# Manus vs Scale

Manus records 19,195,779 monthly visits with -1.7% month-over-month growth and Free Trial pricing. Scale records 616,915 monthly visits with +12.5% growth and Contact for Pricing pricing.

| Metric | [Manus](https://openaitools.app/tool/manus) | [Scale](https://openaitools.app/tool/scale) |
| :--- | :--- | :--- |
| Website URL | https://manus.im | https://scale.com |
| Categories | AI Assistant, AI Agent, AI Copilot | AI Developer Tools, Large Language Models (LLMs), AI Models, AI Agent |
| Pricing Model | Free Trial | Contact for Pricing |
| Monthly Visits | 19,195,779 | 616,915 |
| MoM Growth Rate | -1.7% | +12.5% |
| Primary Market | Brazil | United States |
| Direct Visits | 10,563,180 | 191,408 |
| Review Score | 4.6 | 4.7 |
| Saved Count | 10 | 3 |
| Supported Platforms | Website | Website |

## Manus

Manus positions itself as an "action engine" rather than a chatbot. You describe an outcome, and the agent breaks it into steps, decides which tools to use, browses the web when it needs current information, and assembles the final deliverable in a cloud sandbox. Typical outputs include presentation decks, working websites and small games, generated images and video, and long-form research reports assembled through its Wide Research workflow.

The product ships as a mobile app (iOS and Android), a desktop app, and a browser extension, plus a web console with an API for programmatic use. A Slack integration lets teams dispatch tasks from chat, and workspace features such as team plans and SSO make it viable inside organizations rather than only for individuals. Because the agent runs asynchronously, a common pattern is to queue a task, walk away, and review the result later.

Pricing combines a free trial-style entry point with paid subscription tiers and a business plan; exact credit allowances and seats change over time, so confirm current terms on the official pricing page. The obvious trade-off is control: autonomous agents can misread intent or burn credits on the wrong approach, so clear briefs and intermediate review matter.

**Pricing & Plans:** Free trial available, with paid subscription tiers and a business plan for teams and higher usage. Credit allowances and seat details change, so check the official pricing page.

- **Autonomous task execution:** Give the agent a goal and it plans the steps, chooses tools, and works through the task in a cloud environment without constant supervision.
- **Deliverable generation:** Produces finished artifacts such as slide decks, functional websites, small games, and formatted documents rather than raw text.
- **Wide Research:** Runs broad, multi-source investigations and compiles the findings into a structured report.
- **Media creation:** Generates images, video, and music as part of a larger task or as standalone outputs.
- **Integrations and API:** Connects to Slack for task dispatch, offers mobile and desktop apps, and exposes an API for embedding agent work in your own stack.

**Strengths:** Delivers finished artifacts instead of only conversational answers; Works across web, mobile, desktop, Slack, and API surfaces; Wide Research handles broad multi-source investigations well; Team plans and SSO make it usable in organizational settings

**Limitations:** Autonomous runs consume credits and can pursue the wrong approach if the brief is vague; Complex tasks benefit from human review at checkpoints; Output quality varies by task type, especially outside common formats

[Profile (Markdown)](https://openaitools.app/tool/manus.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 Manus and Scale compare in monthly traffic?

Manus has 19,195,779 monthly visits, while Scale has 616,915. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Manus has a month-over-month growth rate of -1.7%; Scale has +12.5%.

### How does pricing compare?

Manus: Free Trial. Free trial available, with paid subscription tiers and a business plan for teams and higher usage. Credit allowances and seat details change, so check the official pricing page. 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 | [ChatGPT](https://openaitools.app/tool/chatgpt-4) | 6,048,022,723 | +2.2% | Freemium | Provides powerful reasoning agents and deep research, but lacks Manus's specialized continuous cloud workspace execution. | [.md](https://openaitools.app/tool/chatgpt-4.md) |
| 2 | [Claude](https://openaitools.app/tool/claude-2) | 1,253,439,413 | +23.8% | Freemium | Features advanced computer use and interactive artifacts, but operates primarily as a chat assistant rather than a dedicated autonomous agent platform. | [.md](https://openaitools.app/tool/claude-2.md) |
| 3 | [Muse](https://openaitools.app/tool/muse-ai-1) | 45,751,822 | +228.3% | Contact for Pricing | Executes tasks using cloud virtual Linux machines, but focuses more on personal desktop automation than complex multi-app research. | [.md](https://openaitools.app/tool/muse-ai-1.md) |
| 4 | [Hermes-Agent](https://openaitools.app/tool/hermes-agent-1) | 3,638,741 | -5.4% | Freemium | Provides open-source personal task automation, but lacks the polished cloud sandbox environment of Manus. | [.md](https://openaitools.app/tool/hermes-agent-1.md) |
| 5 | [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) |
| 6 | [Runable](https://openaitools.app/tool/runable) | 1,048,370 | -1.9% | Freemium | Automates multi-step workflows and asset creation, but with fewer built-in general browser navigation tools. | [.md](https://openaitools.app/tool/runable.md) |
| 7 | [Skywork.ai](https://openaitools.app/tool/skywork-ai) | 1,021,069 | -11.8% | Freemium | Converts prompts into structured office deliverables, but acts primarily as a document generation workspace. | [.md](https://openaitools.app/tool/skywork-ai.md) |
| 8 | [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) |
| 9 | [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) |
| 10 | [LibreChat](https://openaitools.app/tool/librechat) | 346,879 | -3.5% | Free | Unites multiple models and custom agents in a self-hosted workspace, but lacks pre-built autonomous execution sandboxes. | [.md](https://openaitools.app/tool/librechat.md) |

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Source: https://openaitools.app/compare/manus-vs-scale

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