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I had no idea they had their own cloud offering, I thought the whole point of Ollama was local models? Why would I pay $20/month to use small inferior models in

I had no idea they had their own cloud offering, I thought the whole point of Ollama was local models? Why would I pay $20/month to use small inferior models instead of using one of the usual AI companies like OpenAI or even Mistral? I'm not going to make an account to use models on my own computer.

mchiang 1y ago
Fair question. Some of the supported models are large and wouldn't fit on most local devices. This is just the beginning, and Ollama does not need to exclude cloud hosted frontier models either with the relationship we've built with the model providers. We just have to be mindful and understand that Ollama stands with developers, and solve the needs. https://ollama.com/cloud https://ollama.com/cloud
- sorenjan 1y ago
  > Some of the supported models are large and wouldn't fit on most local devices. Why would I use those models on your cloud instead of using Google's or Anthropic's models? I'm glad there are open models available and that they get better and better, but if I'm paying money to use a cloud API I might as well use the best commercial models, I think they will remain much better than the open alternatives for quite some time.
  - mchiang 1y ago
    When we started Ollama, we were told how open-source (open-weight wasn't a term back then) will always be inferior to the close-sourced models. This was 2 years ago (Ollama's birthday is July 18th, 2023). Fast forward to now, open models are quickly catching up, and at a significantly lower price point for most and can be customized for specific tasks instead of being general purpose. For general purpose models, absolutely the closed models are currently dominating.
    - typpilol 1y ago
      Ya a lot of ppl don't realize you could spend 2k on a 5090 to run some of the large models. Or spend 20 a month for models even a 5090 couldn't run. And not have to spend your own electricity, hardware, maintenance, updates etc.
      - oytis 1y ago
        20 a month for a commercial model is price dumping financed by investors. For ollama it's hopefully a sustainable price.
        theshrike79 1y ago
        The 20 a month models definitely aren't sustainable. This is why everyone needs to get every flavour and speedrun building all the tools they need when the infinite money faucets are turned off. At some point companies will start raising prices or moving towards per-token pricing (Which is sustainable, but expensive).
        gunalx 1y ago
        Depends. API pricing from oss model inference providers basically has to be sustainable, because of competition in the space. And with that in mind, i definetly dont use more than a couple of bucks a month in API refils. (not that i really am a power user or anything) So if you consider the 20 bucks to be balanced between poer and non power users, and with the existing rate limits, its probably not that far off being profitable, at least on the pure inference side.
  - ineedasername 1y ago
    A person can use Google’s Gemma models on ollama’s cloud and possibly pay less. And have more quality control that way (and other types of control I guess) since there is no don’t need to wonder if a recent model update or load balance throttling impacted results. Your use case doesn’t generalize.
- disiplus 1y ago
  hi, to me this sounds like you are going into the direction of openrouter.
ricardobeat 1y ago
For models you can't run locally like gpt-oss-120b, deepseek or qwen3-coder 480b. And a way for them to monetize the success of Ollama.
dcreater 1y ago
Yeah it's been a steady pivot to profitable features. Wonderful to see them build a reputation through FOSS and codebase from free labor to then cash in.
- all2 1y ago
  What sort of monetization model would you like to see? What model would you deem acceptable?
  - dcreater 1y ago
    Ollama , the local inference platform, stays completely local. Maintained by a non-profit org with dev time contributed to by a for-profit company. That company can be VC backed and can make their cloud inference platform. And can use ollama as its backed, as a platform to market etc. But keep it as a separate product (not named ollama). This is almost exactly how duckdb/motherduck functions and I think theyre doing an excellent job. EDIT: grammar and readability
    - discardedrefuse 1y ago
      You might want to check out RamaLama. It's a container based replacement for Ollama by the same folks that brought us Podman. I tried it a while back, I was very surprised to find that simply running `uvx ramalama run deepseek-r1:1.5b` just worked. I'm on Fedora Silverblue with nothing layered on the ostree. Before RamaLama, getting llama.cpp working with my GPU was a major PITA. https://github.com/containers/ramalama https://github.com/containers/ramalama
  - troyvit 1y ago
    If I were them I'd go whole-hog on local models and: * Work with somebody like System76 or Framework to create great hardware systems come with their ecosystem preinstalled. * Build out a PaaS, perhaps in partnership with an existing provider, that makes it easy for anybody to do what Ollama search does. I'm more than half certain I could convince our cash strapped organization to ditch elastic search for that. * Partner with Home Assistant, get into home automation and wipe the floor with Echo and its ilk (yeah basically resurrect Mycroft but add whole-house automation to it). Each of those are half-baked, but it also took me 7 minutes to come up with them, and they seem more in line with what Ollama tries to represent than a pure cloud play using low-power models.
kordlessagain 1y ago
You make an account to use their hosted models AND to have them available via the Ollama API LOCALLY. I'm spending $100 on Claude and $200 on GPT5, so $20 bucks is NOTHING and totally worth having access to: Qwen3 235b Deepseek 3.1 671b (thinking and non thinking) Llama 3.1 405b GPT OSS 120b Those are hardly "small inferior models". What is really cool is that you can set Codex up to use Ollama's API and then have it run tools on different models.
- n4bz0r 1y ago
  Has anyone tried the hosted models? How do they compare to GPT-5? I was thinking about trying ChatGPT Pro, but I seem to have completely missed that they bumped the price from $100 to $200. It was $100 just a while ago, right? Before GPT-5, I assume.
  - pama 1y ago
    No it was never $100 for ChatGPT Pro.
- mrheosuper 1y ago
  If you are on $100 tier Claude, what makes you think the $20 Tier Ollama is enough for you ?
  - theshrike79 1y ago
    If your workflow is general enough, you can (and should) switch between models. They all have different styles and blind spots. Like I had Codex + gpt-5-codex (20€ tier) build me a network connectivity monitor for my very specific use case. It worked, but had some really weird choices. Gave it to Claude Code (20€ tier again) and it immediately found a few issues and simplifications.
    - kordlessagain 1y ago
      Right. And then there's using an MCP tool that instantiates another agent except uses a different model. Here's a good example. For summarization of a page of content. Content is maybe pulled down by an agentic crawler, so using a local model to summarize is great. It's fast, doesn't cost anything (or much) and I can run it without guardrails as it doesn't represent a cost risk if it ran out of control.
zmmmmm 1y ago
a lot of "local" models are still very large to download and slow to run on regular hardware. I think it's great to have a way to evaluate them cheaply in the cloud before deciding to pull down the model to run locally. At some level it's also more of a principle that I could run something locally that matters rather than actually doing it. I don't want to become dependent on technology that someone could take away from me.

mchiang 1y ago

Fair question. Some of the supported models are large and wouldn't fit on most local devices. This is just the beginning, and Ollama does not need to exclude cloud hosted frontier models either with the relationship we've built with the model providers. We just have to be mindful and understand that Ollama stands with developers, and solve the needs. https://ollama.com/cloud https://ollama.com/cloud

sorenjan 1y ago
> Some of the supported models are large and wouldn't fit on most local devices. Why would I use those models on your cloud instead of using Google's or Anthropic's models? I'm glad there are open models available and that they get better and better, but if I'm paying money to use a cloud API I might as well use the best commercial models, I think they will remain much better than the open alternatives for quite some time.
- mchiang 1y ago
  When we started Ollama, we were told how open-source (open-weight wasn't a term back then) will always be inferior to the close-sourced models. This was 2 years ago (Ollama's birthday is July 18th, 2023). Fast forward to now, open models are quickly catching up, and at a significantly lower price point for most and can be customized for specific tasks instead of being general purpose. For general purpose models, absolutely the closed models are currently dominating.
  - typpilol 1y ago
    Ya a lot of ppl don't realize you could spend 2k on a 5090 to run some of the large models. Or spend 20 a month for models even a 5090 couldn't run. And not have to spend your own electricity, hardware, maintenance, updates etc.
    - oytis 1y ago
      20 a month for a commercial model is price dumping financed by investors. For ollama it's hopefully a sustainable price.
      - theshrike79 1y ago
        The 20 a month models definitely aren't sustainable. This is why everyone needs to get every flavour and speedrun building all the tools they need when the infinite money faucets are turned off. At some point companies will start raising prices or moving towards per-token pricing (Which is sustainable, but expensive).
      - gunalx 1y ago
        Depends. API pricing from oss model inference providers basically has to be sustainable, because of competition in the space. And with that in mind, i definetly dont use more than a couple of bucks a month in API refils. (not that i really am a power user or anything) So if you consider the 20 bucks to be balanced between poer and non power users, and with the existing rate limits, its probably not that far off being profitable, at least on the pure inference side.
- ineedasername 1y ago
  A person can use Google’s Gemma models on ollama’s cloud and possibly pay less. And have more quality control that way (and other types of control I guess) since there is no don’t need to wonder if a recent model update or load balance throttling impacted results. Your use case doesn’t generalize.
disiplus 1y ago
hi, to me this sounds like you are going into the direction of openrouter.

ricardobeat 1y ago

For models you can't run locally like gpt-oss-120b, deepseek or qwen3-coder 480b. And a way for them to monetize the success of Ollama.

dcreater 1y ago

Yeah it's been a steady pivot to profitable features. Wonderful to see them build a reputation through FOSS and codebase from free labor to then cash in.

all2 1y ago
What sort of monetization model would you like to see? What model would you deem acceptable?
- dcreater 1y ago
  Ollama , the local inference platform, stays completely local. Maintained by a non-profit org with dev time contributed to by a for-profit company. That company can be VC backed and can make their cloud inference platform. And can use ollama as its backed, as a platform to market etc. But keep it as a separate product (not named ollama). This is almost exactly how duckdb/motherduck functions and I think theyre doing an excellent job. EDIT: grammar and readability
  - discardedrefuse 1y ago
    You might want to check out RamaLama. It's a container based replacement for Ollama by the same folks that brought us Podman. I tried it a while back, I was very surprised to find that simply running `uvx ramalama run deepseek-r1:1.5b` just worked. I'm on Fedora Silverblue with nothing layered on the ostree. Before RamaLama, getting llama.cpp working with my GPU was a major PITA. https://github.com/containers/ramalama https://github.com/containers/ramalama
- troyvit 1y ago
  If I were them I'd go whole-hog on local models and: * Work with somebody like System76 or Framework to create great hardware systems come with their ecosystem preinstalled. * Build out a PaaS, perhaps in partnership with an existing provider, that makes it easy for anybody to do what Ollama search does. I'm more than half certain I could convince our cash strapped organization to ditch elastic search for that. * Partner with Home Assistant, get into home automation and wipe the floor with Echo and its ilk (yeah basically resurrect Mycroft but add whole-house automation to it). Each of those are half-baked, but it also took me 7 minutes to come up with them, and they seem more in line with what Ollama tries to represent than a pure cloud play using low-power models.

kordlessagain 1y ago

You make an account to use their hosted models AND to have them available via the Ollama API LOCALLY. I'm spending $100 on Claude and $200 on GPT5, so $20 bucks is NOTHING and totally worth having access to: Qwen3 235b Deepseek 3.1 671b (thinking and non thinking) Llama 3.1 405b GPT OSS 120b Those are hardly "small inferior models". What is really cool is that you can set Codex up to use Ollama's API and then have it run tools on different models.

n4bz0r 1y ago
Has anyone tried the hosted models? How do they compare to GPT-5? I was thinking about trying ChatGPT Pro, but I seem to have completely missed that they bumped the price from $100 to $200. It was $100 just a while ago, right? Before GPT-5, I assume.
- pama 1y ago
  No it was never $100 for ChatGPT Pro.
mrheosuper 1y ago
If you are on $100 tier Claude, what makes you think the $20 Tier Ollama is enough for you ?
- theshrike79 1y ago
  If your workflow is general enough, you can (and should) switch between models. They all have different styles and blind spots. Like I had Codex + gpt-5-codex (20€ tier) build me a network connectivity monitor for my very specific use case. It worked, but had some really weird choices. Gave it to Claude Code (20€ tier again) and it immediately found a few issues and simplifications.
  - kordlessagain 1y ago
    Right. And then there's using an MCP tool that instantiates another agent except uses a different model. Here's a good example. For summarization of a page of content. Content is maybe pulled down by an agentic crawler, so using a local model to summarize is great. It's fast, doesn't cost anything (or much) and I can run it without guardrails as it doesn't represent a cost risk if it ran out of control.

zmmmmm 1y ago

a lot of "local" models are still very large to download and slow to run on regular hardware. I think it's great to have a way to evaluate them cheaply in the cloud before deciding to pull down the model to run locally. At some level it's also more of a principle that I could run something locally that matters rather than actually doing it. I don't want to become dependent on technology that someone could take away from me.