Muse Spark 1.3: Meta's Agentic Coding Model Explained

Meta's Muse Spark 1.3 is a hosted, closed-weight model built for long-horizon agentic coding: 1M context, $1.25/$4.25 pricing and AutomationBench scores level with GPT-5.6 Sol. Here is what changed and where it fits.

Published 23 September 2026 by Jake Hissitt, Founder of Stob.AI.

Meta spent two years being the open-weight company.

Muse Spark 1.3 is the clearest sign that this is no longer the whole strategy.

It is hosted, closed-weight, priced in the middle of the market, and aimed squarely at long-running agents rather than chat.

Here is what changed from 1.2, what the numbers actually say, and where it belongs in a production stack.

What Muse Spark 1.3 is built for Meta positions this release around three things: Long-horizon agentic workflows.

The model tracks context and prior results across a long task, works through messy or conflicting inputs, and asks for input when it is genuinely stuck rather than guessing.

Coding across many turns.

It is tuned for multi-step coding work with fewer unnecessary turns and cleaner output, whether you are building coding agents or using it as a development partner.

Native multimodal perception.

Video, images and documents are handled natively, and visual reasoning runs through a real execution environment rather than scripted steps.

You can hand it a screenshot or a clip and ask it to build from that.