Muse Code

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Muse Code is a terminal coding agent developed by Meta Superintelligence Labs, released in beta on August 5, 2026 alongside the Muse Spark 1.2 model that powers it ^[1][3]. It is Meta's first coding agent, entering a category defined by Anthropic's Claude Code, OpenAI's Codex, and Google's Gemini CLI ^[5][9]. Meta pitches the tool at long-horizon software engineering across large repositories: it plans changes, writes code, validates the results, and coordinates persistent sub-agents that work on multi-file tasks with less human steering ^[1][3]. The company is positioning it on price rather than raw capability, with a discounted "Contributor" tier for developers who let Meta train on their prompts and completions ^[5][9].

Background

Meta Superintelligence Labs, the unit Mark Zuckerberg formed in June 2025 around former Scale AI chief executive Alexandr Wang, replaced the open-weight Llama line with the proprietary Muse Spark family on April 8, 2026 ^[7][15]. Muse Spark 1.1 followed on July 9, 2026, with stronger agent and coding abilities, a 1 million token context window, and the public preview of the Meta Model API for developers in the United States ^[11][12]. TechCrunch framed that release as Meta's entry into "the crowded AI coding battle," and described the company as a straggler in agent harnesses that was trying to catch up ^[6][12].

Muse Code is the harness half of that effort. Meta says Muse Spark 1.2 and Muse Code were co-trained so the model performs best inside its own agent, using rejection-sampled harness trajectories and training recipes tuned for goals, context compaction, and sub-agent delegation ^[1]. CNBC reported the launch as Meta's first coding agent and the latest major release under Wang, who oversees foundation model development ^[5].

Launch

Meta announced Muse Code on August 5, 2026 in a Meta Superintelligence Labs blog post titled "Introducing Muse Code and Muse Spark 1.2" ^[1]. Zuckerberg wrote on X that the tool "takes on complete software engineering tasks across large repos: planning changes, writing code, validating the results" ^[4]. The AI at Meta account described "persistent sub-agents" solving complex multi-file changes ^[3]. The beta installs on macOS and Linux with a single shell command; there is no desktop application, unlike the app-based options that exist for Claude Code and Codex ^[1][8].

The launch drew immediate attention: the announcement reached the front page of Hacker News, where the thread collected 326 points and 257 comments in its first days ^[14].

Design

Meta describes Muse Code as a simple agent loop augmented by asynchronous background agents. These background agents stay alive for the whole session instead of being spawned per task, which Meta says avoids repeated information gathering and reduces latency on difficult multi-step work. They carry out next steps on their own and decide when to report back to the main agent ^[1].

Zuckerberg gave more detail in his launch posts: when a job is large enough, Muse Code fans out to sub-agents that work in parallel inside isolated worktrees, so the developer's working copy is never touched. In Meta's testing, the agent built six features for a game simultaneously without collisions ^[6][7].

The runtime is built around a local append-only event log that records every model call, tool run, approval, and edit. Meta says this makes the runtime replay-exact and restart-safe: after a crash, the agent resumes exactly where it stopped, which matters for tasks that run for hours ^[1][8]. Muse Code also ships with default skills: /plan turns a task into an approval-gated plan, /grill stress-tests that plan, and /goal keeps the agent working toward a stated objective ^[1][9].

Muse Spark 1.2

The model behind the agent is Muse Spark 1.2, a coding-focused update to Muse Spark 1.1. Meta says it scaled up training compute on coding tasks, widened training environment diversity, and trained extensively on long-horizon work such as whole-repository generation and large end-to-end projects, with planning, goal conditioning, and context compaction used to sustain progress ^[1]. Meta also describes a self-improvement loop: Muse Spark 1.1 generated challenging coding environments and instruction-following templates, then graded candidate solutions, producing training data for 1.2 ^[1].

As a capability demonstration, Meta had the model iteratively optimize GPU kernels over more than 1,000 tool calls and up to 24 hours per run, benchmarking KDA and MLA kernels written in Triton for NVIDIA Hopper GPUs against reference implementations. Models were barred from importing existing kernel libraries and had to implement the algorithms themselves ^[1][7].

Muse Spark 1.2 is available in Muse Code and through the Meta Model API "with expanded global access," a change from the US-only preview that accompanied 1.1 ^[1][11]. The model remains closed-weight. Asked on X whether Muse Spark would be open-sourced, Zuckerberg replied "I'll have more to share on that soon" ^[7]. Meta has not said whether the Muse Code client itself will be open source, and no public source repository for it had been identified as of August 7, 2026 ^[14].

Benchmark results

Meta published bar charts of its own evaluations rather than claiming state of the art. On every coding chart in the announcement, Muse Spark 1.2 with Muse Code trails Anthropic's Claude Opus 5 running in Claude Code and beats xAI's Grok 4.5 in Grok Build; against OpenAI's GPT-5.6 Terra in Codex it splits the results, leading on Terminal-Bench 2.1 and Meta Internal Coding Bench but trailing on DeepSWE 1.1 (59.3% versus 64.8%). The Register summed the showing up as "close to the best, but never the very best" ^[7]. All figures below are Meta's numbers from the August 5 announcement and should be read as vendor-reported ^[1][2].

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The one chart Muse Spark 1.2 tops is MCP Atlas, a Scale AI benchmark of tool use across real Model Context Protocol servers ^[1][2]. GDPVal-AA v2 scores are Elo ratings produced by Artificial Analysis on professional deliverable tasks drawn from OpenAI's GDPval dataset ^[2].

Meta's accompanying methodology report explains how the numbers were produced. Terminal-Bench 2.1 (a Stanford and Laude Institute benchmark) was run on all 89 tasks of the official release, five attempts per task, each agent in an isolated cloud sandbox; DeepSWE v1.1 is Datacurve's 113-task software engineering benchmark spanning 91 repositories in five languages; Meta Internal Coding Bench is 440 tasks derived from Meta's internal pull requests. Each third-party model ran inside its own vendor's agent (Claude Code for Opus 5, Codex for GPT-5.6 Terra, Grok Build for Grok 4.5, Antigravity for Gemini 3.6 Flash), and Meta cautions that its setup may not show those models at their best ^[2].

The numbers are not official leaderboard entries. On the public Terminal-Bench 2.1 leaderboard at tbench.ai, which lists runs from many different agent harnesses, submitted through the benchmark's harbor framework and verified by the Terminal-Bench team, the top verified entry as of August 7, 2026 was Claude Code running Anthropic's Fable 5 model at 83.8%, and Muse Spark 1.2 did not yet appear; Muse Spark 1.1 sat at 76.2% with the mini-SWE-agent harness, matching Meta's chart ^[10]. Commenters on Hacker News and The Register also asked why Meta compared against OpenAI's GPT-5.6 Terra rather than the larger GPT-5.6 Sol on the coding charts ^[7][14].

Pricing and availability

Muse Code is metered through the Meta Model API rather than sold as a subscription, and billing runs through the same Meta developer account that hosts the API ^[5]. Meta offers two tiers. The Standard tier matches the Muse Spark 1.1 API prices of $1.25 per million input tokens and $4.25 per million output tokens ^[5][9]. The Contributor tier drops the price to $0.10 per million input tokens and $0.20 per million output tokens; in exchange, developers opt in to letting Meta use their prompts and completions to train future models ^[9]. Wang called the cheaper tier "more than 10 times cheaper than even the pay-as-you-go tier" ^[5].

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Pricing and rate limits per MacRumors and CNBC, August 5, 2026 ^[5][9]; Meta documents the tiers on its developer site ^[13].

Wang also said Meta was "starting to accept requests for zero-data retention" for enterprises that do not want any developer data kept ^[5]. Beyond Meta's own API, Muse Spark 1.2 is available through OpenRouter ^[5][7]. The model offers a 1 million token context window, a capacity introduced with Muse Spark 1.1 ^[7][11].

Competitive landscape

Muse Code enters a crowded field of terminal agents: Claude Code, OpenAI Codex, Gemini CLI, and editor-centric tools such as Cursor. Wang told CNBC that Meta is differentiating on price rather than capability against Anthropic and OpenAI ^[5], and told the Wall Street Journal the tool "can be an incredibly good option, especially from a cost perspective" for many workflows ^[6]. The Contributor tier's discount, roughly a twelfth of standard input pricing, is the sharpest expression of that strategy, though it revives a familiar Meta trade-off: MacRumors headlined its coverage "Meta's New Mac Coding Agent Costs Up to 20x Less If You Let Meta Train on Your Data" ^[9].

The launch also fits a broader monetization push. CNBC noted that Meta, which still earns 98% of its revenue from advertising, is trying to build AI revenue while spending heavily on data centers, and that its shares fell the prior week on a light revenue forecast and shrinking free cash flow ^[5].

Reception

Early reviews treated Muse Code as a credible but not category-leading entry. The Register judged that Muse Spark 1.2 "performed honorably" against Opus 5, GPT-5.6 Terra, Grok 4.5, and Gemini 3.6 in tightly clustered scores, and noted researcher Hongyu Ren of Meta Superintelligence Labs boasting "TBH it's a good harness" ^[7]. On Hacker News, commenters welcomed the expanded global API access and the cheap Contributor pricing, comparing it to DeepSeek-level rates, but criticized the required Meta account sign-in, pressed Meta to publish cost and latency alongside benchmark scores, and repeatedly asked whether the client or the model weights would be opened ^[14]. The closed-weight release continues the break from Meta's Llama-era openness, which The Register called out directly ^[7].

See also

• Muse Spark
• Meta Superintelligence Labs
• Claude Code
• OpenAI Codex
• Gemini CLI
• Terminal-Bench
• SWE-bench
• Meta AI

References

1. ^Meta Superintelligence Labs. "Introducing Muse Code and Muse Spark 1.2." Meta AI Research Blog. August 5, 2026. research.meta.ai/...g-muse-code-and-muse-spark-1-2
2. ^Meta Superintelligence Labs. "Muse Spark 1.2 & Muse Code: Evaluation Methodology." August 2026. research.meta.ai/...muse-spark-1-2-methodology
3. ^AI at Meta (@AIatMeta). "Introducing Muse Code (beta), a terminal coding agent built for long-horizon software engineering..." X. August 5, 2026. x.com/...2085084709277565213
4. ^Mark Zuckerberg (@finkd). "Releasing Muse Code in beta today..." X. August 5, 2026. x.com/...2085080750034940201
5. ^Jonathan Vanian. "Meta debuts first AI coding agent to take on Anthropic and OpenAI." CNBC. August 5, 2026. cnbc.com/...-code-to-take-on-anthropic-and-openai-
6. ^Lucas Ropek. "Meta launches Muse Code, an AI agent for large code bases." TechCrunch. August 5, 2026. techcrunch.com/...an-ai-agent-for-large-code-bases
7. ^Joab Jackson. "Meta wants to get inside your terminal with its new coding agent." The Register. August 6, 2026. theregister.com/...5283717
8. ^Zac Hall. "Meta launches Muse Code AI coding agent for macOS and Linux." 9to5Mac. August 5, 2026. 9to5mac.com/...ai-coding-agent-for-macos-and-linux
9. ^Juli Clover. "Meta's New Mac Coding Agent Costs Up to 20x Less If You Let Meta Train on Your Data." MacRumors. August 5, 2026. macrumors.com/...meta-muse-code-for-mac
10. ^Terminal-Bench. "terminal-bench@2.1 Leaderboard." tbench.ai. Accessed August 7, 2026. tbench.ai/...2.1
11. ^Meta Superintelligence Labs. "Introducing Muse Spark 1.1." Meta AI Research Blog. July 9, 2026. research.meta.ai/...cing-muse-spark-meta-model-api
12. ^Lucas Ropek. "Meta enters the crowded AI coding battle with Muse Spark 1.1." TechCrunch. July 9, 2026. techcrunch.com/...oding-battle-with-muse-spark-1-1
13. ^Meta. "Model API: Pricing and rate limits." dev.meta.ai. Accessed August 7, 2026. dev.meta.ai/...pricing-rate-limits
14. ^Hacker News. "Muse Code and Muse Spark 1.2" (discussion thread). August 5, 2026. news.ycombinator.com/item
15. ^Meta Superintelligence Labs. "Introducing Muse Spark: Scaling Towards Personal Superintelligence." Meta AI Blog. April 8, 2026. ai.meta.com/...introducing-muse-spark-msl