Meta Muse Spark 1.3

meta/muse-spark-1.3

Run Meta Muse Spark 1.3 in a hosted Python Task with structured output, extended thinking and file inputs.

Meta's Muse Spark 1.3 via OpenRouter. A multimodal reasoning model for long-running agent and coding work. Accepts image, video and file input with a 1M token context window.

What Meta Muse Spark 1.3 supports in qbash

Structured outputReplies as JSON that matches a schema you pass.
Extended thinkingReasons through a problem before it replies.
Reasoning effort6 levels, from minimal 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 Meta Muse Spark 1.3 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

Structured output with Meta Muse Spark 1.3 in a Python Task

qbash.ai.raw calls Meta Muse Spark 1.3 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="meta/muse-spark-1.3",
    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

Reasoning effort with Meta Muse Spark 1.3

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

Turn on Thinking in the same Settings popover to have Meta Muse Spark 1.3 reason through a problem before it replies.