Meta is back. 🔥 Finally dropped its first model since Zuckerberg started writing checks like crazy. Launched Muse Spark (originally codenamed Avocado). Its a natively multimodal reasoning model that can look, reason, use tools, and split hard work across multiple cooperating agents. Claims it can reach similar capability with 10x+ less training compute than Llama 4 Maverick, They are not positioning Muse Spark as a top-of-the-line model, but is instead highlighting its efficiency and “competitive performance” on various tasks. The old bottleneck in AI is that one model often has to read, plan, call tools, and solve everything in one stream, which wastes compute and slows hard tasks. The key idea here is multi-agent orchestration, where several copies of the model work on the same problem in parallel and then compare or merge results, which is closer to a small team than a single assistant. That changes the scaling story because better performance no longer comes only from making 1 model bigger, but also from spending compute more intelligently at run time. So Muse is a stack built around 3 scaling axes: stronger pretraining for basic world and code understanding, steadier RL for improving answers after pretraining, and test-time reasoning so the model spends extra compute only when a problem is hard. The most interesting part is multi-agent orchestration, where several copies of the model reason in parallel and compare work, which raised Humanity’s Last Exam to 58% and FrontierScience Research to 38% in its heavier Contemplating mode. Meta also says the new pretraining recipe reaches similar capability with over 10x less compute than Llama 4 Maverick, which matters because cheaper training usually means faster iteration and more room to scale.