models

OpenAI: GPT-6.1 Terra Pro

Markdown · JSON

OpenAI: GPT-6.1 Terra Pro

openai/gpt-6.1-terra-pro
OpenAITextInput $0.002 / 1KOutput $0.01 / 1K

The GPT-6.1 Terra Pro text listing for document work, comparing material and preparing structured responses.

Working with text material

GPT-6.1 Terra Pro in Ailoot API accepts a text request and returns a text response. This listing can form part of document preparation, source-material analysis and iterative refinement through conversation. Provide the task, necessary information and desired response format in one request or across the conversation’s messages.

Preparing a document

Start with the goal: which document you need, who it is for and what action it should help someone take. Include key points, source excerpts or a draft. Then define the structure—for example, an introduction, main conclusions, supporting arguments and next steps. For editing, specify what should change: length, tone, terminology or the order of presentation. This defines a verifiable result rather than an open-ended instruction to “improve the text.”

Analysis and comparison

To analyze several sources, separate them by title and define the comparison criteria. You can request a short summary of each text, a combined list of questions or a point-by-point comparison of requirements. If precise source attribution matters, ask for the document title and relevant passage alongside each conclusion. A field list and a completed example can help produce a response suited to further manual processing.

Connection and size

In Ailoot API, this listing is configured with the Messages, Responses, Chat Completions and Gemini-compatible generateContent text interfaces. Use the message format supported by your client. Document contents and other source material are supplied as text; the result is text that can be saved, edited or passed to the next stage of work.

For a large task, distribute the available space between source material, instructions and the expected response. If you need a brief conclusion, specify its length directly; if completeness matters, list the mandatory sections and verification criteria.

Request sequence

  1. Describe the end task and include the source text.
  2. Define the constraints and desired structure.
  3. Compare the response with the source material.
  4. Refine individual sections while preserving the overall goal and requirements.

Available through Ailoot API

Ultra Anthropic MessagesPOST /v1/messages
Input types
text
Output types
text
Context
Not specified in the catalogue
Max. output
Not specified in the catalogue
Input
$0.002 / 1K
Output
$0.01 / 1K
Cache read
$0.0001 / 1K
Cache write
$0.0025 / 1K
Cache write, 5 min
$0.0025 / 1K tokens
Cache write, 1 hour
$0.0025 / 1K tokens
web_search_call
$0.02 per call

Prices by request length · Anthropic Messages

Request size, tokensInputOutputCache readCache write5 min cache1 hour cache
Request size, tokens(0; 272,000]Input$0.002Output$0.01Cache read$0.0001Cache write$0.00255 min cache$0.00251 hour cache$0.0025
Request size, tokens(272,000; ∞)Input$0.004Output$0.015Cache read$0.0002Cache write$0.0055 min cache$0.0051 hour cache$0.005

Rates in USD per 1K tokens. If no rate is set, the base rate for this method is inherited; «—» means no base rate is set.

Ultra OpenAI ResponsesPOST /v1/responses
Input types
text
Output types
text
Context
Not specified in the catalogue
Max. output
Not specified in the catalogue
Input
$0.002 / 1K
Output
$0.01 / 1K
Cache read
$0.0001 / 1K
Cache write
$0.0025 / 1K
Cache write, 5 min
$0.0025 / 1K tokens
Cache write, 1 hour
$0.0025 / 1K tokens
web_search_call
$0.02 per call

Prices by request length · OpenAI Responses

Request size, tokensInputOutputCache readCache write5 min cache1 hour cache
Request size, tokens(0; 272,000]Input$0.002Output$0.01Cache read$0.0001Cache write$0.00255 min cache$0.00251 hour cache$0.0025
Request size, tokens(272,000; ∞)Input$0.004Output$0.015Cache read$0.0002Cache write$0.0055 min cache$0.0051 hour cache$0.005

Rates in USD per 1K tokens. If no rate is set, the base rate for this method is inherited; «—» means no base rate is set.

Ultra OpenAI ChatPOST /v1/chat/completions
Input types
text
Output types
text
Context
Not specified in the catalogue
Max. output
Not specified in the catalogue
Input
$0.002 / 1K
Output
$0.01 / 1K
Cache read
$0.0001 / 1K
Cache write
$0.0025 / 1K
Cache write, 5 min
$0.0025 / 1K tokens
Cache write, 1 hour
$0.0025 / 1K tokens
web_search_call
$0.02 per call

Prices by request length · OpenAI Chat

Request size, tokensInputOutputCache readCache write5 min cache1 hour cache
Request size, tokens(0; 272,000]Input$0.002Output$0.01Cache read$0.0001Cache write$0.00255 min cache$0.00251 hour cache$0.0025
Request size, tokens(272,000; ∞)Input$0.004Output$0.015Cache read$0.0002Cache write$0.0055 min cache$0.0051 hour cache$0.005

Rates in USD per 1K tokens. If no rate is set, the base rate for this method is inherited; «—» means no base rate is set.

Ultra Gemini generateContentPOST /v1beta/models/openai/gpt-6.1-terra-pro:generateContent
Input types
text
Output types
text
Context
Not specified in the catalogue
Max. output
Not specified in the catalogue
Input
$0.002 / 1K
Output
$0.01 / 1K
Cache read
$0.0001 / 1K
Cache write
$0.0025 / 1K
Cache write, 5 min
$0.0025 / 1K tokens
Cache write, 1 hour
$0.0025 / 1K tokens
web_search_call
$0.02 per call

Prices by request length · Gemini generateContent

Request size, tokensInputOutputCache readCache write5 min cache1 hour cache
Request size, tokens(0; 272,000]Input$0.002Output$0.01Cache read$0.0001Cache write$0.00255 min cache$0.00251 hour cache$0.0025
Request size, tokens(272,000; ∞)Input$0.004Output$0.015Cache read$0.0002Cache write$0.0055 min cache$0.0051 hour cache$0.005

Rates in USD per 1K tokens. If no rate is set, the base rate for this method is inherited; «—» means no base rate is set.

openai/gpt-6.1-terra-pro · JSON
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You can request a short summary of each text, a combined list of questions or a point-by-point comparison of requirements. If precise source attribution matters, ask for the document title and relevant passage alongside each conclusion. A field list and a completed example can help produce a response suited to further manual processing.\n\n### Connection and size\n\nIn Ailoot API, this listing is configured with the Messages, Responses, Chat Completions and Gemini-compatible generateContent text interfaces. Use the message format supported by your client. Document contents and other source material are supplied as text; the result is text that can be saved, edited or passed to the next stage of work.\n\nFor a large task, distribute the available space between source material, instructions and the expected response. If you need a brief conclusion, specify its length directly; if completeness matters, list the mandatory sections and verification criteria.\n\n### Request sequence\n\n1. Describe the end task and include the source text.\n2. Define the constraints and desired structure.\n3. Compare the response with the source material.\n4. 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Questions

How do I choose a model for my task?

First identify the required input and output: text, image, audio or video. Then compare compatible API methods, the exact model ID or current alias target, price and billing unit. GET /v1/models is free and lists models available to your key.

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Use the API methods and input/output types listed on the model card. Support for text, images, audio or video depends on the selected model and method; check their request example before sending your data.

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Check the model card for the price and billing unit of the selected API method. Compare the same unit and input/output type; request history shows actual usage and the charged amount.

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