Goal announced spark muse 1.1 is now available in the US public preview, which gives developers access to tools that can handle coding assistance, file inspection, and more complex software tasks.
The model starts at $1.25 per million input tokens and $4.25 per million output tokens, making it a more affordable option compared to similar models from OpenAI and Anthropic. US developers participating in the preview receive $20 in free credits before charges apply.
Muse Spark 1.1 features a one million token contextual window, according to Meta.
What Muse Spark 1.1 does and what is its price
Meta introduces Muse Spark 1.1, a model designed for various tasks, including encoding and media understanding, on different input types. It can handle writing and debugging code, using software tools, interpreting text, images, videos, and documents, and performing multi-step tasks with minimal human supervision.
Developers can ask the model to interpret written instructions, review screenshots, read project files, or operate within software environments as part of a single job. Meta claims that the model excels in agent performance, tool usage, and computational tasks.
Mark Zuckerberg described Muse Spark 1.1 on X as “a solid agent and coding model at a very low price”, emphasizing its strengths in agent performance and tool utilization.
The API pricing for Muse Spark 1.1 is $1.25 per million input tokens and $4.25 per million output tokens.
The US public preview offers $20 in free credits for new users, allowing for trials without immediate payment. Meta’s AI director Alexandr Wang told CNBC that the pricing is “very aggressive and attractive” and that Meta is aiming for a pricing model that scales with high usage.
Compared to other coding-focused models, Muse Spark 1.1 costs are lower. anthropic Claudius Sonnet 5 charges $2 per entry and $10 per exit per million tokens, with an introductory rate valid until August 31, 2026, after which prices increase to $3 and $15 respectively.
anthropic Close Job 4.8 charges $5 per entry and $25 per exit per million tokens. Pricing for OpenAI’s GPT-5.6 has not yet been publicly announced for wide availability.
Overall, Muse Spark 1.1 offers a competitive option at both entry and exit pricing.
API Support, Free Credits, and How to Preview
Meta has indicated that Muse Spark 1.1 supports OpenAI-style APIs, which could make it easier for teams to compare it to other AI models. This means that developers switching vendors or testing multiple models can find it easier to use similar tools and integration approaches, reducing the amount of rework required. While
Meta has not provided specific details on compatibility parameters, the mention of the OpenAI-style framework suggests an API design that aligns with the patterns established by OpenAI’s Chat Completions API.
For developers interested in trying out Muse Spark 1.1, Meta is offering a public preview in the US through its developer platform. New preview users can redeem $20 in free credits.
To get started, configure API access using the endpoints provided by Meta. This allows you to try coding wizards, app development, and agent-based workflows before deciding to move to paid use.
Meta has not shared details on regional availability beyond the US public preview. Developers outside the US should stay tuned for announcements regarding international access.
What teams should consider before production use and current availability
For engineering teams considering Muse Spark 1.1 in their production coding workflows, there are several practical considerations to keep in mind. It is important to establish rules about where the tool can operate and when human approval should be required before making any changes to the code.
It is also advisable to configure logging to track changes made by the agent, especially for AI-assisted fixes that may cause problems later.
Defining review requirements for pull requests generated or modified by the agent helps maintain oversight. Additionally, sandboxed agent operations can prevent unwanted changes to critical systems.
While the lower price now removes cost as a barrier to experimentation, it does not reduce the operational risks associated with running encryption agents at scale. Responsibility for code quality and system stability lies with the engineering team using the tool.
The launch of Meta positions it as a serious contender in the agent coding market, alongside companies like Anthropic, OpenAI, and Google. Meta previously introduced Muse Spark as an AI assistant for its apps and smart glasses. Now, Muse Spark 1.1 is aimed at a different audience: developers who want to integrate the model into their coding tools and workflows.
This move fits with Meta’s broader push toward infrastructure services beyond social media. The company has been expanding its enterprise AI efforts, including investing in custom silicon and data center partnerships to support large-scale model training and inference.
Muse Spark 1.1 is currently available in the US through the Meta development platform in a public preview. The launch includes a free $20 credit and preview pricing structure, which will be live starting Thursday.
Meta has not announced a general availability date or timeline for regional expansion. Developers can stay tuned to Meta’s developer channels for updates on pricing, new features, and availability outside the US.
