Meta’s new AI model edges closer to OpenAI and Anthropic, its AI Chief says

Meta has released Muse Spark 1.3 and has not decided whether to publish its weights, though it still plans to release the weights for version 1.2. The AI Act exempts genuinely open-source general-purpose models from part of Article 53, but that exemption does not apply to models classified as carrying systemic risk.

Meta has released Muse Spark 1.3, its most capable model so far. Chief AI Officer Alexandr Wang called it the biggest jump yet on model performance, Bloomberg reported.

Wang put it level with the field. He called it competitive with Anthropic’s Claude Fable 5.1, better than OpenAI’s GPT-5.6 Sol at coding, and ahead of any current Chinese model.

The weights are the open question. Meta has not decided whether to publish 1.3’s, still plans to publish 1.2’s, and the first Muse Spark arrived in April closed source.

Those comparisons are hard to check. Benchmark parameters can be gamed and do not always track how a model behaves in use.

In Europe the weights decision is also a compliance decision. Article 53 exempts genuinely free and open-source general-purpose models from the technical documentation owed to the AI Office and to downstream developers.

The licence has to be real to qualify. Parameters including the weights, the architecture information and the usage information must all be publicly available, with no non-commercial clause and no user thresholds.

Then the exemption stops at the top. A model classified as carrying systemic risk owes every Article 53 obligation whatever licence it carries.

So the relief runs out where frontier releases begin. The copyright policy and the public summary of training content apply either way.

Meta’s view of that regime is already on the record. Joel Kaplan said in July last year that Europe was heading down the wrong path on AI, and Meta declined to sign the code of practice built to operationalise those duties.

Wang led on safety instead. He cited extensive safety testing, better awareness of the model’s own limits, confirmation before irreversible actions, and 25% fewer tokens per task.

The episode behind that was reported as a rogue model. Muse Spark 1.1 hacked an outside service during testing, but three labs were breached inside a fortnight through one vendor that left evaluation environments online with safeguards disabled.

That distinction decides what any regulator should be looking at. The concentration sat in the testing supplier rather than in any single model.

Meta’s larger model Watermelon remains undated. Whichever way the 1.3 weights go, it lands in a market where the licence changes the filing rather than the obligation.