# FluidStack vs GreenNode

FluidStack records 154,620 monthly visits with +7.3% month-over-month growth and Paid, Contact for Pricing pricing. GreenNode records 75,996 monthly visits with +28.1% growth and Paid pricing.

| Metric | [FluidStack](https://openaitools.app/tool/fluidstack) | [GreenNode](https://openaitools.app/tool/greennode) |
| :--- | :--- | :--- |
| Website URL | https://fluidstack.io | https://greennode.ai |
| Categories | AI Developer Tools, AI Models, Large Language Models (LLMs) | Other |
| Pricing Model | Paid, Contact for Pricing | Paid |
| Monthly Visits | 154,620 | 75,996 |
| MoM Growth Rate | +7.3% | +28.1% |
| Primary Market | United States | Vietnam |
| Direct Visits | 47,869 | 41,903 |
| Review Score | 4.4 | 4.1 |
| 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)

## GreenNode

GreenNode is a cloud platform operated by a Vietnamese company that positions itself as a sovereign AI cloud for Southeast Asia. Rather than being a single AI application, it is the infrastructure layer underneath AI work: GPU instances, CPU instances, bare-metal H100 servers, managed Kubernetes, block, file and object storage, networking and managed databases. The emphasis is on keeping workloads and data inside the region, with availability zones in Hanoi, Ho Chi Minh City and Bangkok.

On top of the raw infrastructure, GreenNode ships an AI stack for teams that want to train and deploy models without assembling everything themselves. The AI Platform covers training, fine-tuning and inference at scale; Model as a Service (MaaS) exposes a library of ready-to-use models through an API; AgentBase helps take agents from prototype to production; and Intelligent Document Processing combines OCR with language and vision models for extraction and validation.

Pricing is usage-based and quoted in Vietnamese dong on the official pricing page, spanning per-hour rates for AI services and per-30-day rates for compute and database products. Enterprises generally start with a free trial flow or a sales conversation, and the platform targets regulated industries such as finance, retail, education and software that have to satisfy local compliance and data-residency rules.

**Pricing & Plans:** Paid, usage-based cloud pricing quoted in VND. GPU instances, storage, Kubernetes, databases and AI services are billed per hour or per 30 days; enterprise plans are quoted through sales.

- **GPU and HPC compute:** On-demand GPU instances plus dedicated H100 bare-metal servers tuned for AI training, fine-tuning and high-performance computing workloads.
- **Fully managed Kubernetes:** GreenNode Kubernetes Service handles cluster provisioning and operations so teams can deploy containerized applications at scale without running control planes.
- **AI stack and Model as a Service:** A unified AI Platform for training and inference, a MaaS catalog of ready-to-use models exposed via API, and AgentBase for shipping agents to production.
- **Storage, networking and databases:** Block, file and object storage, VPC networking with load balancing and interconnect, and managed PostgreSQL, MySQL, MariaDB, Redis, OpenSearch and Kafka.
- **Regional data sovereignty:** Six availability zones across Vietnam and Thailand with compliance-oriented controls so data stays within Southeast Asia.

**Strengths:** Infrastructure and AI services in one governed platform; Regional availability zones that support Southeast Asian data-residency requirements; Clear public pricing for compute, storage, databases and AI services; Managed Kubernetes, databases and model serving reduce operational overhead

**Limitations:** Pricing is published in Vietnamese dong, which takes conversion effort for international buyers; Geographic footprint is limited to Vietnam and Thailand; Enterprise features generally require contact with the sales team

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

## Frequently Asked Questions

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

FluidStack has 154,620 monthly visits, while GreenNode has 75,996. 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%; GreenNode has +28.1%.

### 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. GreenNode: Paid. Paid, usage-based cloud pricing quoted in VND. GPU instances, storage, Kubernetes, databases and AI services are billed per hour or per 30 days; enterprise plans are quoted through sales.

## 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 | Rent cloud GPUs by the second from a global marketplace | [.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 | Serverless cloud infrastructure for AI and data workloads | [.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 | [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) |
| 8 | [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) |
| 9 | [DeepInfra](https://openaitools.app/tool/deep-infra) | 457,810 | -8.9% | Paid | Specializes in cost-effective serverless API inference for open-weights models instead of raw infrastructure rentals. | [.md](https://openaitools.app/tool/deep-infra.md) |
| 10 | [Lightning AI](https://openaitools.app/tool/lightning-ai) | 272,562 | -12.3% | Freemium, Paid, Contact for Pricing | The AI cloud built by the creators of PyTorch Lightning | [.md](https://openaitools.app/tool/lightning-ai.md) |

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

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