# Mercor vs Scale

Mercor records 14,164,192 monthly visits with +34% month-over-month growth and Contact for Pricing pricing. Scale records 616,915 monthly visits with +12.5% growth and Contact for Pricing pricing.

| Metric | [Mercor](https://openaitools.app/tool/mercor-com) | [Scale](https://openaitools.app/tool/scale) |
| :--- | :--- | :--- |
| Website URL | https://mercor.com | https://scale.com |
| Categories | AI Recruiting, AI Jobs, AI Interview Assistant, AI Resume Checker | AI Developer Tools, Large Language Models (LLMs), AI Models, AI Agent |
| Pricing Model | Contact for Pricing | Contact for Pricing |
| Monthly Visits | 14,164,192 | 616,915 |
| MoM Growth Rate | +34% | +12.5% |
| Primary Market | United States | United States |
| Direct Visits | 7,518,232 | 191,408 |
| Review Score | 4.4 | 4.7 |
| Saved Count | 3 | 3 |
| Supported Platforms | Website | Website |

## Mercor

Mercor started as an AI recruiting marketplace that used machine learning to match candidates with remote jobs faster than traditional hiring. The platform interviews and vets applicants automatically, then routes matched professionals to short-term and long-term engagements that range from software and data work to specialist expert tasks.

Over time Mercor expanded well beyond recruiting. It now positions itself around "organizing human intelligence to power the AI economy," running interfaces for frontier research, AI benchmarks and AI-agent training at scale. Its enterprise arm builds industry benchmarks with partner organizations, sells human evaluation capacity to frontier labs, and lets businesses turn their own workflow data into a new revenue stream through anonymized licensing.

Mercor reports hundreds of thousands of roles created, an average contracted expert rate around $90 per hour and millions in daily payouts. It has raised significant venture funding and works with leading AI labs and large enterprises, serving both experts looking for flexible paid work and companies that need human data, evaluations or AI-ready talent.

**Pricing & Plans:** Free to sign up for experts; Mercor takes no fee from talent. Enterprises and AI labs pay custom, quote-based rates for data, benchmarking and evaluation services — contact sales for details.

- **AI-powered talent matching:** Machine-learning models screen and match candidates to remote roles in hours rather than weeks, based on skills, experience and availability.
- **Automated expert vetting:** AI-driven interviews and assessments validate professional expertise before experts are surfaced to hiring partners.
- **Paid expert engagements:** Experts work on flexible, remote projects with rates reported to average around $90 per hour and fast, recurring payouts.
- **Industry benchmark building:** Mercor collaborates with enterprises to design benchmarks such as legal, accounting and software-engineering evaluations for AI agents.
- **Enterprise data monetization:** Businesses can license anonymized workflow data to Mercor, with automated masking of sensitive identifiers and full control over what is shared.

**Strengths:** Fast, AI-driven matching that shortens time-to-hire dramatically; High reported pay rates and quick, frequent payouts for experts; Broad scope beyond recruiting — benchmarks, evals and data monetization; Works with major AI labs and enterprises, signaling strong credibility

**Limitations:** Enterprise pricing is quote-only, so costs are not transparent upfront; Work is project-based and may be irregular for some experts; Availability depends on demand from AI labs and enterprise partners

[Profile (Markdown)](https://openaitools.app/tool/mercor-com.md)

## Scale

Scale positions itself as the infrastructure layer for reliable AI - the data, evaluations and deployment support that sit underneath working systems rather than a single consumer-facing model. Founded in 2016, it built its reputation supplying training data and labelling capacity to the autonomous vehicle and then the generative AI wave, and now describes itself as powering a large share of the world's leading generative AI model builders.

The offering spans three broad areas. Data covers sourcing and expert annotation for training and fine-tuning, including RLHF-style preference data. Evaluation covers public leaderboards and private benchmarks used to measure model capability and safety. Applications covers the build-and-deploy side: identifying a viable use case, constructing the system and owning the outcome, with agentic AI for enterprise operations.

Scale's customer list leans heavily enterprise and public sector, including large technology companies, healthcare providers, media organisations, energy companies and government defence programmes. Because engagements are scoped rather than self-serve, pricing is arranged through a sales process, and the platform is aimed at organisations with serious data volume, strict compliance needs and a mandate to put AI into production.

**Pricing & Plans:** Contact for pricing. Scale does not publish rates; engagements are scoped through a sales conversation and depend on data volume, services and programme complexity.

- **Data Engine:** Human-sourced and expert-annotated training data, including specialist contributors with advanced degrees, at the quality bar frontier labs require.
- **Model evaluation & benchmarks:** Public leaderboards plus private benchmarks that test model capability and safety for the most ambitious AI developers.
- **Enterprise AI applications:** Platform and services teams that pick the right use case, build the system and take ownership of the outcome.
- **Agentic deployment:** Agentic systems designed around measurable business outcomes across private equity portfolios, energy and healthcare operations.
- **Domain expertise:** Programmes spanning healthcare, robotics, defence, public sector and enterprise with human oversight built in.

**Strengths:** Backed by a long track record in training data and model evaluation.; End-to-end coverage from data sourcing through to deployed systems.; Experienced with regulated, classified and safety-critical environments.; Benchmarks and leaderboards give an independent view of model capability.

**Limitations:** No public pricing or self-serve signup - you need a sales conversation to get started.; Enterprise-scale contracting and data operations require real internal commitment.; Overkill for small teams with modest data or evaluation needs.; Some projects involve sensitive government and defence work with strict compliance overhead.

[Profile (Markdown)](https://openaitools.app/tool/scale.md)

## Frequently Asked Questions

### How do Mercor and Scale compare in monthly traffic?

Mercor has 14,164,192 monthly visits, while Scale has 616,915. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Mercor has a month-over-month growth rate of +34%; Scale has +12.5%.

### How does pricing compare?

Mercor: Contact for Pricing. Free to sign up for experts; Mercor takes no fee from talent. Enterprises and AI labs pay custom, quote-based rates for data, benchmarking and evaluation services — contact sales for details. Scale: Contact for Pricing. Contact for pricing. Scale does not publish rates; engagements are scoped through a sales conversation and depend on data volume, services and programme complexity.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Workable](https://openaitools.app/tool/workable) | 10,780,627 | +5.5% | Free Trial, Paid | Offers robust general HR and recruiting tools with native AI agents, but lacks Mercor's specialized expert network. | [.md](https://openaitools.app/tool/workable.md) |
| 2 | [Roboflow](https://openaitools.app/tool/roboflow) | 1,431,204 | +6.6% | Freemium, Contact for Pricing | Streamlines computer vision dataset annotation and model training, but is less suited for general LLM text tasks. | [.md](https://openaitools.app/tool/roboflow.md) |
| 3 | [Labelbox](https://openaitools.app/tool/labelbox) | 762,803 | -22.8% | Contact for Pricing | Focuses heavily on enterprise data labeling and training data curation, similar to Scale's core annotation business. | [.md](https://openaitools.app/tool/labelbox.md) |
| 4 | [HireAI: AI Recruiter by Arc](https://openaitools.app/tool/hireai-ai-recruiter-by-arc) | 496,923 | -2.2% | Paid | Sources software professionals through Arc's vetted remote-talent marketplace using AI candidate matching. | [.md](https://openaitools.app/tool/hireai-ai-recruiter-by-arc.md) |
| 5 | [SuperAnnotate](https://openaitools.app/tool/super-annotate) | 386,034 | +37.4% | Free Trial, Contact for Pricing | Provides enterprise multimodal annotation and data management tools, but with less emphasis on managed labeling workforces. | [.md](https://openaitools.app/tool/super-annotate.md) |
| 6 | [Weights & Biases (CoreWeave Forge)](https://openaitools.app/tool/prompts) | 315,624 | -80.2% | Freemium, Contact for Pricing, Free | Track, evaluate, and ship AI models and agents in one connected environment. | [.md](https://openaitools.app/tool/prompts.md) |
| 7 | [Arize AI](https://openaitools.app/tool/arize-com) | 249,028 | +3.2% | Paid, Contact for Pricing | Focuses on post-deployment LLM observability and evaluation rather than training data generation or annotation. | [.md](https://openaitools.app/tool/arize-com.md) |
| 8 | [Encord](https://openaitools.app/tool/encord-com) | 244,204 | +9.4% | Contact for Pricing | Specializes in data infrastructure and annotation specifically tailored for computer vision and physical AI workloads. | [.md](https://openaitools.app/tool/encord-com.md) |
| 9 | [Alex AI](https://openaitools.app/tool/alex-ai) | 235,876 | +49.3% | Contact for Pricing | Automates technical screening, video interviews, and candidate scheduling at enterprise scale. | [.md](https://openaitools.app/tool/alex-ai.md) |
| 10 | [Label Studio](https://openaitools.app/tool/label-studio) | 137,199 | -16.1% | Contact for Pricing, Free | Offers a flexible open-source alternative for custom data labeling and human-in-the-loop annotation pipelines. | [.md](https://openaitools.app/tool/label-studio.md) |

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Source: https://openaitools.app/compare/mercor-com-vs-scale

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