On April 8, 2026, Mark Zuckerberg announced that Meta had spent $14.3 billion, hired a 29-year-old to run a new division called Meta Superintelligence Labs, and spent nine months rebuilding the company's entire AI infrastructure from scratch — the architecture, the training pipeline, the data curation, all of it. The result is a model called Muse Spark. It is completely free. It ranks 4th in the world on the most comprehensive independent AI benchmark available. And within the next few weeks, it will be the AI model running inside Facebook, Instagram, and Messenger — apps that over 180 million Americans use every single month. Source: Meta official blog, April 8, 2026; CNBC, April 8, 2026.
The question that every American who pays $20 a month for ChatGPT Plus or Claude Pro is now asking is obvious: does free actually mean anything when it scores 4th in the world? The short answer is yes, in specific areas, and no in others. The long answer is this article — every benchmark, every honest weakness, every privacy consideration you should know before deciding whether Muse Spark changes your AI workflow.
This is not a press release. Meta has been caught overstating benchmark results before — most notably with Llama 4, the model released in April 2025 that was widely criticized for benchmarks that did not reflect real-world performance. We are using third-party independent benchmark data from Artificial Analysis, not Meta's self-reported numbers, wherever it differs. Where we cite Meta's own data, we say so. The picture that emerges is more nuanced and more interesting than the headlines suggest.
The $14.3 Billion Comeback: How We Got Here
To understand what Muse Spark is, you need to understand how completely Meta failed the last time it tried to compete at the AI frontier. In April 2025, Meta released the Llama 4 family of models — Scout and Maverick — with a blizzard of benchmark claims that placed them among the world's best AI systems. Independent researchers found within days that the benchmark versions of the models were meaningfully different from the versions available to actual users. Meta was publicly accused of benchmark manipulation. The developer community, which had been genuinely enthusiastic about Meta's previous open-source AI work, turned sharply negative. Llama 4's reception was, in the words of multiple reviewers, 'a dud.' Source: Fortune, April 8, 2026; VentureBeat, April 8, 2026.
Mark Zuckerberg's response was to invest $14.3 billion for a 49% stake in Scale AI and bring its 29-year-old co-founder and CEO, Alexandr Wang, to Meta as Chief AI Officer to lead a newly formed division called Meta Superintelligence Labs. This was not a hiring announcement. It was a statement of intent: Meta was going to rebuild its AI from the ground up with a person whose entire career was built on the data infrastructure that makes frontier AI possible. Wang's mandate was complete and explicit — new infrastructure, new architecture, new data pipelines, built from scratch, faster than any previous development cycle. That nine-month rebuild produced Muse Spark. Source: CNBC, April 8, 2026; VentureBeat, April 8, 2026.
The model's internal codename was 'Avocado.' It is the first model in what Meta is calling the Muse series — a naming convention that signals a deliberate and scientific approach where each generation validates and builds on the last before scaling up. Meta has been explicit that Muse Spark is not a claim to state-of-the-art status. Wang himself said as much when announcing it: it is step one, not the destination. Bigger models are already in development. The question for Americans today is whether step one is good enough to matter. Source: Meta official blog, April 8, 2026; Axios, April 8, 2026.
The Benchmarks: What the Independent Numbers Actually Say
All benchmark data in this section comes from the Artificial Analysis Intelligence Index v4.0, the most comprehensive independent third-party model ranking available, unless otherwise noted. We are using this specifically because Meta has a documented history of selective benchmark reporting. Where Meta's own numbers differ from independent evaluation, we note it. The independent picture is, in most cases, still highly favorable to Muse Spark — just not as dramatically favorable as Meta's press release implies.
The headline number: Muse Spark scores 52 on the Artificial Analysis Intelligence Index v4.0, placing it 4th globally behind Gemini 3.1 Pro (57), GPT-5.4 (57), and Claude Opus 4.6 (53). To put that in context — Llama 4 Maverick and Llama 4 Scout, Meta's previous models, scored 18 and 13 respectively on the same index. Muse Spark is not a marginal improvement over its predecessor. It nearly tripled Llama 4 Maverick's score on an independent benchmark. That is the most important number in this entire review. Source: Artificial Analysis, April 2026.
| Benchmark | Muse Spark | GPT-5.4 | Gemini 3.1 Pro | Claude Opus 4.6 |
|---|---|---|---|---|
| Intelligence Index Overall (Artificial Analysis) | 52 | 57 | 57 | 53 |
| HealthBench Hard (medical AI) | 42.8 | 40.1 | 20.6 | 14.8 |
| CharXiv Reasoning (figure understanding) | 86.4 | 82.8 | 80.2 | 65.3 |
| MMMU Pro (vision reasoning) | 80.5 | ~78 | 82.4 | — |
| SimpleVQA (visual factuality) | 71.3 | 61.1 | 72.4 | — |
| GPQA Diamond (PhD-level reasoning) | 89.5% | 92.8% | 94.3% | 92.7% |
| SWE-bench Verified (real coding)** | 77.4 | ~84 | 80.6 | 80.8 |
| Terminal-Bench 2.0 (coding/tools) | 59.0 | 75.1 | 68.5 | — |
| ARC-AGI-2 (abstract reasoning)* | 42.5 | 76.1 | 76.5 | — |
| HLE Contemplating mode (Meta claim, with tools) | 50.2%* | — | — | — |
| Token efficiency (eval cost) | 58M tokens | 120M tokens | 58M tokens | 157M tokens |
Note on benchmark sources: Overall Intelligence Index scores are from Artificial Analysis v4.0 (independent, third-party). ARC-AGI-2 (*) and SWE-bench Verified (**) scores are sourced from Meta AI technical blog, April 8, 2026 — they are not part of the Artificial Analysis Intelligence Index composite. HealthBench Hard, CharXiv, MMMU Pro, SimpleVQA, GPQA Diamond, and Terminal-Bench scores are from Artificial Analysis model-specific evaluations outside the Index composite, April 2026.
Three numbers in that table deserve individual attention. First: HealthBench Hard at 42.8. Meta worked with over 1,000 physicians to curate the training data specifically for health and medical reasoning. The result is a model that scores more than double what Gemini 3.1 Pro achieves on this benchmark (20.6) and ahead of GPT-5.4 (40.1). Claude Opus 4.6 scores 14.8. For Americans who use AI to understand medical information, research symptoms, or navigate the healthcare system — and given US healthcare costs and complexity, this is a significant share of AI users — Muse Spark is the strongest free tool available, and arguably the strongest tool period. Source: Meta official benchmarks, April 8, 2026; Artificial Analysis, April 2026.
Second: ARC-AGI-2 at 42.5. This benchmark tests abstract pattern recognition and novel problem-solving — the ability to identify visual patterns the model has never seen before and generalize from minimal examples. Muse Spark scores 42.5. GPT-5.4 scores 76.1. Gemini 3.1 Pro scores 76.5. That is not a close race. It is a meaningful structural gap that suggests Muse Spark's architecture handles out-of-distribution reasoning less effectively than the leading models. For most everyday use cases this will not matter. For research, novel problem-solving, and tasks that require genuine creative abstraction, this gap is real. Note: ARC-AGI-2 is not part of the Artificial Analysis Intelligence Index — these scores are sourced from Meta AI technical blog, April 8, 2026, and independent ARC Prize tracking.
Third: token efficiency. Muse Spark completed the full Intelligence Index evaluation using just 58 million output tokens — comparable to Gemini 3.1 Pro (57M) and far below Claude Opus 4.6 (157M) and GPT-5.4 (120M). This is not just a technical footnote. It means Muse Spark responds faster and at lower computational cost per query. For individual users, it translates to faster responses in practice. Source: Artificial Analysis, April 2026.
The Price: Why Free Changes the Equation for Americans
Muse Spark is completely free through meta.ai and the Meta AI app. There is no paid tier, no usage limit announced, and no premium version for power users — at least as of April 10, 2026. ChatGPT Plus, which gives you access to GPT-5.4, costs $20 per month. Claude Pro, which gives you access to Claude Opus 4.6, also costs $20 per month. Gemini Advanced, Google's premium tier, costs $19.99 per month. Source: Official pricing pages, April 2026.
Put differently: the 4th-ranked AI model in the world is now available to every American for zero dollars. The top three models cost $240 a year each. That price gap alone will drive significant adoption among students, small business owners, and anyone who has been hesitant to pay a monthly subscription for AI access. Whether Muse Spark's specific strengths — health questions, visual reasoning, general conversation — match what those users actually need is a different question. But the price is the first answer to whether Muse Spark matters, and the price is zero.
Pro Tip: How to access Muse Spark right now: Go to meta.ai or download the Meta AI app. You will need a Facebook or Instagram account to log in. The model currently runs in Instant mode (fast, general queries) and Thinking mode (deeper reasoning). A third mode called Contemplating — which uses multiple AI agents working in parallel on complex problems — is rolling out in the coming weeks. Meta claims this mode scored 50.2% on Humanity's Last Exam with tools enabled, beating both GPT-5.4 Pro and Gemini Deep Think. Important caveat: Artificial Analysis's independent evaluation measured Muse Spark at 39.9% on HLE in standard single-agent mode — the gap likely reflects the multi-agent Contemplating setup versus standard evaluation conditions, but it is a gap worth knowing before taking Meta's number at face value. Source: Meta official blog, April 8, 2026; Artificial Analysis, April 2026.
What Muse Spark Is Actually Good At — Five Real Use Cases
The benchmarks tell you where Muse Spark leads statistically. This section translates that into the five situations where choosing Muse Spark is genuinely the correct decision for an American user in April 2026. These are not marketing claims. They are derived directly from the independent benchmark data and the structural characteristics of how Meta built the model.
- Health and medical questions: This is Muse Spark's clearest lead. HealthBench Hard at 42.8 is not a marginal win — it is a category-defining result, achieved in part because Meta explicitly trained the model with input from over 1,000 physicians. If you are researching a diagnosis, understanding a medication interaction, preparing for a doctor's appointment, or trying to parse a medical bill or insurance explanation of benefits, Muse Spark is the strongest AI tool available for this specific use case — for free. Source: Meta official benchmarks, April 8, 2026.
- Visual analysis and chart reading: CharXiv Reasoning at 86.4 places Muse Spark ahead of every competitor on figure understanding. If you need an AI to read a chart, interpret an infographic, extract data from a photo of a document, or analyze a visual, Muse Spark is the strongest free option available. The CharXiv benchmark specifically tests AI's ability to understand and reason about the kind of charts found in academic papers and financial reports. Source: Artificial Analysis Intelligence Index v4.0, April 2026.
- General conversation and everyday questions: The Instant mode is designed specifically for this, and the token efficiency means responses come back fast. For the tasks that make up the majority of AI usage — drafting an email, summarizing a document, answering a factual question, planning a trip — Muse Spark's 52 overall score represents genuinely capable performance. It is not a toy. It is a fourth-ranked global model being used for daily tasks for zero dollars.
- Shopping research and product comparisons: Meta has specifically built what it calls a 'shopping mode' that combines language model capability with data on user interests across Instagram and Facebook. For Americans researching a purchase, comparing product options, or looking for recommendations, this integration with social product data is a feature no competitor has. It will expand as the model rolls out across Meta's platforms. Source: Axios, April 8, 2026.
- Ray-Ban Meta AI glasses users: Muse Spark will power the AI in Meta's Ray-Ban smart glasses, giving the glasses a dramatically more capable model than the previous AI running on them. For Americans who have adopted the Ray-Ban Meta AI glasses for hands-free AI access, this is a significant upgrade with no additional cost. Source: Meta official blog, April 8, 2026.
Where Muse Spark Fails — The Honest Assessment
The benchmarks are clear and the honest framing requires covering these gaps as directly as the strengths. Three areas where Muse Spark lags meaningfully behind the competition are worth understanding before you change any workflow that depends on them.
Coding is the clearest weakness. SWE-bench Verified at 77.4 versus Claude Opus 4.6's 80.8 and GPT-5.4's approximate 84% is a gap that matters in practice. Terminal-Bench 2.0 at 59.0 versus GPT-5.4's 75.1 and Gemini's 68.5 is a larger gap. Meta's own blog explicitly acknowledges this: the company says it 'continues to invest in areas with current performance gaps, specifically long-horizon agentic systems and coding workflows.' If you use AI for software development, debugging, or complex code generation, Muse Spark is not the right choice today. Claude Opus 4.6 for complex coding and GPT-5.4 for agentic workflows remain the standards. Note: SWE-bench and Terminal-Bench are not part of the Artificial Analysis Intelligence Index — these scores are sourced from Meta AI technical blog, April 8, 2026; Artificial Analysis model-specific testing outside the Index composite.
Abstract reasoning is the second gap. ARC-AGI-2 at 42.5 versus GPT-5.4's 76.1 and Gemini 3.1 Pro's 76.5 represents a fundamental difference in out-of-distribution problem-solving capability. For novel tasks, creative problem-solving, and anything requiring the model to generalize from patterns it has not seen before, the gap is substantial. Most everyday users will not encounter this limitation. Researchers, scientists, and anyone using AI for genuinely novel analytical work will. Source: Artificial Analysis Intelligence Index v4.0, April 2026.
The privacy question is the third concern — and it is one that matters specifically to Americans in 2026. To use Muse Spark through meta.ai, you must log in with a Facebook or Instagram account. That means your AI queries are associated with your Meta profile — the same profile that Meta uses for behavioral advertising across Facebook, Instagram, Messenger, and its advertising network. Meta's ad-targeting machine will know what you ask your AI assistant. The company has said it uses prompts and interactions to improve model quality and has a data policy covering AI data, but the commercial incentive to connect AI behavior data to advertising profiles is substantial. No other major frontier AI model requires a social media login. This is a real consideration, not a theoretical one. Source: Fortune, April 8, 2026; Meta terms of service.
The Privacy Question Every American Should Think About
Meta's approach to AI privacy is structurally different from every other major AI provider. ChatGPT, Claude, and Gemini can all be used with a standalone account that has no connection to a social media profile. Muse Spark cannot — at least not in its current consumer-facing form. The API preview that will eventually be available to developers may change this, but as of April 10, 2026, every conversation you have with Muse Spark is associated with your Facebook or Instagram identity.
This matters because Meta's business model is built on behavioral advertising. The company generated approximately $195 billion in advertising revenue in 2025, the overwhelming majority of which came from targeting ads to users based on their behavior across Meta's platforms. Source: Meta Q4 2025 earnings, January 28, 2026. There is a reasonable concern that AI query data — what you ask, what health symptoms you describe, what products you consider, what financial questions you have — represents behavioral signal that Meta has an incentive to incorporate into its advertising model, even if the current policy does not explicitly permit this use. Asking an AI about a medical symptom is different from clicking on a health article. The specificity and intimacy of AI queries is significantly higher than passive browsing behavior.
The counterargument is straightforward: Meta has a data policy and is subject to US privacy law, including FTC oversight and sector-specific rules for health data. The company says it uses conversations to improve models and does not sell data to third parties. This is also true of OpenAI and Anthropic. But the integration of AI query data with one of the world's largest behavioral advertising profiles is a meaningful structural difference from alternatives. For queries about health, finances, legal questions, or anything you would not want associated with your Facebook identity, using a model that does not require a social media login is the more conservative choice. Source: Meta privacy policy, April 2026.
What It Means When Muse Spark Comes to Facebook and Instagram
Within the next few weeks, Muse Spark will be the model powering Meta AI inside Facebook, Instagram, Messenger, and WhatsApp. Facebook has approximately 180 million monthly active users in the United States. Instagram has approximately 143 million US monthly users. Most of those users have never deliberately chosen an AI assistant and will not be given a choice about which one appears in their feed — Muse Spark will simply be there. Source: Statista, 2025 US social media usage data; Meta official blog, April 8, 2026.
The practical consequence is that Muse Spark may become the most widely used AI model in America not because people chose it, but because 180 million people already use Facebook monthly. This is Meta's core competitive advantage — its distribution network is larger than any AI company's user base by an order of magnitude. The rollout to Meta's platforms is not just a product update. It is the largest single AI deployment event in history by raw reach. Source: Meta earnings reports; OpenAI usage statistics, March 2026.
What changes for Facebook users: the AI chat experience across Meta's apps will become meaningfully more capable. The previous Meta AI running inside Instagram and Messenger was powered by Llama 4 — a model that ranked 18 on the same intelligence index where Muse Spark ranks 52. Users who found the previous Meta AI frustratingly limited will find Muse Spark a substantial improvement on health questions, visual tasks, and general conversation quality. Users who are comparing it to ChatGPT Plus or Claude Pro should expect broadly competitive performance on most everyday tasks — with the specific strengths and weaknesses outlined in this article.
Why Developers Are Frustrated: Open Source Is Delayed, Not Dead
For three years, Meta was the most important company in open-source AI. The Llama model family — Llama 2, Llama 3, Llama 4 — was released with open weights, meaning any developer could download the model, run it locally, fine-tune it on their own data, and deploy it without paying Meta anything. This was genuinely transformational. The Llama ecosystem reached 1.2 billion downloads by early 2026, with approximately one million downloads per day. An 88% cost reduction compared to proprietary API providers made Llama a default choice for startups, researchers, and enterprises that wanted AI capability without vendor lock-in. Source: VentureBeat, April 8, 2026.
Muse Spark is launching as a closed proprietary model — accessible only through Meta's own products and, eventually, a private API. This is a departure from the Llama playbook and developer frustration is real. However, the open-source door has not been closed. Axios reported that Meta plans to release a version of Muse Spark under an open-source license. Wang's statement on X was direct: 'Nine months ago we rebuilt our AI stack from scratch... plans to open-source future versions.' Zuckerberg separately wrote on Threads that Meta plans to release 'new open source models' going forward. Multiple sources also report Meta is actively developing open-weight versions of upcoming models in parallel. The accurate read is that open-source is delayed for this first model — not abandoned. Source: Axios, April 8, 2026; Alexandr Wang on X, April 8, 2026; VentureBeat, April 8, 2026.
The practical consequence today: developers who built workflows on Llama — who valued the ability to run models locally, avoid data leaving their infrastructure, and operate without per-query costs — cannot do any of that with Muse Spark right now. For the enterprise customers, researchers, and startups who adopted Meta precisely because of its open-source stance, this launch represents a temporary reversal of the value proposition that built Meta's developer community. Meta's signaled intention to open-source future versions is some reassurance, but there is no timeline attached to that commitment. This will not affect most consumers. It is a significant and still-unresolved development for anyone who made technical decisions based on Llama's openness. Source: VentureBeat, April 8, 2026; Axios, April 8, 2026.
The Practical Decision: Should You Change Your AI Stack?
The honest answer depends on what you actually use AI for. The following matrix is derived directly from the benchmark data. It is not a promotional guide for Muse Spark — it is a routing guide based on where each model genuinely leads as of April 10, 2026.
| Use Case | Best Free Choice | Best Paid Choice | Why |
|---|---|---|---|
| Health / medical questions | Muse Spark | Muse Spark (still free) | HealthBench Hard 42.8 — highest of any frontier model |
| Reading charts, figures, images | Muse Spark | Gemini 3.1 Pro | CharXiv 86.4 — beats GPT-5.4 and Gemini on figure understanding |
| Writing / editing / emails | Muse Spark or Gemini Free | Claude Sonnet 4.6 | All models competitive here; Sonnet has strong writing quality |
| Complex software development | Gemini 3.1 Pro (free tier) | Claude Opus 4.6 ($20/mo) | SWE-bench: Claude 80.8, GPT ~84, Muse Spark 77.4 |
| Autonomous AI agents / tasks | Gemini 3.1 Pro (free tier) | ChatGPT GPT-5.4 ($20/mo) | Agentic capability is Muse Spark's explicitly stated weak area |
| Abstract reasoning / research | Gemini 3.1 Pro (free tier) | GPT-5.4 or Gemini 3.1 Pro | ARC-AGI-2: Muse Spark 42.5 vs GPT 76.1 and Gemini 76.5 |
| Everyday questions / chat | Muse Spark | Any of the above | 4th-ranked global model; fast responses; zero cost |
| Product research / shopping | Muse Spark | Muse Spark (social data integration) | Shopping mode uses Meta social data — unique advantage |
The bottom line for the average American paying $20 a month for ChatGPT or Claude: Muse Spark is not a replacement today if you use those subscriptions primarily for coding, agentic tasks, or complex reasoning. It is a genuine replacement for health questions, visual analysis, and everyday conversation — and it is free. The most rational approach for most users is to add Muse Spark to your toolkit rather than swap it in wholesale, and to use it specifically where its benchmark data says it leads. Source: Artificial Analysis Intelligence Index v4.0, April 2026.
The broader observation is worth stating clearly. The 4th-ranked AI model in the world is now free and will be distributed to hundreds of millions of Americans through apps they already use. Twelve months ago, access to frontier AI required a credit card. That is no longer true. The democratization argument is real — and the competitive pressure on OpenAI and Anthropic to justify $20-a-month subscriptions with capability that free models cannot match is going to intensify significantly in Q2 and Q3 2026.
Frequently Asked Questions
Is Muse Spark actually free? Is there a catch?
Yes, it is free. The catch is that you need a Facebook or Instagram account to access it through meta.ai or the Meta AI app. Meta's business model does not require you to pay for AI access because its revenue comes from advertising, not subscriptions. The practical implication is that your queries are associated with your Meta identity and subject to Meta's data policy — which is a privacy consideration worth weighing. There is no announced paid tier or usage limit as of April 10, 2026. Source: Meta official blog, April 8, 2026.
How does Muse Spark compare to ChatGPT and Claude right now?
On overall capability (Artificial Analysis Intelligence Index v4.0): Muse Spark scores 52, Claude Opus 4.6 scores 53, GPT-5.4 scores 57, Gemini 3.1 Pro scores 57. Muse Spark beats GPT-5.4 on HealthBench Hard (42.8 vs 40.1), figure understanding, and visual factuality. GPT-5.4 and Claude Opus 4.6 beat Muse Spark on coding (SWE-bench), abstract reasoning (ARC-AGI-2), and agentic tasks. For most everyday use cases, the gap between these models in practice is smaller than the benchmark numbers suggest. Source: Artificial Analysis Intelligence Index v4.0, April 2026.
When will Muse Spark be available on Facebook, Instagram, and Messenger?
Meta said 'in the coming weeks' from the April 8 launch date — meaning Muse Spark should begin appearing in Facebook, Instagram, Messenger, and WhatsApp by late April to mid-May 2026. The rollout starts in the US. The Meta AI app and meta.ai already have Muse Spark running as of April 8. Ray-Ban Meta AI glasses are also in the rollout queue. Source: Meta official blog, April 8, 2026.
Is Muse Spark open source like Llama was?
Not at launch. Muse Spark is launching as a closed proprietary model — the first Meta AI model that is not open weights. However, Axios reported that Meta plans to release a version of Muse Spark under an open-source license, and Wang's statement on X confirmed 'plans to open-source future versions.' Zuckerberg also wrote that Meta plans to release new open source models going forward. There is no announced timeline for the open-source release, and the API is currently in private preview for select partners only. Developers who built on Llama and valued the ability to self-host, fine-tune, and deploy locally cannot do those things with Muse Spark today — but the open-source door has not been closed. Source: Axios, April 8, 2026; Alexandr Wang on X, April 8, 2026; VentureBeat, April 8, 2026.
What is the Contemplating mode Meta mentioned?
Contemplating mode is a multi-agent reasoning approach where Muse Spark runs multiple AI agents in parallel, each working on the same problem from different angles, then synthesizes their outputs. Meta claims this mode scored 50.2% on Humanity's Last Exam with tools enabled — beating both GPT-5.4 Pro and Gemini Deep Think on that benchmark. However, Artificial Analysis's independent evaluation measured 39.9% on HLE in standard single-agent conditions, so the 50.2% figure reflects the multi-agent setup rather than a like-for-like comparison. Contemplating mode is rolling out gradually in the coming weeks. Source: Meta official blog, April 8, 2026; Artificial Analysis, April 2026.
Should I cancel my ChatGPT Plus or Claude Pro subscription?
Not yet, unless your primary use cases are health questions and visual analysis. If you use your AI subscription primarily for coding, complex reasoning, agentic tasks, or software development, the models behind those subscriptions (Claude Opus 4.6 and GPT-5.4) still lead Muse Spark meaningfully on those benchmarks. If you use AI primarily for everyday conversation, document summarization, and health-related questions, Muse Spark is a genuine free alternative. The most cost-effective approach for most users is to add Muse Spark via meta.ai and use it where it leads, while keeping a paid subscription for the specific capabilities it does not yet match. Source: Artificial Analysis Intelligence Index v4.0, April 2026.
Pro Tip: The single best first test for Muse Spark: ask it a health question you have actually wondered about — a symptom, a medication interaction, or a question about a specific condition. HealthBench Hard at 42.8 is not an abstract benchmark number. It was built with input from over 1,000 physicians specifically to measure how useful an AI model is for real medical questions. This is where Muse Spark has the clearest, most verified lead over every paid alternative. Source: Meta official blog, April 8, 2026.