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GPT-6 Astra

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gpt-6-astra

Run GPT-6 Astra in a hosted Python Task with structured output, web search and file inputs.

OpenAI's most capable flagship model, built for the hardest end-to-end work: complex reasoning, coding, research, and document creation. Features a 1.05M token context window, 128K max output, image understanding, and the full reasoning effort range up to max. Knowledge cutoff April 2026. OpenAI documents additional native tools for this family, but qbash currently exposes the verified web search path only.

What GPT-6 Astra supports in qbash

  • Structured outputReplies as JSON that matches a schema you pass.
  • Web searchSearches the web while it answers.
  • Reasoning effort5 levels, from low to max.
  • Image inputReads WEBP, PNG, JPEG and GIF images.
  • Document inputReads PDF, TEXT, DOC, XLS, RTF and 7 more files.
  • Prompt cachingRepeated input is billed at the cached rate.

What is qbash?

qbash is where you build Tasks: Python programs that run a business process on managed infrastructure. Your code runs the steps and calls a model like GPT-6 Astra only at the ones that need judgment, with integrations, memory and files available in the same script.

A developer writes the Task once, and anyone on the team runs it from a form, on a schedule, from a webhook or from chat. Each Task is versioned and every run is logged.

How Tasks work

Specifications

Context window
1.05Mtokens
Max output
128,000tokens

Structured output with GPT-6 Astra in a Python Task

qbash.ai.raw calls GPT-6 Astra from a Task. Pass a JSON Schema as output_schema and the reply comes back as a Python dict that matches it, ready to route to a connector.

main.py
ticket = qbash.inputs.get("ticket")

triage = qbash.ai.raw(
    f"Summarize this support ticket and rate its urgency:\n\n{ticket}",
    model="gpt-6-astra",
    output_schema={
        "type": "object",
        "properties": {
            "summary": {"type": "string"},
            "urgency": {"type": "string", "enum": ["low", "medium", "high"]},
        },
        "required": ["summary", "urgency"],
    },
)

# triage is a dict, e.g. {"summary": "...", "urgency": "high"}
if triage["urgency"] == "high":
    qbash.integrations.slack.create_message(
        channel="#support",
        text=triage["summary"],
    )

qbash.output(triage)
Structured output in Tasks

Use GPT-6 Astra with web search

Turn on Web Search in an inline prompt's model bar and GPT-6 Astra searches the web while it answers. Searches are billed at $10.00 per 1,000.

Provider web tools

Reasoning effort with GPT-6 Astra

Set Effort to low, medium, high, xhigh and max in the prompt's Settings. The default is high. Higher effort spends more tokens on reasoning before the reply.

GPT-6 Astra pricing

Input$10.00 per 1M tokens
Output$50.00 per 1M tokens
Cached input$1.00 per 1M tokens
Cache write$12.50 per 1M tokens
Web search$10.00 per 1K searches
Input, above 272K input tokens$20.00 per 1M tokens
Output, above 272K input tokens$75.00 per 1M tokens

Standard rates in USD.

Supported file formats

Images

  • WEBP up to 20 MB
  • PNG up to 20 MB
  • JPEG up to 20 MB
  • GIF up to 20 MB

Documents

  • PDF
  • TEXT
  • DOC
  • XLS
  • RTF
  • DOCX
  • XLSX
  • PPTX
  • PPT
  • ODT
  • ODP
  • ODS

Automate GPT-6 Astra with qbash

Guides that use GPT-6 Astra