Muse Spark 1.3
Released
Muse Spark 1.3 is an AI model released by Meta on Wednesday, Sep 2 2026, 23 days after Muse Glimmer. It has a 1M token context window. Benchmark results (shown below) cover DeepSWE 1.1, SWEAtlas CodeBase QnA, JobBench, DeepSearchQA, Agentic IF Index (Internal), MRCR, and 4 more.
Benchmarks
Coding
Terminal & CLI
Agentic & tool use
Reasoning & science
Knowledge work
Long context
About
Muse Spark 1.3, released September 2, 2026, arrived four weeks after Muse Spark 1.2 and was announced by Mark Zuckerberg on X rather than through a launch post — a same-day rollout into Muse Code and the Meta Model API, pitched as frontier performance "almost too cheap to meter" and as the biggest jump Meta had made on coding and agentic work. It kept the shape of the 1.2 release, proprietary and with a 1M-token context window, but widened the launch comparison from a handful of coding rows to eleven benchmarks spanning knowledge work, agentic tool use, long context and terminal coding. Meta used the same announcement to trail two unshipped releases — an unnamed model and open weights for the Muse Spark line — giving a date for neither.
The comparison table set Muse Spark 1.3 at its max reasoning setting against Muse Spark 1.2 at xhigh, GPT-5.6 Sol and Claude Opus 5. Its clearest gains at launch were in long context and code comprehension: 98.5% and 98.1% on MRCR at the 256k-512k and 512k-1M spans, against 66.3% and 55.5% for 1.2, with Opus 5 reporting no figure at either span, and 59.4% on SWEAtlas CodeBase QnA, ahead of every rival on the table. It took the coding rows too, with 75.4% on DeepSWE v1.1 and 88.8% on Terminal-Bench 2.1, the latter tied with GPT-5.6 Sol. The agentic and knowledge-work rows went the other way: 1754 on GDPval-AA v2, 64.9% on JobBench, 66.9% on OSWorld 2.0 and 49.4% on AutomationBench each sat just behind Claude Opus 5, while 89.4% on DeepSearchQA and 57.8% on Meta's internal Agentic IF Index trailed both rivals. As at the 1.2 launch, the figures for competing models were Meta's own runs rather than each lab's published results, and several of them differ from the numbers those labs reported themselves.
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Frequently asked questions
Muse Spark 1.3 was released by Meta on Wednesday, Sep 2 2026.
Muse Spark 1.3 was built by Meta. Develops the open-weight Llama series of models. Committed to open-source AI research.
Muse Spark 1.3 reports 11 tracked benchmark scores — DeepSWE 1.1: 75.4%; SWEAtlas CodeBase QnA: 59.4%; Terminal-Bench 2.1: 88.8%; JobBench: 64.9%; DeepSearchQA: 89.4%; Agentic IF Index (Internal): 57.8%; OSWorld 2.0: 66.9%; AutomationBench: 49.4%; GDPval-AA v2: 1754; MRCR (256k-512k): 98.5%; MRCR (512k-1M): 98.1%. Scores are the figures published at release by Meta. It holds the best score among all models tracked here on DeepSWE 1.1, SWEAtlas CodeBase QnA, JobBench, DeepSearchQA, Agentic IF Index (Internal), MRCR (256k-512k) and MRCR (512k-1M).
Muse Spark 1.3 has a context window of 1M. That is the maximum amount of input plus output the model can hold in a single request.
No. Muse Spark 1.3 is a proprietary model. The weights are not published — it is available only through the provider's own API, apps, or partner platforms.
Meta's previous tracked release was Muse Glimmer on Aug 10 2026, 23 days earlier. It is the most recent Meta model tracked on AI Release Tracker.