# Labelbox vs RunningHub

Labelbox records 762,803 monthly visits with -22.8% month-over-month growth and Contact for Pricing pricing. RunningHub records 3,105,554 monthly visits with -28.5% growth and Freemium pricing.

| Metric | [Labelbox](https://openaitools.app/tool/labelbox) | [RunningHub](https://openaitools.app/tool/runninghub) |
| :--- | :--- | :--- |
| Website URL | https://labelbox.com | https://www.runninghub.ai |
| Categories | AI Developer Tools, AI API, AI Workflow, AI Productivity Tools | AI App Builder, AI Workflow, AI Image Generator, AI Developer Tools |
| Pricing Model | Contact for Pricing | Freemium |
| Monthly Visits | 762,803 | 3,105,554 |
| MoM Growth Rate | -22.8% | -28.5% |
| Primary Market | United States | China |
| Direct Visits | 370,024 | 2,297,199 |
| Review Score | 4.4 | 4.4 |
| Saved Count | 0 | 2 |
| Supported Platforms | Website | Website |

## Labelbox

Labelbox occupies an unusual position in the AI stack: it does not primarily sell a chatbot or a generator, it builds the environments and data that models learn from plus the agents that take over recurring engineering and research work. The homepage claim is direct — frontier AI labs train on Labelbox environments and expert data, while engineering and research teams hand their recurring backlog to agents running on Recursion. A recent Series E of more than $100 million signals a heavily funded bet on that thesis.,For enterprises, the newer half of the product is Recursion. Agents are triggered by real signals — a failing build, a PagerDuty alert, a new dependency release, a fresh model checkpoint, or a Monday morning schedule — and then work in the background until the job is done. The examples the company promotes are concrete deliverables rather than summaries: a tested pull request with a preview link, a postmortem draft in Confluence with every event sourced, an ablation table naming the changes that mattered, or a patch for each exposed service after a critical CVE. A grader agent scores each run, and the graded session leaves behind memories, notes and skills that the next session reads before it acts.,The original foundation remains the data business: labeling, annotation, curation and model evaluation supported by expert human reviewers, used for computer vision, NLP, supervised fine-tuning, RLHF and red teaming. In practice the two halves reinforce each other, since the environments that produce high-quality training data are the same environments where agents learn to do real work. Pricing is enterprise-style, routed through sales conversations and shaped by data volume and agent usage, with no public self-serve tier.

**Pricing & Plans:** Contact for pricing. Labelbox does not publish self-serve plans or public rate cards; its pricing route instead directs interested teams to talk to sales, and cost is shaped by data production scope, agent deployment and enterprise requirements. There is no published free tier. Prospective customers should request a quote based on their volumes and use cases.

- **Data labeling and expert annotation:** Structured annotation, curation, model evaluation and human-in-the-loop review across vision, language and generative tasks, used to build the training and eval data behind production models.
- **Autonomous agent sessions:** Recursion agents start on their own from builds, alerts, commits, checkpoints and schedules, then work in the background until the task is finished and reviewable.
- **Domain specialists by function:** Specialist agents cover software engineering, reliability, security, ML research, evals, R&D, product and finance workflows, from flaky test fixes to postmortem drafts and vulnerability patches.
- **Graded outcomes that compound:** Every agent run is scored by a grader, and graded sessions leave memories, notes and skills that the next session reads before acting, so quality compounds over time.
- **Native tool and data integrations:** Agents operate against the tools teams already use, including GitHub, Jira, Linear, Slack, Datadog, PagerDuty, BigQuery, Databricks, Vercel and cloud providers.

**Strengths:** Covers both sides of the problem: training and eval data production plus agents that act on recurring work; Backed by a recent $100M+ Series E and adoption by frontier AI labs, indicating real funding and demand; Agent runs produce concrete deliverables with proof — tests, reruns, ablations — rather than unverified suggestions; Integrates with the toolchain teams already run: GitHub, Jira, Linear, Slack, Datadog, PagerDuty, BigQuery and Databricks

**Limitations:** No self-serve pricing or open signup: everything routes through a sales conversation, which slows down evaluation; The platform assumes real engineering and research infrastructure (GitHub, cloud providers, data warehouses) to deliver value; Positioning has shifted quickly toward autonomous agent sessions, so teams wanting only labeling workflows may find it heavier than needed

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

## RunningHub

RunningHub is an all-in-one AI content creation platform built around cloud ComfyUI. Instead of installing Stable Diffusion, Flux, ControlNet, and LoRA setup on your own GPU, you run workflows on RunningHub's servers and interact through a browser. The platform supports importing and running ComfyUI graphs, then turning them into polished single-click "AI Apps" that non-technical users can operate with simple prompts.

Beyond the workflow engine, RunningHub bundles a broad creative toolkit: text-to-image and text-to-video generation, image-to-image and image-to-video conversion, inpainting, outpainting, and upscaling powered by self-developed models. An infinite canvas and rapid-creation templates help users assemble campaigns, product visuals, and short videos. The homepage also showcases a community gallery of featured workflows, model APIs, and viral video templates.

RunningHub follows a freemium, credit-based model with free daily usage and subscription tiers for heavier production. It targets creators, small studios, and developers, and offers workflow, model, LLM, and app APIs so teams can embed generational capabilities into their own products.

**Pricing & Plans:** Freemium with daily free credits and pay-as-you-go credits; subscription tiers unlock higher concurrency, member discounts, and advanced models. API usage is priced separately.

- **Cloud ComfyUI:** Run, import, and share ComfyUI workflows in the cloud without local GPU hardware.
- **AI Apps Builder:** Publish a workflow as a single-click AI app that anyone can run with simple inputs.
- **Image & Video Generation:** Use hosted image and video models, including self-developed upscaling and enhancement tools, from one dashboard.
- **Developer APIs:** Integrate generation into your product via workflow, model, LLM, and app APIs.
- **Template Library & Community:** Explore a gallery of community workflows, viral video templates, and creator rewards.

**Limitations:** Complex workflows have a learning curve; Credit-based costs add up for heavy video generation; Best experience assumes some ComfyUI familiarity

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

## Frequently Asked Questions

### How do Labelbox and RunningHub compare in monthly traffic?

Labelbox has 762,803 monthly visits, while RunningHub has 3,105,554. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Labelbox has a month-over-month growth rate of -22.8%; RunningHub has -28.5%.

### How does pricing compare?

Labelbox: Contact for Pricing. Contact for pricing. Labelbox does not publish self-serve plans or public rate cards; its pricing route instead directs interested teams to talk to sales, and cost is shaped by data production scope, agent deployment and enterprise requirements. There is no published free tier. Prospective customers should request a quote based on their volumes and use cases. RunningHub: Freemium. Freemium with daily free credits and pay-as-you-go credits; subscription tiers unlock higher concurrency, member discounts, and advanced models. API usage is priced separately.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Adobe Firefly](https://openaitools.app/tool/adobe) | 396,998,213 | -8.6% | Freemium | Commercially safe generative AI workspace for images, video, audio, vectors, and multi-model creative production. | [.md](https://openaitools.app/tool/adobe.md) |
| 2 | [Higgsfield](https://openaitools.app/tool/higgsfield) | 47,127,865 | +16.2% | Freemium, Free Trial | AI-native creative suite for cinematic video and images | [.md](https://openaitools.app/tool/higgsfield.md) |
| 3 | [Runway](https://openaitools.app/tool/runwayml) | 7,498,396 | +16.9% | Freemium, Paid, Contact for Pricing | Generative video, image, and audio tools built on frontier AI research | [.md](https://openaitools.app/tool/runwayml.md) |
| 4 | [Civitai](https://openaitools.app/tool/civitai) | 6,963,136 | +12.8% | Freemium | Discover, download and generate with open-source AI models for image, video and 3D. | [.md](https://openaitools.app/tool/civitai.md) |
| 5 | [Pollo AI](https://openaitools.app/tool/pollo-ai) | 6,641,636 | -9.6% | Freemium | All-in-one AI studio for video, image, and agent-driven content creation | [.md](https://openaitools.app/tool/pollo-ai.md) |
| 6 | [Krea](https://openaitools.app/tool/krea) | 4,583,022 | +2.9% | Freemium | Realtime generative AI studio for images, video and custom models | [.md](https://openaitools.app/tool/krea.md) |
| 7 | [ComfyUI](https://openaitools.app/tool/comfyui) | 4,379,348 | +13.4% | Contact for Pricing, Free | Node-based visual AI studio for images, video, 3D and audio | [.md](https://openaitools.app/tool/comfyui.md) |
| 8 | [Tensor.Art](https://openaitools.app/tool/tensor-art) | 2,618,069 | +9.4% | Free | Free online AI image generation, video creation and model hosting in your browser | [.md](https://openaitools.app/tool/tensor-art.md) |
| 9 | [Together AI](https://openaitools.app/tool/together-ai) | 1,645,930 | +64.9% | Freemium, Paid | Together AI is the AI Native Cloud — a full-stack platform for running, fine-tuning and training open-source models. It spans serverless inference APIs, dedicated endpoints, GPU clusters, post-training and storage, all b | [.md](https://openaitools.app/tool/together-ai.md) |
| 10 | [Roboflow](https://openaitools.app/tool/roboflow) | 1,431,204 | +6.6% | Freemium, Contact for Pricing | Streamlines end-to-end computer vision workflows from annotation to model deployment, but lacks Labelbox's general enterprise agent orchestration. | [.md](https://openaitools.app/tool/roboflow.md) |

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Source: https://openaitools.app/compare/labelbox-vs-runninghub

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