Seclai

Seclai

Pricing

Gemini 2.5 Pro

LLM
Google

Gemini 2.5 Pro is a reasoning model with configurable thinking budgets, excelling at complex coding, math, and science tasks, with multimodal support and 1-million token context.

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Context tokens

1,048,576

Output tokens

8,192

Training cutoff

Jan 1, 2025

Released

Jun 17, 2025

Schema

You can specify content config parameters as a regular JSON object with the JSON prompt format. We handle the model parameter and only the text modaility is supported at this time.

Schema documentation

Capabilities

Tool use
Structured output
Thinking
Multilingual
Multimodal

Supported languages

ar
bg
bn
cs
da
de
el
en
es
et
fi
fil
fr
hi
hr
hu
id
it
ja
ko
lt
lv
mr
ms
nl
no
pl
pt
ro
ru
sk
sl
sv
sw
ta
te
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.

  • URL Context

    The URL context tool lets you provide additional context to the models in the form of URLs. By including URLs in your request, the model will access the content from those pages (as long as it's not a URL type listed in the limitations section) to inform and enhance its response.

Pricing

TypeCreditsUnits
Cache hit1.66Credits per 1k tokens

Variants

Context Window

Support for longer context windows.

OptionDescriptionInput credits (per 1k tokens)Output credits (per 1k tokens)
200K or More ContextContext windows of 200,000 tokens or more.33.25199.50
Less than 200K ContextContext windows less than 200,000 tokens.16.63133.00