Meta’s closed flagship for long coding sessions, with near-perfect recall across a million tokens. Priced in Australian dollars for teams in Australia, on the same key as every other model.
Muse Spark 1.3 is not on our public price list right now. Ask us if your team needs it.
Muse Spark is Meta’s proprietary line from Meta Superintelligence Labs — unlike Llama, its weights are not released. Version 1.3, from September 2026, is built for long agent sessions and coding across large repositories; Meta reports 75.4% on DeepSWE and 88.8% on Terminal-Bench 2.1.
Its most unusual strength is recall over long inputs: 98.1% on the MRCR test between half a million and a million tokens, so it finds what you need even at the far end of a huge document. Meta also says it is harder to trick with injected instructions, and more careful about actions that cannot be undone.
muse-spark-1.3Roar AI provides access to Muse Spark 1.3 through the Roar AI gateway, charged in Australian dollars on one bill with every other model. Requests from Australia go through our gateway in Singapore today; a gateway in Sydney is coming. Developers can use Muse Spark 1.3 alongside other supported models without a separate integration for every provider.
Use the OpenAI SDK you already have — point it at Roar AI and name the model. Read the docs.
from openai import OpenAI
client = OpenAI(base_url="https://api.roar-ai.com/v1", api_key="roar_live_…")
reply = client.chat.completions.create(
model="muse-spark-1.3",
messages=[{"role": "user", "content": "Summarise this contract in plain English."}],
)Muse Spark 1.3 is a frontier model, and requests are processed on international infrastructure, outside Australia. The model directory says where each model is processed.
No. Meta does not publish the weights, so it is only available through an API like this one.
Sign up, get a key and call it with the SDK you already use. Pay in your local currency, on one bill.