_fetch for retrieving page content in markdown, HTML, or plain text, and seclai_web_search for finding relevant pages with content snippets.

Pricing

TypeCreditsUnits
Input19.95Credits per 1k tokens
Output119.70Credits per 1k tokens

Variants

No variants available for this model.

Try This Model

Write a prompt and experiment with Gemini 3.5 Flash in the model experiments page. You can compare it with other models side by side.