Run Dify at 55% Lower Cost
Move self-managed Dify workflows from local Docker to persistent CPU infrastructure with public endpoints, background workers, and storage. Connect the model provider you choose—or a separate self-hosted inference endpoint—while keeping the Dify application stack on CPU.
Fluence
$2.54/mo
Hetzner
$14.00/mo
DigitalOcean
$31.50/mo
AWS
$53.50/mo
Run Dify at 55% Lower Cost
Move self-managed Dify workflows from local Docker to persistent CPU infrastructure with public endpoints, background workers, and storage. Connect the model provider you choose—or a separate self-hosted inference endpoint—while keeping the Dify application stack on CPU.
Fluence
$2.54/mo
Hetzner
$14.00/mo
DigitalOcean
$31.50/mo
AWS
$53.50/mo
Built for always-on Dify hosting
Dify’s visual canvas is only one part of the stack. Give its apps, APIs, workers, schedules, databases, and vector state a long-lived home beyond your local Docker session.
Built for always-on Dify hosting
Dify’s visual canvas is only one part of the stack. Give its apps, APIs, workers, schedules, databases, and vector state a long-lived home beyond your local Docker session.
One architecture for Dify workflow and agents
Run Dify’s application, orchestration, and data services on Fluence CPU Cloud. Keep model inference outside the base VM by default, or add a separate GPU endpoint when local models require one.
One architecture for Dify workflow and agents
Run Dify’s application, orchestration, and data services on Fluence CPU Cloud. Keep model inference outside the base VM by default, or add a separate GPU endpoint when local models require one.
Get Dify running in 3 easy steps
Start with Dify’s official Docker Compose deployment path, then configure the public, persistent, and operational pieces a local installation does not need.
1
Provision the host
Choose a region, server type, storage, operating system, and networking settings for your Dify backend.
2
Configure and start Dify
Install Docker and Docker Compose, clone a tagged Dify release, and copy the example environment file: cd dify/docker cp .env.example .env Replace the default secrets, configure public URLs, and start the stack: docker compose up -d
3
Connect, publish, and operate
Add a model-provider key or custom model endpoint, publish your applications and triggers, and verify that every required container is healthy. Before production, configure TLS, monitoring, backups, restore tests, firewall rules, certificate renewal, and a controlled upgrade process.
Get Dify running in 3 easy steps
Start with Dify’s official Docker Compose deployment path, then configure the public, persistent, and operational pieces a local installation does not need.
1
Provision the host
Choose a region, server type, storage, operating system, and networking settings for your Dify backend.
2
Configure and start Dify
Install Docker and Docker Compose, clone a tagged Dify release, and copy the example environment file: cd dify/docker cp .env.example .env Replace the default secrets, configure public URLs, and start the stack: docker compose up -d
3
Connect, publish, and operate
Add a model-provider key or custom model endpoint, publish your applications and triggers, and verify that every required container is healthy. Before production, configure TLS, monitoring, backups, restore tests, firewall rules, certificate renewal, and a controlled upgrade process.
Save up to 55% on Dify base VM costs
Use lower-cost CPU infrastructure for the Dify runtime, then add inference, storage, and external services only where the workload requires them.
No egress fees
Transparent daily pricing
Public IPv4 and persistent storage available
Note: Calculator estimates reflect only the Virtual Server layer used for LlamaIndex hosting.
Save up to 55% on Dify base VM costs
Use lower-cost CPU infrastructure for the Dify runtime, then add inference, storage, and external services only where the workload requires them.
No egress fees
Transparent daily pricing
Public IPv4 and persistent storage available
Note: Calculator estimates reflect only the Virtual Server layer used for LlamaIndex hosting.
Dify AI on Fluence vs. a local machine
Local Docker is ideal for development and evaluation. Fluence is the stronger fit when Dify needs a public, persistent, and remotely accessible home.
Capability
Dify on Fluence
Dify on a local machine
Public access
Public IPv4 with customer-configured domain and TLS
Requires tunneling, port forwarding, or local network configuration
Webhooks and schedules
Continue while the VM and Dify services remain healthy
Stop when the device or Docker stack stops
Persistent data
VM storage plus optional persistent volumes and customer-managed backups
Stored on a device-bound local disk
Team access
Shared remote deployment for authorized users
Tied to one workstation or local network
Scaling path
Move to a larger configuration or split services as requirements grow
Limited by local hardware
Dify AI on Fluence vs. a local machine
Local Docker is ideal for development and evaluation. Fluence is the stronger fit when Dify needs a public, persistent, and remotely accessible home.
Dify on Fluence
Dify on a local machine
Public access
Public IPv4 with customer-configured domain and TLS
Requires tunneling, port forwarding, or local network configuration
Webhooks and schedules
Continue while the VM and Dify services remain healthy
Stop when the device or Docker stack stops
Persistent data
VM storage plus optional persistent volumes and customer-managed backups
Stored on a device-bound local disk
Team access
Shared remote deployment for authorized users
Tied to one workstation or local network
Scaling path
Move to a larger configuration or split services as requirements grow
Limited by local hardware
Why run Dify on Fluence
Why run Dify on Fluence
What you can build with Dify on Fluence
What you can build with Dify on Fluence
A global marketplace of compute
Compare available providers and locations, provision the CPU instance for your Dify runtime, attach storage and public IPs, and add GPU resources only when self-hosted inference requires them.
A global marketplace of compute
Compare available providers and locations, provision the CPU instance for your Dify runtime, attach storage and public IPs, and add GPU resources only when self-hosted inference requires them.
FAQ
Can I self-host Dify on Fluence?
How much CPU and RAM does Dify need?
Does Dify need a GPU?
Which model providers can I connect to Dify?
Can Dify expose APIs, webhooks, and scheduled workflows?
Show more
FAQ
Can I self-host Dify on Fluence?
How much CPU and RAM does Dify need?
Does Dify need a GPU?
Which model providers can I connect to Dify?
Can Dify expose APIs, webhooks, and scheduled workflows?
Show more
Be the first to know
Be the first to know