# FluidStack vs Workable

FluidStack records 154,620 monthly visits with +7.3% month-over-month growth and Paid, Contact for Pricing pricing. Workable records 10,780,627 monthly visits with +5.5% growth and Free Trial, Paid pricing.

| Metric | [FluidStack](https://openaitools.app/tool/fluidstack) | [Workable](https://openaitools.app/tool/workable) |
| :--- | :--- | :--- |
| Website URL | https://fluidstack.io | https://www.workable.com |
| Categories | AI Developer Tools, AI Models, Large Language Models (LLMs) | AI Recruiting, AI Agent, AI CRM |
| Pricing Model | Paid, Contact for Pricing | Free Trial, Paid |
| Monthly Visits | 154,620 | 10,780,627 |
| MoM Growth Rate | +7.3% | +5.5% |
| Primary Market | United States | United States |
| Direct Visits | 47,869 | 5,309,440 |
| Review Score | 4.4 | 4.4 |
| Saved Count | 1 | 0 |
| 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)

## Workable

Workable positions itself as agentic software for recruiting and HR. The centrepiece is a native AI recruiting agent that operates inside the applicant tracking system: it continuously sources passive candidates from a 400M+ profile pool, evaluates every inbound applicant against up to 14 job criteria, messages candidates to verify interest and fill gaps, and produces a scored shortlist where strong fits auto-advance and clear rejections are filtered out. Because the agent inherits the platform's permissions and security model, every action is logged, permissioned and reviewable.

Underneath the agent sits a deep, conventional ATS. Teams manage requisitions and approvals, custom pipelines and profiles, interview kits, scorecards and assessments, self-service interview scheduling, and offer management with e-signatures and integrated background checks. One click publishes a job to 200+ boards across 100+ countries, and a drag-and-drop careers page builder plus LinkedIn Preferred and Indeed Platinum partnerships help with visibility. A searchable talent CRM keeps past applicants warm for future roles.

After the hire, Workable keeps going as a full HR platform: automated onboarding portals, employee self-service, employee records and document management, time off and attendance, performance and engagement tools, and payroll reporting. It is also deliberately open — MCP-native with comprehensive coverage for Claude, ChatGPT or custom agents, a documented REST API with webhooks, 270+ integrations, custom reporting dashboards and a mobile-first experience. Pricing combines a free trial with paid plans tiered by company size and modules.

**Pricing & Plans:** Free trial available with paid subscription plans; pricing scales by company size and selected modules, with demo and enterprise options. Check the official pricing page for current rates.

- **AI candidate sourcing:** The agent continuously searches 400M+ profiles, identifies strong fits before they apply and sends each a personalised outreach message for every open role.
- **Automated screening and engagement:** Every applicant is scored against up to 14 job criteria with visible reasoning, then messaged directly to confirm interest and close information gaps before reaching a recruiter.
- **Complete ATS underneath:** Requisitions, pipelines, interview kits and scorecards, interview scheduling, offer letters with e-signatures and integrated background checks in one platform.
- **Job ad syndication and careers pages:** Publish jobs to 200+ boards in 100+ countries and build branded career sites with a drag-and-drop editor, plus LinkedIn and Indeed Apply integration.
- **HR platform after the hire:** Onboarding, employee self-service, time off and attendance, performance reviews and engagement tools sit on the same employee data created during hiring.
- **Open platform and integrations:** MCP-native coverage plus a documented REST API with webhooks, 270+ integrations, custom reporting dashboards and a mobile-first employee and candidate experience.

**Strengths:** Native AI agent does real sourcing, screening and candidate messaging, not just keyword ranking; Runs on top of a complete ATS rather than being a bolt-on tool with limited context; Hiring context carries through to onboarding and HR, so talent data compounds over time; Open and MCP-native: bring Claude, ChatGPT or your own agents while Workable stays the system of record

**Limitations:** Pricing scales with headcount and module selection, so costs grow as you add HR features; Full value depends on adopting both the ATS and HR modules, which is a bigger rollout for small teams; Very feature-rich, so administrators need time to configure workflows, permissions and approvals; Partner job-board and integration advantages vary by region and plan tier

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

## Frequently Asked Questions

### How do FluidStack and Workable compare in monthly traffic?

FluidStack has 154,620 monthly visits, while Workable has 10,780,627. 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%; Workable has +5.5%.

### 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. Workable: Free Trial, Paid. Free trial available with paid subscription plans; pricing scales by company size and selected modules, with demo and enterprise options. Check the official pricing page for current rates.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [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) |
| 2 | [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) |
| 3 | [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) |
| 4 | [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) |
| 5 | [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) |
| 6 | [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) |
| 7 | [Recruit CRM](https://openaitools.app/tool/recruit-crm) | 729,799 | -7.8% | Contact for Pricing | Unifies applicant tracking and client management with AI outreach, but is tailored more heavily for agency recruiters. | [.md](https://openaitools.app/tool/recruit-crm.md) |
| 8 | [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) |
| 9 | [Cerebras](https://openaitools.app/tool/cerebras) | 701,013 | -12.6% | Contact for Pricing | Utilizes proprietary wafer-scale processors for extreme training speeds, differing from standard NVIDIA GPU cluster setups. | [.md](https://openaitools.app/tool/cerebras.md) |
| 10 | [Kula AI](https://openaitools.app/tool/kula-ai) | 492,326 | +4.2% | Paid, Contact for Pricing | Provides an AI-native ATS with automated sourcing and CRM, but has a steeper learning curve than Workable. | [.md](https://openaitools.app/tool/kula-ai.md) |

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Source: https://openaitools.app/compare/fluidstack-vs-workable

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