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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11Yes. Ollama runs on a Linux VPS, including a CPU-only server. The practical limits are memory, CPU performance, disk space, and how you expose the API. RAM determines which model can load, while CPU-only inference is usually much slower than GPU-backed inference. By default, Ollama listens only on 127.0.0.1:11434, so remote clients cannot reach it until you deliberately change the network design.
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What a VPS installation can and cannot do
A VPS is a rented virtual Linux server with dedicated limits for vCPU, memory, storage and network traffic. Ollama can run there much like it runs on a local Linux machine: install the service, download a model, and send prompts to its local API.
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The important distinction is that “it starts” does not mean “it is a good production setup.” A small VPS may launch Ollama but fail when a larger model is loaded, when the context window grows, or when two users generate text at the same time. A CPU-only VPS is also functional but can feel slow for interactive use. A GPU is optional rather than mandatory.
- Memory: the largest model you can load is primarily constrained by available RAM, with additional headroom needed for the operating system, Ollama and the model’s working context.
- CPU: more and faster vCPUs can improve CPU inference, but virtualized CPU performance varies by host and plan.
- Storage: model files can consume several gigabytes each, so the boot disk must hold the operating system, Ollama and every model you intend to keep.
- Networking: Ollama is local-only by default. Making it reachable from the internet is a separate security project, not an installation checkbox.
VPS requirements: how much RAM, CPU and disk do you need?
There is no official Ollama hardware minimum published in the material available for this guide. Third-party sizing guides disagree, so treat their figures as planning estimates rather than guarantees. The following figures describe different planning points, not interchangeable requirements.
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| Planning figure | What it represents | Qualification |
|---|---|---|
| 2 vCPU, 4 GB RAM, 20 GB disk | A reported entry-level floor | From a third-party VPS guide; enough only for a modest, carefully chosen workload and not a promise that every model will fit. |
| 8 GB RAM, 64-bit CPU with AVX2, about 10 GB disk | Another published minimum estimate | From a separate third-party guide; it says a GPU is not required. The lower disk figure may leave little room for multiple models. |
| About 16 GB RAM | Suggested size for regular 7B-class use | A third-party guide’s recommendation for daily use, not an official Ollama specification. |
These conflicting numbers are best read as a sizing range. A 4 GB VPS might be adequate for a very small model and light testing, while a 16 GB machine gives a 7B-class workload considerably more breathing room. Leave memory for Linux, background services and temporary allocations; assigning every available gigabyte to a model invites swapping or an out-of-memory kill.
CPU and instruction-set considerations
Choose a 64-bit Linux image. One guide specifically calls out AVX2 support, so verify that the virtual CPU exposes the instruction set before committing to a long-running deployment. CPU-only generation works, but response speed depends on the host CPU, virtualization policy, model, quantization and context size. Published throughput figures in the available material were not attributable to a verified source, so do not plan around a particular tokens-per-second number.
Disk planning
Disk estimates in the guides range from about 10 GB to 20 GB for a basic installation. That is space for the operating system, Ollama and a limited model set, not a universal allowance. Keep extra capacity for additional model downloads, logs and upgrades. A full filesystem can prevent new models from downloading and can also break unrelated system services.
Choose a VPS size before you install
Start with the workload, not a provider’s smallest advertised plan. Ask these questions:
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- Will one person test models, or will several clients send requests concurrently?
- Do you need a small model for classification and short answers, or a larger model for longer prompts?
- Can requests wait for CPU generation, or is interactive latency important?
- Will the VPS host only Ollama, or also a database, web application, reverse proxy and monitoring stack?
For a proof of concept, the 4–8 GB figures reported by third-party guides may be a starting point if you select a model that fits and accept slow CPU responses. For regular 7B-class use, budgeting around 16 GB RAM is the more conservative interpretation of the available guidance. Scale up when the host swaps, the process is killed for lack of memory, or concurrent requests exhaust headroom.
Install Ollama on a Linux VPS
Use a supported 64-bit Linux distribution and connect over SSH with an account that can use sudo. The exact package behavior can change, so check the installer output and confirm the service name after installation.
- Update the operating system. Apply security updates and reboot if the kernel requires it. Do not expose a newly provisioned server to the internet with an unpatched base image.
- Install Ollama. The standard Linux installer is commonly invoked as
curl -fsSL https://ollama.com/install.sh | sh. Review the script’s output rather than assuming it succeeded silently. - Confirm the binary and service. Run
ollama --version, then checksudo systemctl status ollama. If the service is not active, inspectsudo journalctl -u ollama -n 100 --no-pagerbefore attempting model downloads. - Download a model deliberately. Use
ollama pull <model-name>and watch available disk space while it downloads. Keep only the models the VPS can store and load reliably. - Run a local test first. Execute
ollama run <model-name>from the VPS. Confirm that the model loads and produces a response before changing any listener or firewall setting.
Keep the first test on the server itself. This separates model, memory and CPU problems from later network-access problems.
Ollama’s network default and what OLLAMA_HOST changes
The official FAQ documents Ollama’s default listener as 127.0.0.1:11434. That loopback address accepts connections from the VPS itself, not from another machine. The networking details are documented at https://docs.ollama.com/faq.
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Changing the OLLAMA_HOST environment variable changes the bind address. Setting it to 0.0.0.0:11434 makes Ollama listen on every network interface. That is a reachability change, not an authentication or encryption feature. The operating-system firewall and any router, security group or upstream network device still determine whether outside clients can connect.
Change the bind address with systemd
On a typical Linux service installation, create a systemd override rather than editing a generated unit file:
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sudo systemctl edit ollama. - Add:
[Service]
Environment="OLLAMA_HOST=0.0.0.0:11434"- Save the file, then run
sudo systemctl daemon-reload. - Restart Ollama with
sudo systemctl restart ollama. - Verify the effective listener with
ss -tupln | grep 11434.
If the output still shows 127.0.0.1:11434, inspect the service environment and logs. If it shows 0.0.0.0:11434, every interface is listening; that does not mean the port is safely reachable or protected.
Secure remote access: do not publish port 11434 casually
Public exposure is the main risk in a VPS deployment. A process listening on all interfaces can become reachable as soon as firewall and upstream network rules allow it. Anyone who can reach the API may consume CPU, RAM and bandwidth, submit sensitive prompts, or retrieve responses. The captured official FAQ does not confirm whether the API provides built-in authentication; therefore, do not assume that changing the bind address gives you login protection.
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Third-party deployment guides consistently recommend putting a private network or an authenticating TLS layer in front of Ollama and restricting source addresses. Use one of these designs:
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Preferred for private teams: a VPN
Keep Ollama bound to 127.0.0.1:11434 when possible, and connect administrators or applications through a private VPN such as WireGuard. The VPN creates a controlled path without putting the Ollama port on the public internet. Permit only the VPN interface or VPN address range at the host firewall, and remove broad public rules.
For an application endpoint: a TLS reverse proxy
Place nginx, Caddy or Traefik in front of the local Ollama port. Terminate HTTPS at the proxy, enforce an authentication policy there, and proxy only the routes your application needs. Keep the Ollama listener on loopback or a private interface. If the proxy and Ollama are on the same VPS, there is usually no reason to bind Ollama to every interface.
Authentication, rate limiting, request-size limits and access logging belong at the proxy or the calling application unless you have verified support in your exact Ollama release. Use a valid certificate and rotate credentials. Never send API keys or prompts over plain HTTP across an untrusted network.
If you must allow direct access
Use the narrowest possible firewall rule: restrict TCP port 11434 to known source IP addresses or a private subnet. Do not create an unrestricted “allow from anywhere” rule merely because a client cannot connect. Check both layers:
- Host firewall: confirm the local firewall allows the intended source and port.
- Upstream controls: check the VPS provider’s security group, router or network ACL for the same port.
- Listener: verify the address with
ss -tupln | grep 11434. - Application path: test locally, then from an approved remote address, so a successful local request does not hide a blocked network path.
Firewall example and safer alternatives
If you use a host firewall such as UFW, a source-restricted rule is safer than a global port opening. Replace the example address with the fixed address of your trusted client or private network:
sudo ufw allow from 203.0.113.10 to any port 11434 proto tcp
sudo ufw status numberedThe address 203.0.113.10 is an example documentation address, not a value to copy for production. If client addresses change, use a VPN or authenticated proxy instead of repeatedly widening the firewall. Also remember that a firewall rule cannot add TLS or user authentication; it only controls reachability.
Common failure modes and fixes
| Symptom | Likely cause | What to check |
|---|---|---|
| The service starts, then exits while loading a model | Insufficient RAM or disk | Review journalctl -u ollama, free memory and free disk; remove unused models or move to a larger VPS. |
| Responses are extremely slow | CPU-only inference, weak vCPUs or an oversized model | Check CPU saturation and choose a smaller model; a GPU-backed host is optional but can materially improve latency. |
| Local requests work but remote requests time out | Still bound to loopback, or blocked by firewall/security group | Run ss -tupln | grep 11434, inspect OLLAMA_HOST, then check both host and upstream firewall rules. |
| The port is reachable from the internet unexpectedly | Binding to 0.0.0.0 combined with a broad network rule |
Restore loopback binding, remove the public firewall rule, and use a VPN or authenticated reverse proxy. |
| A model download fails halfway | Insufficient disk, interrupted connection or a full filesystem | Check disk usage, service logs and network stability before retrying. |
| Two users cause failures or swapping | Memory headroom is too small for concurrent work | Reduce concurrency, use a smaller model, stop unrelated services or resize the VPS. |
Operational checklist before you rely on the VPS
- Confirm the VPS is 64-bit and, preferably, exposes AVX2 as expected by your selected software stack.
- Measure available RAM after the operating system and other services start; do not size from advertised memory alone.
- Keep enough disk for the operating system, Ollama, the selected models, logs and future downloads.
- Test the model locally before touching network exposure.
- Record the intended listener address and verify it after every service change.
- Prefer loopback plus VPN or a TLS reverse proxy over direct public exposure.
- Restrict source IPs at every applicable firewall or security-group layer.
- Monitor memory, CPU, disk and request latency, especially when adding models or users.
- Apply operating-system and Ollama updates during a planned maintenance window, then retest the service and listener.
Is a VPS the right place for Ollama?
A VPS is a reasonable choice when you need an always-on Linux endpoint, predictable access from your own applications, or a private service reachable through a VPN. It is less attractive when you require fast interactive generation but have only weak CPU instances, or when your model and concurrency needs exceed the server’s memory. In those cases, compare a larger-memory VPS or a GPU-capable host rather than exposing a small machine and hoping optimization will compensate.
The safe default is conservative: install Ollama, keep the API on loopback, validate a model locally, and add private networking or an authenticated TLS proxy only when remote access is required. Treat the published RAM figures as estimates because no official hardware minimum is established here and third-party guides conflict.
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