Poolside Laguna S 2.1

poolside/laguna-s-2.1

Run Poolside Laguna S 2.1 in a hosted Python Task with extended thinking and file inputs.

Poolside's Laguna S 2.1 via OpenRouter. A coding agent model (118B total, 8B active parameters) with a 1M token context window.

What Poolside Laguna S 2.1 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 Poolside Laguna S 2.1 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 Poolside Laguna S 2.1 in a Python Task

qbash.ai.raw calls Poolside Laguna S 2.1 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="poolside/laguna-s-2.1",
    system="You are a concise analyst.",
)

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

Model calls in Tasks

Extended thinking with Poolside Laguna S 2.1

Turn on Thinking in the same Settings popover to have Poolside Laguna S 2.1 reason through a problem before it replies.