Meta says it has caught up with Anthropic and OpenAI with Muse Spark 1.3, its most powerful AI model so far

Meta Platforms Inc. released Muse Spark 1.3, its most powerful large language model to date, claiming it is now competitive with Anthropic PBC's Claude Fable 5.1 and better than OpenAI Group PBC's GPT-5.6 Sol in coding and agentic automation. An independent analysis by Artificial Analysis scored Muse Spark 1.3 at 62 on its Intelligence Index, placing it behind only Claude Fable 5.1 and Claude Opus 5. Meta Chief AI Officer Alexandr Wang said the model also outperforms current Chinese models, as the company shifts to a proprietary strategy after spending hundreds of billions on AI infrastructure.

Meta says it has caught up with Anthropic and OpenAI with Muse Spark 1.3, its most powerful AI model so far Meta Platforms Inc. https://www.meta.com/ says it has more or less caught up with the biggest artificial intelligence labs with the release of its most powerful large language model so far, Muse Spark 1.3. The company said in a blog post https://research.meta.ai/blog/introducing-muse-spark-1-3 today that the new model can be accessed by developers willing to pay for it through its application programming interface. It’s also going to be rolled out to users of Meta’s social media platforms, Facebook and Instagram, as well as the Meta AI application, in the coming days. In an interview https://www.bloomberg.com/news/articles/2026-09-02/meta-releases-more-powerful-ai-model-edging-closer-to-rivals with Bloomberg, Meta Chief AI Officer Alexandr Wang said Muse Spark 1.3 represents the company’s biggest jump in model performance so far, putting it at the same level as the most recent models created by OpenAI Group PBC and Anthropic PBC. Pointing to advances in Muse Spark 1.3’s coding and agentic automation capabilities, Wang said it is now “competitive” with Anthropic’s Claude Fable 5.1 and “better than” OpenAI’s GPT-5.6 Sol model, especially in terms of its ability to generate code. It also “outperforms any of the current Chinese models out there,” Wang claimed. Such claims are always difficult to judge when it comes to AI models, because they tend to be better at some tasks than others, and it’s easy for companies to game the benchmark tests they publish. However, an independent analysis by Artificial Analysis showed https://artificialanalysis.ai/models/muse-spark-1-3 intelligence-breakdown that Muse Spark achieved a score of 62 on its Intelligence Index after evaluating its performance across a host of popular benchmarks, putting it behind only Fable 5.1 and Opus 5, and ahead of OpenAI’s models. Meta has released Muse Spark 1.3, their fourth Muse Spark model release in five months. Muse Spark 1.3 max , which is in limited preview for Meta’s partners, scores 62 on the Artificial Analysis Intelligence Index, behind only Claude Fable 5.1 and Claude Opus 5. The variant… pic.twitter.com/D7eL8bGwAU — Artificial Analysis @ArtificialAnlys September 2, 2026 The evaluation suggests that Meta could finally start seeing some payback from its massive, multibillion-dollar investments in AI https://siliconangle.com/2026/07/28/meta-build-14b-el-paso-data-center-campus-blackrock/ . The company has been spending hundreds of billions of dollars https://siliconangle.com/2026/07/13/meta-boosts-investment-hyperion-data-center-campus-50b/ on AI infrastructure and development in an effort to catch up with Anthropic, OpenAI and its Chinese rivals. Last year, founder and Chief Executive Mark Zuckerberg revamped Meta’s AI strategy, paying over $14 billion https://siliconangle.com/2025/06/12/scale-ai-ceo-alexandr-wang-departs-join-meta-securing-multibillion-investment/ to acquire a stake in Wang’s former company ScaleAI Inc. and hire him to run his new Superintelligence Labs unit. Since then, Wang has stepped up Meta’s game by enhancing the capabilities of its models and launching new versions as part of an aggressive release cadence. However, Meta’s spending has drawn a lot of scrutiny https://siliconangle.com/2026/07/29/metas-ai-bill-swallows-nearly-free-cash-flow-profit-falls-14/ from investors, who are getting nervous about when it will see a return on investment. That’s why Meta has abandoned the open-source model it followed with its Llama models in favor of a proprietary strategy similar to Anthropic and OpenAI. In July, when it launched Muse Spark 1.1 https://siliconangle.com/2026/07/09/meta-launches-flagship-muse-spark-1-1-model-multi-agent-upgrades/ , the company said it would be charging developers to access the model for the first time, though it was noticeably cheaper than its rivals’ models. Zuckerberg said at the time that the plan is to make the Muse Spark family one of the most affordable LLMs on the market. According to Wang, developers will not have to pay any more to access Muse Spark 1.3 than they were paying to use Muse Spark 1.2, which was launched in August https://siliconangle.com/2026/08/05/meta-takes-anthropic-openai-first-ai-coding-agent-muse-code/ . Like its two predecessors, it’s available through the Meta Model API, which also provides developers with various tools for building AI applications. Wang told Bloomberg that Meta has seen rapid adoption of the Muse Spark LLM family, with some developers using “trillions of tokens per week.” He said they’ll be very happy with Muse Spark 1.3, because it’s more efficient that version 1.2, using around 25% fewer tokens to accomplish the same tasks. It can also support multiple workflows at once, instead of requiring separate sessions for each one, and it’s better at handling long and complex instructions, and retaining context across multiple tasks. It also has more awareness of its own limitations, Wang said, and it is much safer. In every case when it’s about to take an action that’s irreversible, it will ask for confirmation before it goes and does it. Though Meta is now charging for access to its most powerful models, Zuckerberg recently authored a blog post stressing the need to make AI development more open and accessible. But the company has not yet decided if it’s going to release Muse Spark 1.3’s weights. Open-weights models, popularized by Chinese AI model makers, also release the “weights,” or the internal blueprint that shows how the model responds to user’s prompts. When companies release a model alongside its weights, it means that developers can download it and run it anywhere, and modify it in any way they see fit, without paying for it. Meta has previously promised to release the weights for Muse Spark 1.2, but has not yet done so. Meta may get around to doing this by the time it releases its highly anticipated model, called Watermelon, which is said to be larger and much more powerful than the Muse Spark models. The company has been working on Watermelon for some time, but Wang declined to say when it might be released. For now, it remains a work in progress, but Wang believes it will be worth the wait. “We believe that Watermelon will be extremely competitive,” he added. 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