Meituan LongCat 2.0

meituan/longcat-2.0

Run Meituan LongCat 2.0 in a hosted Python Task with extended thinking and file inputs.

Meituan's LongCat 2.0 via OpenRouter. A mixture-of-experts model (1.6T total, 48B active parameters) for coding and repository-level changes, with a 1M token context window.

What Meituan LongCat 2.0 supports in qbash

Extended thinkingReasons through a problem before it replies.
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 Meituan LongCat 2.0 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: 131,072tokens
Temperature: 0 to 1default 1

Use Meituan LongCat 2.0 in a Python Task

qbash.ai.raw calls Meituan LongCat 2.0 from a Task and returns its reply as a string.

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

summary = qbash.ai.raw(
    f"Summarize these meeting notes in five bullets:\n\n{notes}",
    model="meituan/longcat-2.0",
    system="You are a concise analyst.",
)

qbash.output({"summary": summary})

Model calls in Tasks

Extended thinking with Meituan LongCat 2.0

Turn on Thinking in the same Settings popover to have Meituan LongCat 2.0 reason through a problem before it replies.