Ollama vs the OpenAI API: Real Monthly Cost

The OpenAI API charges by the token: every million tokens you send and every million it writes back has a price. Ollama on your own server has no token price; you pay for the server, whatever it processes. That sounds like a clear win for the server, and often it is not. VeloxaHost servers have no GPU, so Ollama runs models on the CPU, and a CPU-only server is slow with large models and runs only small ones well. OpenAI prices below are from its pricing page as of 2026-10-19.

The monthly cost

Ollama here is the one-click Ollama app on Veloxa 4 ($30 a month, $0.05 an hour), its recommended size: 4 vCPU and 8 GB of RAM, enough for one 7B or 8B model. The OpenAI columns use the standard short-context prices per million tokens: gpt-6-luna at $0.10 input and $0.50 output, and gpt-6.1-sol at $2.00 input and $10.00 output.

Tokens a month (input + output)	gpt-6-luna	gpt-6.1-sol	Ollama on VeloxaHost
2M + 0.5M	$0.45	$9.00	$30
10M + 2M	$2.00	$40.00	$30
50M + 10M	$10.00	$200.00	$30, if the server keeps up
200M + 40M	$40.00	$800.00	$30, if the server keeps up

At these mixes, $30 buys about 150 million input and 30 million output tokens of gpt-6-luna. Below that, the API's small model costs less than the server. Above it, the server is cheaper only if it can produce the tokens: 30 million output tokens in a 31-day month means about 11 tokens a second, around the clock, on top of reading every prompt. Whether a CPU-only server sustains that depends on the model and the prompt lengths, so measure it before you plan on it. ollama run <model> --verbose prints the generation rate after each answer.

OpenAI's pricing page lists Batch prices at half the standard rate for these two models (gpt-6-luna at $0.05 input and $0.25 output), which widens the API's lead for work that can wait. Longer prompts are billed at a higher long-context rate.

The comparison is also not like for like. A 7B or 8B model on a CPU is not a substitute for gpt-6.1-sol on harder tasks. The fair matchup for a small local model is the API's small model, and there the API is cheaper at most volumes.

What the VeloxaHost column leaves out

• Speed. Generation on a CPU is much slower than on a GPU, and waits grow with longer answers and bigger models.
• Bigger models. A larger model needs more memory: Veloxa 8 ($60 a month, $0.09 an hour) has 16 GB of RAM, and the comparison shifts further toward the API.
• HTTPS and access control. Ollama has no authentication of its own. Keep its API on the server, or put a proxy with authentication in front of it. HTTPS on port 443 with your domain needs a dedicated IPv4 address, a paid add-on with limited availability; the console shows its current price.
• Your time. You choose models, update Ollama and check each model's license.

Where the OpenAI API is the better pick

• Most volumes. Up to about 150 million input and 30 million output tokens a month, gpt-6-luna costs less than a Veloxa 4.
• Quality on hard tasks. The larger API models do things a small model on a CPU does not.
• Speed and scale. The API answers quickly and handles bursts without you adding servers.
• Uneven use. A quiet month on the API costs almost nothing.

Where self-hosted Ollama is the better pick

• Prompts that must stay on your server. Nothing is sent to a third party, which can matter more than price.
• Steady, high-volume work with a small model. Classification, tagging or extraction running all day, measured and known to fit on the CPU, costs a fixed $30.
• Batch jobs that run for hours, not months. A Veloxa 4 that runs 100 hours for a one-off job costs $5.00; stop or delete it afterwards and the charges stop.
• No per-token surprises. The month is capped at the size's price, however many tokens you process.

FAQ

Can Ollama on VeloxaHost use a GPU?

No. VeloxaHost servers have no GPU, so Ollama runs models on the CPU. That suits small models, batch jobs and internal tools.

Which models fit on a Veloxa 4?

With 8 GB of RAM, one 7B or 8B model fits with room for its context; llama3.1:8b is a 4.9 GB download. Larger models need a bigger size, and run slower on the CPU.

Is Ollama free?

Ollama is released under the MIT license and has no token fee. The models you pull have their own licenses, set by whoever published them. You pay for the server: $30 a month on Veloxa 4.

Can I switch my app from the OpenAI API to Ollama?

Often, if a small model is good enough for the task. Ollama serves a REST API on port 11434. Test the answers on your own prompts before switching, and compare their quality as well as their cost.

What does it cost if I only run Ollama when I need it?

Its hours: $0.05 for each hour a Veloxa 4 runs, up to $30 in a month.