Mark Zuckerberg says Meta's Watermelon model and Muse Spark open weights are “coming soon”
Muse Spark 1.3 is rolling out today with frontier performance almost too cheap to meter. This is the biggest jump we've made so far on coding and agentic work. Try it in Muse Code and our API. Next up 🍉 and Muse Spark open weights releases coming soon.
@finkdMark Zuckerberg
Context & Ripple Effects
Meta has been pairing fast-moving proprietary access with an open-weight track: it made Muse Spark 1.1 available through a public API preview in July, then released Muse Glimmer as open weights in August while signaling a future open-weight version of its more advanced Spark line. Spark 1.3’s rollout in Muse Code and the Meta Model API gives developers a hosted path while they await the promised weights.
The Watermelon and Muse Spark commitments turn that earlier signal into a stated near-term release plan. Public reaction has focused on the prospect of a frontier-capable American open-weight option, but Meta has not yet specified release timing or terms.
First-order effects
Developers using Muse Code and Meta’s API can evaluate Spark 1.3’s coding and agentic improvements while planning for a version of Muse Spark that can be run from released weights.
Meta extends the distribution of its model family beyond its own hosted products by committing to release Watermelon and Muse Spark weights.
Second-order effects
Providers of managed model infrastructure and developer tooling gain a prospective new workload if teams move Muse Spark deployments from Meta’s API to their own environments.
Rival frontier-model vendors face added pressure to distinguish hosted APIs through product integration, reliability, or pricing when a competing model family is available as weights.
The contest in coding and agentic models is broadening from benchmark performance to the choice between vendor-operated access and deployments controlled by customers.
The trend: Frontier AI vendors are increasingly using open weights to widen developer adoption while retaining hosted products as the path for integrated services.
great momentum from @finkd and @alexandr_wang. particularly excited by their upcoming open weights launch - we need more American open weight models at the frontier.
Muse Spark 1.3 is now live! With solid improvements on coding and agentic work including computer use. Please give it a try and let us know what you think.
We've experimented some breakthrough training methods and turns out that it works. Try the model on Muse Code harness! We appreciate any feedback from you.
This week is absolutely nuts for AI releases, and now a major new model update from Muse. We appear to be reaching escape velocity in capability progress. If this thing gets released as open weights it completely changes the dynamic of US open weights competitiveness.
We spent a lot more compute in grading to improve model behaviors such as laziness, instruction following, hedging, and other reward seeking and reward hacking behaviors. As a result the model's usability is vastly improved. Please give it a try and let us know what you think.
Muse Spark 1.3 is our most capable model yet, with major improvements to usability, including complex instruction following and reduced hallucinations in agentic tasks. 🍉 and open-weight Muse Spark are coming soon!
long context benchmark (MRCR) going crazy, very interesting would be great to have other benchmarks such as graphwalks for long context and release test time scaling curves and not just raw benchmark scores in general