# FluidStack vs Outlier AI

FluidStack records 154,620 monthly visits with +7.3% month-over-month growth and Paid, Contact for Pricing pricing. Outlier AI records 10,372,036 monthly visits with +7.6% growth and Paid pricing.

| Metric | [FluidStack](https://openaitools.app/tool/fluidstack) | [Outlier AI](https://openaitools.app/tool/outlier-ai) |
| :--- | :--- | :--- |
| Website URL | https://fluidstack.io | https://outlier.ai |
| Categories | AI Developer Tools, AI Models, Large Language Models (LLMs) | AI Jobs, Large Language Models (LLMs), AI Developer Tools |
| Pricing Model | Paid, Contact for Pricing | Paid |
| Monthly Visits | 154,620 | 10,372,036 |
| MoM Growth Rate | +7.3% | +7.6% |
| Primary Market | United States | United States |
| Direct Visits | 47,869 | 5,819,236 |
| Review Score | 4.4 | 3.8 |
| Saved Count | 1 | 3 |
| Supported Platforms | Website | Website |

## FluidStack

FluidStack is an AI compute provider that builds the physical layer underneath frontier model work: data centers, power, cooling and very large GPU clusters. Its public positioning is deliberately infrastructural rather than product-led — it describes building gigawatt-scale compute, bringing new sites online in months, and operating tens of millions of accelerators reliably. For teams training or serving large models, that translates into reserved, single-tenant-class capacity that is provisioned and operated for you rather than an instant, self-serve VM catalogue.

A distinguishing theme is the pairing of power and compute. FluidStack writes about redesigning compute and power infrastructure from first principles, developing off-grid solar to supply clusters, and using closed-loop cooling that fills tanks once and recirculates water indefinitely. It also emphasises building in the United States with onshored manufacturing, framing infrastructure ownership as a strategic question about which values shape the technology being built. For AI organisations, these are increasingly relevant because energy availability, not chip supply alone, is the binding constraint on scaling.

If you need a small number of GPUs for a day, FluidStack is probably not the fastest route; capacity is engaged at enterprise scale through a sales process. If you are planning a multi-month training run or a production inference fleet and want dedicated, purpose-built infrastructure with managed operations, it is a strong candidate to evaluate alongside the major hyperscalers and specialised GPU clouds.

**Pricing & Plans:** Enterprise and contact-for-pricing. FluidStack does not publish per-GPU-hour rates or a self-serve sign-up on its website; capacity is scoped and quoted through a direct sales conversation based on cluster size, duration and hardware. Catalogue listings classify it as a paid product requiring contact for pricing.

- **Datacenter-scale compute built in-house:** FluidStack designs and builds large AI data centers, including high-density campuses with significant per-site power capacity, rather than reselling capacity from other clouds.
- **GPU clusters for training and inference:** Clusters are architected for large-scale model training and inference, with high-bandwidth interconnect and orchestration suitable for distributed workloads.
- **Power and cooling engineered together:** The company develops off-grid solar and recirculating closed-loop cooling, treating power and water efficiency as core engineering problems.
- **Managed operations and reliability:** Smart hands, cluster provisioning and operations support let research teams focus on models while FluidStack runs the physical and orchestration layers.
- **US-built and onshored supply chain:** Data centers are built in the United States with onshored manufacturing of compute and power infrastructure, a deliberate supply-chain and sovereignty choice.

**Strengths:** Purpose-built AI infrastructure rather than generic cloud resale; Power, cooling and data center design handled in-house, which matters at scale; Managed provisioning and operations for large training and inference clusters; Explicit positioning on US-built, onshored infrastructure

**Limitations:** No published self-serve pricing or instant sign-up; access requires a sales conversation; Enterprise-scale focus means very small individual workloads may not be a fit; Capacity is concentrated in US locations, which may matter for latency-sensitive or data-residency-bound teams

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

## Outlier AI

Outlier AI is a work platform built around the idea that human expertise is still the fastest way to make AI models better. Professionals in fields such as software engineering, mathematics, physics, medicine and dozens of languages sign up, verify their skills, and are matched with projects where they write difficult prompts, build answer rubrics and grade model outputs. Because the work is project-based and fully remote, contributors set their own hours with no minimum commitment.

The platform reports more than 900,000 experts onboarded and over $500 million paid out to contributors across 50 countries, with a large share of participants being graduate students and PhDs. Typical accounts describe a 30 to 90 minute onboarding flow covering account creation, expertise selection, skill screening and identity verification, after which project-specific training begins.

Outlier is part of the Scale AI family of data-labeling businesses, so the projects generally feed into real model-development pipelines rather than academic exercises. Pay is competitive and quality-based, disbursed weekly, and contributors sometimes get free access to paid frontier models as part of their work. Because project availability fluctuates, income is best treated as flexible supplementary earnings rather than a guaranteed full-time salary.

**Pricing & Plans:** Free for experts to join. Outlier pays contributors for completed work rather than charging them; rates vary by project, expertise area and locale, with quality-based bonuses and weekly payouts.

- **Expert-matched project work:** After skill screening, contributors are matched to projects that fit their domain, from coding and math to linguistics and medicine.
- **Genuinely flexible schedule:** No minimum hours and fully remote work, so experts can fit tasks around study, research or a primary job.
- **Varied AI-training tasks:** Typical work includes writing hard prompts, producing grading rubrics, ranking competing answers and reviewing model reasoning.
- **Weekly, quality-based pay:** Contributors are paid for approved work each week, with rewards that scale with the quality of their output.
- **Skills that transfer:** Contributors build hands-on prompt-engineering and evaluation experience that carries into AI and data roles.

**Strengths:** Remote, project-based work with no minimum hours; Open to strong generalists as well as advanced degree holders; Weekly payouts with quality-based rewards; Builds practical prompt-engineering and evaluation experience

**Limitations:** Project availability and hours can be inconsistent; Onboarding, skill screening and identity checks take time; Rates and project access vary significantly by region and specialty

[Profile (Markdown)](https://openaitools.app/tool/outlier-ai.md)

## Frequently Asked Questions

### How do FluidStack and Outlier AI compare in monthly traffic?

FluidStack has 154,620 monthly visits, while Outlier AI has 10,372,036. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

FluidStack has a month-over-month growth rate of +7.3%; Outlier AI has +7.6%.

### How does pricing compare?

FluidStack: Paid, Contact for Pricing. Enterprise and contact-for-pricing. FluidStack does not publish per-GPU-hour rates or a self-serve sign-up on its website; capacity is scoped and quoted through a direct sales conversation based on cluster size, duration and hardware. Catalogue listings classify it as a paid product requiring contact for pricing. Outlier AI: Paid. Free for experts to join. Outlier pays contributors for completed work rather than charging them; rates vary by project, expertise area and locale, with quality-based bonuses and weekly payouts.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Mercor](https://openaitools.app/tool/mercor-com) | 14,164,192 | +34% | Contact for Pricing | Matches vetted domain experts with remote AI training and engineering roles using AI-driven vetting. | [.md](https://openaitools.app/tool/mercor-com.md) |
| 2 | [fal.ai](https://openaitools.app/tool/fal-ai) | 3,093,684 | -3.7% | Paid, pay-as-you-go usage-based pricing | Delivers developer-first serverless endpoints optimized for generative media models rather than general-purpose infrastructure. | [.md](https://openaitools.app/tool/fal-ai.md) |
| 3 | [RunPod](https://openaitools.app/tool/runpod) | 2,881,043 | +5.9% | Paid | Offers flexible on-demand GPU rentals and serverless endpoints, but lacks FluidStack's ultra-scale enterprise GPU clusters. | [.md](https://openaitools.app/tool/runpod.md) |
| 4 | [clickworker](https://openaitools.app/tool/clickworker-com) | 1,861,149 | +0.5% | Contact for Pricing | Offers crowdsourced data collection and annotation services, operating on a broader task-based crowdsourcing model. | [.md](https://openaitools.app/tool/clickworker-com.md) |
| 5 | [Together AI](https://openaitools.app/tool/together-ai) | 1,645,930 | +64.9% | Freemium, Paid | Focuses on optimized serverless inference APIs and managed model hosting rather than raw cluster rentals. | [.md](https://openaitools.app/tool/together-ai.md) |
| 6 | [OpenTrain AI](https://openaitools.app/tool/opentrain-ai) | 1,469,348 | +11.2% | Contact for Pricing | Connects AI research labs with human subject matter experts for specialized evaluation and data annotation tasks. | [.md](https://openaitools.app/tool/opentrain-ai.md) |
| 7 | [Vast.ai](https://openaitools.app/tool/vast-ai) | 1,257,554 | +2.8% | Paid | Delivers peer-to-peer GPU rental marketplaces for lower-cost experimentation, though with less enterprise infrastructure predictability. | [.md](https://openaitools.app/tool/vast-ai.md) |
| 8 | [Modal](https://openaitools.app/tool/modal-com) | 1,196,021 | +30.2% | Freemium, Contact for Pricing | Provides serverless Python container execution for cloud jobs, but lacks raw multi-node cluster provisioning controls. | [.md](https://openaitools.app/tool/modal-com.md) |
| 9 | [Nebius](https://openaitools.app/tool/nebius) | 1,145,711 | +10.7% | Paid, Contact for Pricing | Provides dedicated NVIDIA GPU clusters and managed cloud infrastructure, competing directly on enterprise-grade training workloads. | [.md](https://openaitools.app/tool/nebius.md) |
| 10 | [Salad](https://openaitools.app/tool/salad-gpu-cloud) | 713,519 | +10.4% | Free Trial, Paid, Contact for Pricing | Distributed GPU cloud that orchestrates the world's idle consumer GPUs | [.md](https://openaitools.app/tool/salad-gpu-cloud.md) |

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Source: https://openaitools.app/compare/fluidstack-vs-outlier-ai

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