The release comes the same week as a companion image-generation model, bringing Meta closer to its stated vision of personal superintelligence<\/a>.<\/p>\n (1) Today we\u2019re releasing Muse Spark 1.1 \u2014 a strong agentic and coding model at a very low price. It\u2019s available through our new Meta Model API and in Meta AI.<\/p>\n \u2014 Mark Zuckerberg (@finkd) July 9, 2026<\/a> <\/p>\n Muse Spark 1.1\u2019s Coding and Agentic Gains<\/p>\n Coding performance improved substantially on real-world tasks involving large, complex codebases, with the model able to diagnose and fix complex bugs, implement new features in enterprise-grade systems, and execute large code migrations. As a main agent, Muse Spark 1.1 gathers context, builds a plan, and delegates execution across parallel subagents; as a subagent, it stays within its assigned job and knows when to escalate back.<\/p>\n Amjad Masad, CEO of Replit, calling it a complete agentic foundation, said:<\/p>\n \u201c<\/p>\n What\u2019s most impressive about Muse Spark is how much it packs into one model: massive million-token context, full multimodal support (images, video, PDFs), built-in search with citations, strong reasoning, top-tier coding abilities (particularly frontend and design), structured output, and parallel tool calling \u2013 all in a clean OpenAI-compatible package. A complete agentic foundation.<\/p>\n Amjad MasadCEO \u2013 Replit<\/p>\n Wang\u2019s Meta Superintelligence Labs<\/a>, or MSL, trained Muse Spark 1.1 to excel at coding specifically because that skill underpins broader agentic capability, letting AI agents autonomously handle multiple tasks \u201clike a fleet of human interns,\u201d he said. This positions coding less as a standalone feature and more as the load-bearing skill behind Meta\u2019s wider agent push into AI coding ecosystem<\/a>.<\/p>\n Pricing Aimed Squarely at Anthropic and OpenAI<\/p>\n Meta is charging developers to access Muse Spark 1.1 through the Meta Model API, a shift from the company\u2019s earlier strategy of releasing models to the open-source community. Wang said MSL still has a Muse Spark variant in development that it intends to open-source, though he declined to say when.<\/p>\n That tension between the proprietary API and Meta\u2019s open-source roots is the clearest sign yet of how far the company will bend its own playbook to compete for the same developers who default to OpenAI<\/a> and Anthropic\u2019s Claude<\/a> for agentic coding work today. <\/p>\n \t\t\t\t\t Subscribe To Our Newsletter!<\/p>\n Be the first to get exclusive offers and the latest news.<\/p>\n What\u2019s Next?<\/p>\n Meta has not set a date for opening the Meta Model API beyond its own properties or for the open-source Muse Spark variant Wang referenced. Developers on the current waitlist will be added \u201cover time,\u201d and the pricing Wang called aggressive will face its real test once usage scales past the free-credit tier and against Anthropic\u2019s and OpenAI\u2019s own coding-model pricing moves.<\/p>\n SQ Magazine\u2019s Takeaway<\/p>\n Undercutting on price while still walling the API off to Meta\u2019s own properties is a hedge, not a full commitment to the open developer market Anthropic and OpenAI already compete for. Meta is testing whether aggressive per-token pricing can pull developers away from established coding assistants before it commits to wider distribution through marketplaces like OpenRouter.<\/p>\n The more telling signal is Wang\u2019s framing of coding as instrumental to agentic capability rather than a product in its own right. That reasoning explains why Meta trained Muse Spark 1.1 to work across popular third-party harnesses instead of building a closed coding environment, a bet that agent orchestration, not a standalone code editor, is where the category is actually heading.<\/p>\n","protected":false},"excerpt":{"rendered":"On July 9, 2026, Meta introduced Muse Spark 1.1, an AI model built for coding and agentic tasks,…\n","protected":false},"author":2,"featured_media":101437,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[8],"tags":[1227,53,52796,1123,66,157],"class_list":["post-101436","post","type-post","status-publish","format-standard","has-post-thumbnail","category-anthropic","tag-alexandr-wang","tag-anthropic","tag-meta-muse-spark-1-1-ai-coding","tag-meta-platforms","tag-news","tag-openai"],"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/101436","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/comments?post=101436"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/101436\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media\/101437"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media?parent=101436"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/categories?post=101436"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/tags?post=101436"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}![\"Newsletter\"](\"https:\/\/www.europesays.com\/ai\/wp-content\/uploads\/2026\/04\/newsletter.png\")
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