Mercor vs Scale AI: which is the better training data provider in 2026?
Answer in brief: Mercor is the better buy for labs that want professional-grade post-training data and evals: 5M+ experts by its own count, a licensable catalog of more than 50,000 tasks, and benchmarks built with Harvey, Cognition and Sierra. Scale AI is the better buy for programs that span LLM, image, video and LiDAR data, need SOC 2, ISO 27001 or FedRAMP coverage, or want SEAL evaluations. Scale's Meta ownership tie is a diligence item for rival labs.
Top pick for expert LLM data: Mercor. Senior professionals, published partner benchmarks and same-day dataset samples.
Independent research from vendor sites and current reporting. We did not test these services. Methodology.
Mercor vs Scale AI at a glance
| Factor | Mercor | Scale AI |
|---|---|---|
| Core model | Expert marketplace: data, evals, RL environments | Data Engine plus AI applications for enterprise and government |
| Workforce claim | 5M+ experts; $90/hr average contracted rate | 25% of contributors hold advanced degrees |
| Modalities | Text, code, agentic and multimodal tasks; robotics offering | Text, image, video, 3D sensor fusion (LiDAR); 150,000+ hours of physical-AI data in 2025 |
| Benchmarks | APEX family, Harvey LAB, τ³-Banking, Physical-Engineering's Last Exam | SEAL leaderboards, including Humanity's Last Exam, SWE-Bench Pro and MCP Atlas |
| Off-the-shelf data | Yes: 50K+ tasks, 30+ domains | Not featured |
| Security claims | Trust center at trust.mercor.com | SOC 2, ISO 27001, FedRAMP |
| Ownership note | Independent; $10B valuation reported in October 2025 | Meta minority stake since June 2025; Scale says it is independent |
| Pricing | Custom quote | Demo-led contracts |
Where Mercor wins: real professional work as training signal
Mercor builds data around the jobs labs want models to do. Harvey LAB has 1,749 attorney-built legal tasks graded on finished work products. APEX-SWE, built with Cognition, measures real software engineering. APEX-Agents runs 2,620 expert tasks inside enterprise app clones. Mercor licenses this kind of data off the shelf, sends samples the same day and says it can start sourcing new custom datasets within days of a request. For a lab that needs to fix professional-domain failure modes, that is hard to beat.
Where Scale AI wins: breadth, physical AI and compliance
Scale's Data Engine annotates text, imagery (including infrared), full-motion video and LiDAR. Its 2026 update reports more than 150,000 hours of physical-AI data delivered and 10 new robotics customers in 2025. It lists SOC 2, ISO 27001 and FedRAMP, along with large U.S. government contracts. If your lab trains multimodal or embodied models under strict security review, Scale covers ground Mercor does not lead with.
Evaluation heritage: APEX vs SEAL
Both companies sell evaluation credibility as part of the data relationship, but at different scales and with different emphases. Scale's SEAL team says it introduced 15 new benchmarks in 2025 and published more than 450 evaluations across 50+ models as labs launched new releases. That makes it a reference point for launch-day comparisons.
Mercor's evaluation work is narrower and deeper in the professions. Its leaderboards grade agents on accounting tasks across spreadsheets and PDFs, on legal memos and redlines, on engineering project folders a licensed reviewer would sign off on, and on fintech support tasks spanning 700 interconnected policy documents. Its enterprise evals page describes one coding suite of 200 expert-built tasks that became reusable in five weeks (a company figure). If your eval gap is general capability tracking, Scale fits. If it is professional work quality, Mercor fits.
The Meta question
Meta's June 2025 investment gave it a large minority stake in Scale, and founder Alexandr Wang moved to Meta while staying on as Scale's chairman. TechCrunch reported that OpenAI ended its work with Scale. Scale says customer data stays isolated and that Meta gets the same restrictions as any other customer. Labs that compete with Meta should put data segregation commitments into the contract.
Choose Mercor when…
- Your gaps are in law, finance, accounting, medicine, consulting or software engineering.
- You want to start training in days from licensed datasets.
- You want benchmarks built on real professional deliverables.
Choose Scale AI when…
- You need LiDAR, video or sensor-fusion labels alongside LLM data.
- FedRAMP or government work is in scope.
- You want one large supplier for data, evaluation and deployment.
Pricing model
Neither publishes buyer prices. Mercor is quoted per engagement, and its experts' average contracted rate ($90/hr) gives you a floor for estimating costs. Scale is sold through demos and custom contracts. See pricing models compared.
FAQ
Is Mercor replacing Scale AI at frontier labs?
Public reporting shows labs shifted work after Meta's 2025 investment in Scale, and Mercor raised at a $10B valuation that October. Contract-level details are private, so treat market-share claims with caution.
Which has better security credentials?
Scale publicly lists SOC 2, ISO 27001 and FedRAMP. Mercor runs a trust center at trust.mercor.com. Request current reports from both.
Can Mercor handle robotics data?
Mercor lists a robotics offering. Scale reports a larger public track record in physical AI, including 150,000+ hours of data delivered in 2025.
Keep comparing
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Reviews: Mercor review · Scale AI review. See the full ranking, alternatives to Scale AI and Surge AI vs Scale AI. For embodied-AI suppliers, see Best robotics data providers.
Sources
- Mercor home page
- Mercor off-the-shelf data
- Mercor enterprise evals
- CNBC on Mercor's funding
- Scale AI home page
- Scale Data Engine
- Scale: Building for 2026
- Scale on Meta's investment
- TechCrunch: OpenAI drops Scale AI
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