search legion

Price check · Nov 6, 2026

Ollama pricing

Local Ollama use has no subscription. Cloud plans add credits and request caps, but token rates and some annual prices are not listed.

7.0/10Value score

We may earn a commission if you buy through links on this page. It never changes a score or a ranking. How we make money

Short answer

Paid plans start at $16.67/mo. There's also a free plan.

Ollama costs $0 in subscription fees for local models and occasional cloud use on its Pay as you go plan, according to the pricing page. Cloud use is billed per token, but the token rate is not published on the vendor's site. Pro is $20 monthly or $200 annually ($16.67 a month), with $60 in monthly usage credits. Max is $100 monthly; Team is $500 monthly. Running models on your own hardware can avoid Ollama cloud charges, but your hardware still has to run them.

01Every plan, line by line

PlanBilled annuallyBilled monthlyBuilt for
Pay as you go—QuoteLocal models and occasional cloud use
Pro$16.67$20Short, well-defined daily tasks
Max—$100Power users running multiple agents
Team—$500Teams sharing usage and administration
Enterprise—QuoteLarger teams with volume usage pricing

Add-ons and overages

  • Usage credits can be purchased; prices are not published here.
  • Usage beyond Team's included credits is billed as you go from a shared team balance.

02What the plan grid doesn't tell you

Unpublished token rates

Pay as you go is billed per token, but the pricing details do not publish the rate. Estimate cloud costs before relying on it.

Credits have limits

Pro includes $60 in monthly usage credits; Max includes $300 and Team $1,000 shared. The listed plans cap concurrent requests at 3 or 10.

Team usage overages

Usage beyond Team's included credits is billed as you go from a shared team balance. The per-token price is not published.

Missing annual prices

The pricing page lists annual billing for Pro, but not for Max or Team. Usage-credit purchase prices are also not published.

03Which plan should you buy?

If you are…GetWhy
Local model runnersPay as you goIt has a $0 subscription for local models. Cloud use is billed per token, and the rate is not listed.
Daily individual usersProIt costs $20 monthly or $200 annually and includes $60 in monthly usage credits and 3 concurrent requests.
Teams sharing usageTeamIt includes unlimited users, $1,000 in shared monthly credits, 10 concurrent requests and priority support.

04Is Ollama worth the money?

Ollama is worth considering if you want to run open-weight models locally: the listed $0 subscription and offline-use option make it a different cost proposition from cloud-only usage. Paid cloud plans add monthly credits and request limits, but the pricing details do not publish token rates, and Team overages are billed as you go. We would not treat the plan price as a full cloud-cost estimate. Check whether local hardware or the included credits fit your workload before switching.

Cheaper Ollama alternatives →

Ollama pricing FAQ

Does Ollama cost any money?

Local models have a $0 subscription on the Pay as you go plan, according to the pricing page. Cloud use is billed per token, but the rate is not published on the vendor's site. Paid plans start with Pro at $20 monthly, or $200 billed annually.

Is there anything better than Ollama?

That depends on whether you need local inference or managed cloud usage. Ollama supports local and cloud models, plus OpenAI- and Anthropic-compatible endpoints. The published information does not compare it with alternatives, so we would match tools against your hardware, model and cost requirements rather than name a universal winner.

What are the disadvantages of Ollama?

Cloud costs are hard to forecast from the published pricing details because per-token rates are not listed. Paid plans also cap concurrent requests, and annual prices are not listed for Max or Team. For local inference, you need hardware capable of running the models you choose.

Does Ollama run 100% locally?

It can run models on your own hardware, and Ollama offers offline use and private inference. It also offers cloud use, so not every setup is fully local. To keep inference local, use local models rather than cloud usage; the product information does not specify hardware requirements.