A Fluidstack alternative for flexible GPU infrastructure

Compare Fluence and Fluidstack across GPU access, provider choice, orchestration, pricing, and infrastructure requirements for training and inference.

View available GPUs

Compare GPU costs

A Fluidstack alternative for flexible GPU infrastructure

Compare Fluence and Fluidstack across GPU access, provider choice, orchestration, pricing, and infrastructure requirements for training and inference.

View available GPUs

Compare GPU costs

Review GPU offers across providers, regions, and configurations

Choose containers, virtual machines, or bare metal for each workload

Plan spend around clear hourly rates, unlimited bandwidth, and zero egress fees

Review GPU offers across providers, regions, and configurations

Choose containers, virtual machines, or bare metal for each workload

Plan spend around clear hourly rates, unlimited bandwidth, and zero egress fees

Fluence vs Fluidstack at a glance

Fluence

Fluidstack

Best for

Self-managed AI workloads and flexible infrastructure

Large dedicated training and inference clusters

Core experience

Direct infrastructure control across providers

Single-tenant AI infrastructure with managed operations

Deployment options

GPU containers, VMs, bare metal

Machine instances, managed Kubernetes, managed Slurm

Provider flexibility

Capacity across multiple providers

Infrastructure delivered and operated by Fluidstack

Platform tooling

Console, API, preset or custom images

CLI, APIs, SSO, Lighthouse observability

Cost model

Transparent hourly pricing with zero egress fees

Order-based pricing by minute, hour, or subscription

Compare the full cost of GPU compute

Fluidstack prices infrastructure through customer orders, with billing set per minute, per hour, or by subscription. Fluence shows hourly rates across providers and deployment types. Compare GPU configuration, contract term, orchestration, storage, and support before choosing an option. Need another GPU model or setup? Send us your requirements and we will get back to you.

Compare the full cost of GPU compute

Run GPU workloads with the control you need

GPU containers

Deploy packaged inference, batch, and development workloads without maintaining a complete operating system.

GPU VMs

Run persistent services with full OS access, custom drivers, and system-level controls.

GPU bare metal

Use dedicated hardware for sustained training, strict isolation, and direct accelerator access.

Run GPU workloads with the control you need

GPU containers

Deploy packaged inference, batch, and development workloads without maintaining a complete operating system.

GPU VMs

Run persistent services with full OS access, custom drivers, and system-level controls.

GPU bare metal

Use dedicated hardware for sustained training, strict isolation, and direct accelerator access.

More control over how workloads run

Start with the capacity you need

Launch single-GPU or multi-GPU infrastructure without provisioning a complete managed cluster.

Choose your deployment model

Use containers, virtual machines, or bare metal based on runtime access, isolation, and hardware requirements.

Compare providers before deployment

Review available regions, GPU models, configurations, and hourly prices before launching your workload.

More control over how workloads run

Start with the capacity you need

Launch single-GPU or multi-GPU infrastructure without provisioning a complete managed cluster.

Choose your deployment model

Use containers, virtual machines, or bare metal based on runtime access, isolation, and hardware requirements.

Compare providers before deployment

Review available regions, GPU models, configurations, and hourly prices before launching your workload.

Built for self-managed GPU workloads

Fluence supports:

Production inference

Run model-serving endpoints with control over runtimes, network settings, and GPU allocation.

GPU container or GPU VM

Fine-tuning workflows

Manage adapters, checkpoints, and repeatable training runs in persistent GPU environments.

GPU VM or GPU bare metal

LLM development

Evaluate open models, quantization formats, and serving stacks with the dependencies you choose.

GPU container or GPU VM

Training runs

Run sustained single-server or multi-GPU workloads with control over software, storage, and hardware access.

GPU VM or GPU bare metal

Batch inference

Process documents, embeddings, media, and model outputs through repeatable GPU jobs.

GPU container

Model research

Compare architectures, context lengths, and precision formats in isolated, reproducible environments.

GPU container or GPU VM

AI agent inference

Host models and supporting services for agent applications while retaining control over the surrounding stack.

GPU container or GPU VM

Built for self-managed GPU workloads

Fluence supports:

Production inference

Run model-serving endpoints with control over runtimes, network settings, and GPU allocation.

GPU container or GPU VM

Fine-tuning workflows

Manage adapters, checkpoints, and repeatable training runs in persistent GPU environments.

GPU VM or GPU bare metal

LLM development

Evaluate open models, quantization formats, and serving stacks with the dependencies you choose.

GPU container or GPU VM

Training runs

Run sustained single-server or multi-GPU workloads with control over software, storage, and hardware access.

GPU VM or GPU bare metal

Batch inference

Process documents, embeddings, media, and model outputs through repeatable GPU jobs.

GPU container

Model research

Compare architectures, context lengths, and precision formats in isolated, reproducible environments.

GPU container or GPU VM

AI agent inference

Host models and supporting services for agent applications while retaining control over the surrounding stack.

GPU container or GPU VM

Try Fluence with one GPU workload

Move one representative workload and compare cost, setup, performance, and infrastructure control before expanding the deployment.

Choose a workload

Match its GPU and memory requirements

Select container, VM, or bare metal

Run under representative conditions

Compare cost, performance, and control

Try Fluence with one GPU workload

Move one representative workload and compare cost, setup, performance, and infrastructure control before expanding the deployment.

Choose a workload

Match its GPU and memory requirements

Select container, VM, or bare metal

Run under representative conditions

Compare cost, performance, and control

FAQ

How do Fluidstack and Fluence differ?

How does GPU pricing compare?

Which GPUs are available on Fluidstack and Fluence?

Do both platforms support single-GPU and multi-GPU workloads?

How does regional availability compare?

FAQ

How do Fluidstack and Fluence differ?

How does GPU pricing compare?

Which GPUs are available on Fluidstack and Fluence?

Do both platforms support single-GPU and multi-GPU workloads?

How does regional availability compare?

Run AI workloads on compute you control

Compare GPU offers across providers and choose the deployment model, region, and configuration required by your stack.

Explore latest GPUs

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