Nice release. Part of the problem right now with OSS models (at least for enterprise users) is the diversity of offerings in terms of:
- Speed
- Cost
- Reliability
- Feature Parity (eg: context caching)
- Performance (What quant level is being used...really?)
- Host region/data privacy guarantees
- LTS
And that's not even including the decision of what model you want to use!
Realistically if you want to use an OSS model instead of the big 3, you're faced with evalutating models/providers across all these axes, which can require a fair amount of expertise to discern. You may even have to write your own custom evaluations. Meanwhile Anthropic/OAI/Google "just work" and you get what it says on the tin, to the best of their ability. Even if they're more expensive (and they're not that much more expensive), you are basically paying for the priviledge of "we'll handle everything for you".
I think until providers start standardizing OSS offerings, we're going to continue to exist in this in-between world where OSS models theoretically are at performance parity with closed source, but in practice aren't really even in the running for serious large scale deployments.
I wouldn't be surprised if those undeleted chats or some inferred data that is based on it is part of the gpt-5 training data. Somehow I don't trust this sama guy at all.
I see a lot of hate for ollama doing this kind of thing but also they remain one of the easiest to use solutions for developing and testing against a model locally.
Sure, llama.cpp is the real thing, ollama is a wrapper... I would never want to use something like ollama in a production setting. But if I want to quickly get someone less technical up to speed to develop an LLM-enabled system and run qwen or w/e locally, well then its pretty nice that they have a GUI and a .dmg to install.
Since the new multimodal engine, Ollama has moved off of llama.cpp as a wrapper. We do continue to use the GGML library, and ask hardware partners to help optimize it.
Ollama might look like a toy and what looks trivial to build. I can say, to keep its simplicity, we go through a deep amount of struggles to make it work with the experience we want.
Simplicity is often overlooked, but we want to build the world we want to see.
But Ollama is a toy, it's meaningful for hobbyists and individuals to use locally like myself. Why would it be the right choice for anything more? AWS, vLLM, SGLang etc would be the solutions for enterprise
I knew a startup that deployed ollama on a customers premises and when I asked them why, they had absolutely no good reason. Likely they did it because it was easy. That's not the "easy to use" case you want to solve for.
> Ollama has moved off of llama.cpp as a wrapper. We do continue to use the GGML library
Where can I learn more about this? llama.cpp is an inference application built using the ggml library. Does this mean, Ollama now has it's own code for what llama.cpp does?
vllm and ollama assume different settings and hardware. Vllm backed by the paged attention expect a lot of requests from multiple users whereas ollama is usually for single user on a local machine.
It is weird but when I tried new gpt-oss:b20 model locally llama.cpp just failed instantly for me. At the same time under ollama it worked (very slow but anyway). I didn't find how to deal with llama.cpp but ollama definitely doing something under the hood to make models work.
Ollama is great but I feel like Georgi Gerganov deserves way more credit for llama.cpp.
He (almost) single-handedly brought LLMs to the masses.
With the latest news of some AI engineers' compensation reaching up to a billion dollars, feels a bit unfair that Georgi is not getting a much larger slice of the pie.
Ollama is not a wrapper around llama.cpp anymore, at least for multimodal models (not sure about others). They have their own engine: https://ollama.com/blog/multimodal-models
`ggerganov` is one of the most under-rated and under-appreciated hackers maybe ever. His name belongs next to like Carmack and other people who made a new thing happen on PCs. And don't forget the shout out to `TheBloke` who like single-handedly bootstrapped the GGUF ecosystem of useful model quants (I think he had a grant from pmarca or something like that, so props to that too).
Is Georgi landing any of those big-time money jobs? I could see a conflict-of-interest given his involvment with llama.cpp, but I would think he'd be well positioned for something like that
Seriously, people astroturfing this thread by saying ollama has a new engine. It literally is the same engine that llama.cpp uses and georgi and slaren maintain! VC funding will make people so dishonest and just plain grifters
No one is astroturfing. You cannot run any model with just GGML. It's a tensor library. Yes, it adds value, but I don't think that saying that ollama also does is unfair.
The issue is not companies but governance. OSS licenses and companies are fine. Companies have a natural conflict of interest that can lead them to take software projects they control in a direction that suits their revenue goals but not necessarily the needs/wants of its users. That happens over and over again. It's their nature. This can means changes in direction/focus or worst case license changes that limit what you can do.
The solution is having proper governance for OSS projects that matter with independent organizations made up of developers, companies, and users taking care of the governance. A lot of projects that have that have last for decades and will likely survive for decades more.
And part of that solution is to also steer clear of projects without that. I've been burned a couple of times now getting stuck with OSS components where the license was changed and the companies behind it had their little IPOs and started serving share holders instead of users (elastic, redis, mongo, etc). I only briefly used Mongo and I got a whiff of where things were going and just cut loose from it. With Elastic the license shenenigans started shortly after their IPO and things have been very disruptive to the community (with half using Opensearch now). With Redis I planned the switch to Valkey the second it was announced. Clear cut case of cutting loose. Valkey looks like it has proper governance. Redis never had that.
Ollama seems relatively OK by this benchmark. The software (ollama server) is MIT licensed and there appears to be no contributor license agreement in place. But it's a small group of people that do most of the coding and they all work for the same vc funded company behind ollama. That's not proper governance. They could fail. They could relicense. They could decide that they don't like open source after all. Etc. Worth considering before you bet your company on making this a foundational piece of your tech stack.
I view it a bit like I do cloud gaming, 90% of the time I'm fine with local use, but sometimes it's just more cost effective to offload the cost of hardware to someone else. But it's not an all-or-nothing decision.
Yep, if you just want to play one or two games at 4k HDR etc. it's a lot cheaper to pay 22€ for GeForce Now Ultimate vs. getting a whole-ass gaming PC capable of the same.
Any more information on "Privacy first"? It seems pretty thin if just not retaining data.
For Draw Things provided "Cloud Compute", we don't retain any data too (everything is done in RAM per request). But that is still unsatisfactory personally. We will soon add "privacy pass" support, but still not to the satisfactory. Transparency log that can be attested on the hardware would be nice (since we run our open-source gRPCServerCLI too), but I just don't know where to start.
In theory, "privacy pass" should help, as you can subpoena content, but cannot know who made these. But that is still thin (and Ollama not doing that too anyway).
I’d love to learn more about your project. I’m using socialized cloud regions for AI security and they really lag the mainstream. Definitely need more options here.
Edit: emailed the address on the site in your profile, got an inbox does not exist error.
I would pay more if they let you run the models in Switzerland or some other GDPR respecting country, even if there was extra latency. I would also hope everything is being sent over SSL or something similar.
What could be the benefit of paying $20 to Ollama to run inferior models instead of paying the same amount of money to e.g. OpenAI for access to sota models?
I feel the primary benefit of this Ollama Turbo is that you can quickly test and run different models in the cloud that you could run locally if you had the correct hardware.
This allows you to try out some open models and better assess if you could buy a dgx box or Mac Studio with a lot of unified memory and build out what you want to do locally without actually investing in very expensive hardware.
Certain applications require good privacy control and on-prem and local are something certain financial/medical/law developers want. This allows you to build something and test it on non-private data and then drop in real local hardware later in the process.
> quickly test and run different models in the cloud that you could run locally if you had the correct hardware.
I feel like they're competing against Hugging Face or even Colaboratory then if this is the case.
And for cases that require strict privacy control, I don't think I'd run it on emergent models or if I really have to, I would prefer doing so on an existing cloud setup already that has the necessary trust / compliance barriers addressed. (does Ollama Turbo even have their Trust center up?)
I can see its potential once it gets rolling, since there's a lot of ollama installations out there.
Running models without a filter on it. OpenAI has an overzealous filter and won’t even tell you what you violated. So you have to do a dance with prompts to see if it’s copyright, trademark or whatever. Recently it just refused to answer my questions and said it wasn’t true that a civil servant would get fired for releasing a report per their job duties. Another dance sending it links to stories that it was true so it could answer my question. I want a LLMs without training wheels.
totally respect your choice, and it's a great project too. Of course as a maintainer of Ollama, my preference is to win you over with Ollama. If it doesn't meet your needs, it's okay. We are more energized than ever to keep improving Ollama. Hopefully one day we will win you back.
Ollama does not use llama.cpp anymore; we do still keep it and occasionally update it to remain compatible for older models for when we used it. The team is great, we just have features we want to build, and want to implement the models directly in Ollama. (We do use GGML and ask partners to help it. This is a project that also powers llama.cpp and is maintained by that same team)
I won't use `ollama` on principle. I use `llama-cli` and `llama-server` if I'm not linking `ggml`/`gguf` directly. It's like, two extra commands to use the one by the genius that wrote it and not the one that the guys just jacked it.
The models are on HuggingFace and downloading them is `uvx huggingface-cli`, the `GGUF` quants were `TheBloke` (with a grant from pmarca IIRC) for ages and now everyone does them (`unsloth` does a bunch of them).
Maybe I've got it twisted, but it seems to be that the people who actually do `ggml` aren't happy about it, and I've got their back on this.
Interesting, admittedly, I am slowly getting to the point, where ollama's defaults get a little restrictive. If the setup is not too onerous, I would not mind trying. Where did you start?
First, I must say I appreciate you taking the time to be engaged on this thread and responding to so many of us.
What I'm referring to is a broader pattern that I (and several) others have been seeing. Of the top of my head: not crediting llama.cpp previously, still not crediting llama.cpp now and saying you are using your own inference engine when you are still using ggml and the core of what Georgi made, most importantly why even create your own version - is it not better for the community to just contribute to llama.cpp?, making your own propreitary model storage platform disallowing using weights with other local engines requiring people to duplicate downloads and more.
I dont know how to regard these other than being largely motivated out of self interest.
I think what Jeff and you have built have been enormously helpful to us - Ollama is how I got started running models locally and have enjoyed using it for years now. For that, I think you guys should be paid millions. But what I fear is going to happen is you guys will go the way of the current dogma of capturing users (at least in mindshare) and then continually squeezing more. I would love to be wrong, but I am not going to stick around to find out as its risk I cannot take.
Yes, better to get free sh*t unsustainably. By the way, you're free to create an open source alternative and pour your time into that so we can all benefit. But when you don't — remember I called it!
What? The obvious move is to never have switched to Ollama and just use Llama.cpp directly, which I've been doing for years. Llama.cpp was created first, is the foundation for this product, and is actually open source.
I am so so so confused as to why Ollama of all companies did this other than an emblematic stab at making money-perhaps to appease someone putting pressure on them to do so. Their stuff does a wonderful job of enabling local for those who want it. So many things to explore there but instead they stand up yet another cloud thing? Love Ollama and hope it stays awesome
The problem is that OSS is free to use but it is not free to create or maintain. If you want it to remain free to use and also up to date, Ollama will need someone to address issues on GitHub. Usually people want to be paid money for that.
money is great! I like money! but if this is their version of buy me a coffee I think there’s room to run elsewhere for their skillset/area of expertise
For one of the top local open model inference engines of choice - only supporting OSS out of the gate feels like an angle to just ride the hype knowing OSS is announced today "oh OSS came out and you can use Ollama Turbo to use it"
The subscription based pricing is really interesting. Other players offer this but not for API type services. I always imagine that there will be a real pricing war with LLMs with time / as capabilities mature, and going monthly pricing on API services is possibly a symptom of that
What does this mean for the local inference engine? Does Ollama have enough resources to maintain both?
It says “usage-based pricing” is coming soon. I think that is the sweet spot for a service like this.
I pay $20 to Anthropic, so I don’t think I’d get enough use out of this for the $20 fee. But being able to spin up any of these models and use as needed (and compare) seems extremely useful to me.
> It says “usage-based pricing” is coming soon. I think that is the sweet spot for a service like this.
Agreed, though there are already several providers of these new OpenAI models available, so I'm not sure what ollama's value add is there (there are plenty of good chat/code/etc interfaces available if you are bringing your own API keys).
A flat fee service for open-source LLMs is somewhat unique, even if I don't see myself paying for it.
Usage-based pricing would put them in competition with established services like deepinfra.com, novita.ai, and ultimately openrouter.ai. They would go in with more name-recognition, but the established competition is already very competitive on pricing
I do hope Ollama got a good paycheck from that, as they are essentially help OpenAI to oss-wash their image with the goodwill that Ollama has built up.
That'll be an uphill battle on value proposition tbh. $20 a month for access to a widely available MoE 120B with ~5B active parameters at unspecified usage limits?
I guess their target audience values convenience and easy of use above all else so that could play well there maybe.
Does this mean we can access Ollama APIs for $20/mo and test them without running the model locally? I'm not hardware-rich, but for some projects, I'd like a reliable pricing.
If any of the major inference engines - vLLM, Sglang, llama.cpp - incorporated api driven model switching, automatic model unload after idle and automatic CPU layer offloading to avoid OOM it would avoid the need for ollama.
Interesting - it does indeed seem like llama-server has the needed endpoints to do the model swapping and llama.cpp as of recently also has a new flag for the dynamic CPU offload now.
However the approach to model swapping is not 'ollama compatible' which means all the OSS tools supporting 'ollama' Ex Openwebui, Openhands, Bolt.diy, n8n, flowise, browser-use etc.. aren't able to take advantage of this particularly useful capability as best I can tell.
For production use of open weight models I'd use something like Amazon Bedrock, Google Vertex AI (which uses vLLM), or on-prem vLLM/SGLang. But for a quick assessment of a model as a developer, Ollama Turbo looks appealing. I find Google GCP incredibly user hostile and a nightmare to navigate quotas and stuff.
More than one year in and Ollama still doesn't support Vulkan inference. Vulkan is essential for consumer hardware. Ollama is a failed project at this point: https://news.ycombinator.com/item?id=42886680
There's an open pull request https://github.com/ollama/ollama/pull/9650 but it needs to be forward ported/rebased to the current version before the maintainers can even consider merging it.
Also realistically, Vulkan Compute support mostly helps iGPU's and older/lower-end dGPU's, which can only bring a modest performance speed up in the compute-bound preprocessing phase (because modern CPU inference wins in the text-generation phase due to better memory bandwidth). There are exceptions such as modern Intel dGPU's or perhaps Macs running Asahi where Vulkan Compute can be more broadly useful, but these are also quite rare.
Is there an evaluation of such services available anywhere. Looking for recommendations for similar services with usage based pricing and pro-and-cons.
ps: looking for most economic one to play around with as long as it a decent enough experience (minimal learning curve). buy, happy to pay too
OpenRouter is great. Less privacy I guess, but you pay for usage and you have access to hundreds of models. They have free models too, albeit rate-limited.
I think what matters more here is "All hardware is located outside of China". Located in the US means little because that's not good enough for many regulated industries even within the US.
All things considered though, Europe is getting confusing. They have GDPR but now pushing to backdoor encryption within the EU? [1]
At least there isn't a strong movement in the US trying to outlaw E2E encryption.
Which brings up the point are truly private LLMs possible? Where the input I provide is only meaningful to me, but the LLM can still transform it without gaining any contextual value out of it? Without sharing a key? If this can be done, can it be done performantly?
No I think the point is to choose the best jurisdiction to have cloud hosted data where your data is best protected from access by very wealthy entities via intelligence services bribery. That’s still hands down the USA.
at this point, can i purchase the subscription directly from the model provider or hugging face and use it? or is this ollama attempt to become a provider like them.
Often the math works out that you get a lot more for $20 a month if you settle for smaller sized but capable models (8b-30b). I don’t see how it’s better other than Ollama can “promise” they don’t store your data where as OpenRouter is dependent on which host you choose (and there’s no indicator on OpenRouter exposing which ones do or don’t).
In a universe where everything you say can be taken out of context, things like OpenAi will be a data leak nightmare.
Watching ollama pivot from a somewhat scrappy yet amazingly important and well designed open source project to a regular "for-profit company" is going to be sad.
Thankfully, this may just leave more room for other open source local inference engines.
we have always been building in the open, and so is Ollama. All the core pieces of Ollama are open. There are areas where we want to be opinionated on the design to build the world we want to see.
There are areas we will make money, and I wholly believe if we follow our conscious we can create something amazing for the world while making sure we can keep it fueled to keep it going for the long term.
Some of the ideas in Turbo mode (completely optional) is to serve the users who want a faster GPU, and adding in additional capabilities like web search. We loved the experience so much that we decided to give web search to non-paid users too. (Again, it's fully optional). Now to prevent abuse and make sure our costs don't go out of hand, we require login.
Can't we all just work together and create a better world? Or does it have to be so zero sum?
I wanted to try web search to increase my privacy but it wanted to do login.
For Turbo mode I understand the need for paying but the main poing of running a local model with web search is browsing from my computer without using any LLM provider. Also I want to get rid of the latency to US servers from Europe.
I think this offering is a perfectly reasonable option for them to make money. We all have bills to pay, and this isn't interfering with their open source project, so I don't see anything wrong with it.
>> Watching ollama pivot from a somewhat scrappy yet amazingly important and well designed open source project to a regular "for-profit company" is going to be sad.
if i could have consistent and seamless local-cloud dev that would be a nice win. everyone has to write things 3x over these days depending on your garden of choice, even with langchain/llamaindex
I don't blame them. As soon as they offer a few more models available with the Turbo mode I plan on subscribing to their Turbo plan for a couple of months - a buying them a coffee, or keeping the lights on kind of thing.
The Ollama app using the signed-in-only web search tool is really pretty good.
It was always just a wrapper around the real well designed OSS, llama.cpp. Ollama even messes up the names of models by calling distilled models the name of the actual one, such as DeepSeek.
Ollama's engineers created Docker Desktop, and you can see how that turned out, so I don't have much faith in them to continue to stay open given what a rugpull Docker Desktop became.
Same, was just after a small lightweight solution where I can download, manage and run local models. Really not a fan of boarding the enshittification train ride with them.
Always had a bad feeling when they didn't give ggerganov/llama.cpp their deserved credit for making Ollama possible in the first place, if it were a true OSS project they would have, but now makes more sense through the lens of a VC-funded project looking to grab as much marketshare as possible to avoid raising awareness for alternatives in OSS projects they depend on.
Together with their new closed-source UI [1] it's time for me to switch back to llama.cpp's cli/server.
> Repackaging existing software while literally adding no useful functionality was always their gig.
Developers continue to be blind to usability and UI/UX. Ollama lets you just install it, just install models, and go. The only other thing really like that is LM-Studio.
It's not surprising that the people behind it are Docker people. Yes you can do everything Docker does with Linux kernel and shell commands, but do you want to?
Making software usable is often many orders of magnitude more work than making software work.
I'm not sure which package we use that is triggering this. My guess is llama.cpp based on what I see on social? Ollama has long shifted to using our own engine. We do use llama.cpp for legacy and backwards compatibility. I want to be clear it's not a knock on the llama.cpp project either.
There are certain features we want to build into Ollama, and we want to be opinionated on the experience we want to build.
Have you supported our past gigs before? Why not be more happy and optimistic in seeing everyone build their dreams (success or not).
If you go build a project of your dreams, I'd be supportive of it too.
Why does everything AI-related have to be $20? Why can't there be tiers? OpenAI setting the standard of $20/m for every AI application is one of the worst things to ever happen.
I should have specified less expensive tiers (below the $20 standard). A tier <= $10 would be great. Anything over $10 for casual use seems excessive (or at least from my perspective)
My guess is that’s the lowest price point that provides a modicum of profitability — LLMs are quite expensive to run, and even more so for providers like Ollama, which are entering the market and don’t have idle capacity.
Claude has $20, $100 and $200, ChatGPT $20, and $200, Google has $20 and $250. Those all have free tiers as well, and metered APIs. Grok has $30 and $300 it looks like, the list probably goes on and on.
Ollama at its core will always be open. Not all users have the computer to run models locally, and it is only fair if we provide GPUs that cost us money and let the users who optionally want it to pay for it.
I think it’s the logical move to ensure Ollama can continue to fund development. I think you will probably end up having to add more tiers or some way for users to buy more credits/gpu time. See anthropic’s recent move with Claude code due to the usage of a number of 24/7 users.
I’m not throwing the towel on Ollama yet. They do need dollars to operate, but still provide excellent software for running models locally and without paying them a dime.
I like how the landing page (and even this HN page until this point) completely miss any reference to Meta and Facebook.
The landing page promises privacy but anyone who knows how FB used VPN software to spy on people, knows that as long as the current leadership is in place, we shouldn't assume they've all of a sudden became fans of our privacy.
Ollama isn’t connected to Meta besides offering Llama as one of the potential models you can run.
There is obviously some connection to Llama (the original models giving rise to llama.cpp which Ollama was built on) but the companies have no affiliation.
Nice release. Part of the problem right now with OSS models (at least for enterprise users) is the diversity of offerings in terms of:
- Speed
- Cost
- Reliability
- Feature Parity (eg: context caching)
- Performance (What quant level is being used...really?)
- Host region/data privacy guarantees
- LTS
And that's not even including the decision of what model you want to use!
Realistically if you want to use an OSS model instead of the big 3, you're faced with evalutating models/providers across all these axes, which can require a fair amount of expertise to discern. You may even have to write your own custom evaluations. Meanwhile Anthropic/OAI/Google "just work" and you get what it says on the tin, to the best of their ability. Even if they're more expensive (and they're not that much more expensive), you are basically paying for the priviledge of "we'll handle everything for you".
I think until providers start standardizing OSS offerings, we're going to continue to exist in this in-between world where OSS models theoretically are at performance parity with closed source, but in practice aren't really even in the running for serious large scale deployments.
true but ignores handing over all your prompt traffic without any real legal protections as sama has pointed out:
[1] https://californiarecorder.com/sam-altman-requires-ai-privil...
I wouldn't be surprised if those undeleted chats or some inferred data that is based on it is part of the gpt-5 training data. Somehow I don't trust this sama guy at all.
> OpenAI confirmed it has been preserving deleted and non permanent person chat logs since mid-Might 2025 in response to a federal court docket order
> The order, embedded under and issued on Might 13, 2025, by U.S. Justice of the Peace Decide Ona T. Wang
Is this some meme where “may” is being replaced with “might”, or some word substitution gone awry? I don’t get it.
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Gpt-oss comes only in 4.5 bit quant. This is the native model, so there's no fp16 original
I see a lot of hate for ollama doing this kind of thing but also they remain one of the easiest to use solutions for developing and testing against a model locally.
Sure, llama.cpp is the real thing, ollama is a wrapper... I would never want to use something like ollama in a production setting. But if I want to quickly get someone less technical up to speed to develop an LLM-enabled system and run qwen or w/e locally, well then its pretty nice that they have a GUI and a .dmg to install.
Thanks for the kind words.
Since the new multimodal engine, Ollama has moved off of llama.cpp as a wrapper. We do continue to use the GGML library, and ask hardware partners to help optimize it.
Ollama might look like a toy and what looks trivial to build. I can say, to keep its simplicity, we go through a deep amount of struggles to make it work with the experience we want.
Simplicity is often overlooked, but we want to build the world we want to see.
But Ollama is a toy, it's meaningful for hobbyists and individuals to use locally like myself. Why would it be the right choice for anything more? AWS, vLLM, SGLang etc would be the solutions for enterprise
I knew a startup that deployed ollama on a customers premises and when I asked them why, they had absolutely no good reason. Likely they did it because it was easy. That's not the "easy to use" case you want to solve for.
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> Ollama has moved off of llama.cpp as a wrapper. We do continue to use the GGML library
Where can I learn more about this? llama.cpp is an inference application built using the ggml library. Does this mean, Ollama now has it's own code for what llama.cpp does?
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This kind of gaslighting is exactly why I stopped using Ollama.
GGML library is llama.cpp. They are one and the same.
Ollama made sense when llama.cpp was hard to use. Ollama does not have value preposition anymore.
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> I would never want to use something like ollama in a production setting.
We benchmarked vLLM and Ollama on both startup time and tokens per seconds. Ollama comes at the top. We hope to be able to publish these results soon.
you need to benchmark against llama.cpp as well.
Did you test multi-user cases?
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vllm and ollama assume different settings and hardware. Vllm backed by the paged attention expect a lot of requests from multiple users whereas ollama is usually for single user on a local machine.
It is weird but when I tried new gpt-oss:b20 model locally llama.cpp just failed instantly for me. At the same time under ollama it worked (very slow but anyway). I didn't find how to deal with llama.cpp but ollama definitely doing something under the hood to make models work.
> I would never want to use something like ollama in a production setting
If you can't get access to "real" datacenter GPUs for any reason and essentially do desktop, clientside deploys, it's your best bet.
It's not a common scenario, but a desktop with a 4090 or two is all you can get in some organizations.
Ollama is great but I feel like Georgi Gerganov deserves way more credit for llama.cpp.
He (almost) single-handedly brought LLMs to the masses.
With the latest news of some AI engineers' compensation reaching up to a billion dollars, feels a bit unfair that Georgi is not getting a much larger slice of the pie.
Agreed. Ollama itself is kind a wrapper around llamacpp anyway. Feel like the real guy is not included to the process.
Now I am going to go and write a wrapper around llamacpp, that is only open source, truly local.
How can I trust ollama to not to sell my data.
Ollama only uses llamacpp for running legacy models. gpt-oss runs entirely in the ollama engine.
You don't need to use Turbo mode; it's just there for people who don't have capable enough GPUs.
Ollama is not a wrapper around llama.cpp anymore, at least for multimodal models (not sure about others). They have their own engine: https://ollama.com/blog/multimodal-models
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`ggerganov` is one of the most under-rated and under-appreciated hackers maybe ever. His name belongs next to like Carmack and other people who made a new thing happen on PCs. And don't forget the shout out to `TheBloke` who like single-handedly bootstrapped the GGUF ecosystem of useful model quants (I think he had a grant from pmarca or something like that, so props to that too).
Is Georgi landing any of those big-time money jobs? I could see a conflict-of-interest given his involvment with llama.cpp, but I would think he'd be well positioned for something like that
https://ggml.ai/
> ggml.ai is a company founded by Georgi Gerganov to support the development of ggml. Nat Friedman and Daniel Gross provided the pre-seed funding.
(This is mere speculation)
I think he's happy doing his own thing.
But then, if someone came in with a billion ... who wouldn't give it a thought?
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Seriously, people astroturfing this thread by saying ollama has a new engine. It literally is the same engine that llama.cpp uses and georgi and slaren maintain! VC funding will make people so dishonest and just plain grifters
No one is astroturfing. You cannot run any model with just GGML. It's a tensor library. Yes, it adds value, but I don't think that saying that ollama also does is unfair.
Interested to see how this plays out - I feel like Ollama is synonymous with "local".
There's a small but vocal minority of users who don't trust big companies, but don't mind paying small companies for a similar service.
I'm also interested to see if that small minority of people are willing to pay for a service like this.
The issue is not companies but governance. OSS licenses and companies are fine. Companies have a natural conflict of interest that can lead them to take software projects they control in a direction that suits their revenue goals but not necessarily the needs/wants of its users. That happens over and over again. It's their nature. This can means changes in direction/focus or worst case license changes that limit what you can do.
The solution is having proper governance for OSS projects that matter with independent organizations made up of developers, companies, and users taking care of the governance. A lot of projects that have that have last for decades and will likely survive for decades more.
And part of that solution is to also steer clear of projects without that. I've been burned a couple of times now getting stuck with OSS components where the license was changed and the companies behind it had their little IPOs and started serving share holders instead of users (elastic, redis, mongo, etc). I only briefly used Mongo and I got a whiff of where things were going and just cut loose from it. With Elastic the license shenenigans started shortly after their IPO and things have been very disruptive to the community (with half using Opensearch now). With Redis I planned the switch to Valkey the second it was announced. Clear cut case of cutting loose. Valkey looks like it has proper governance. Redis never had that.
Ollama seems relatively OK by this benchmark. The software (ollama server) is MIT licensed and there appears to be no contributor license agreement in place. But it's a small group of people that do most of the coding and they all work for the same vc funded company behind ollama. That's not proper governance. They could fail. They could relicense. They could decide that they don't like open source after all. Etc. Worth considering before you bet your company on making this a foundational piece of your tech stack.
Ollama, run by Facebook. Small company, huh.
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I view it a bit like I do cloud gaming, 90% of the time I'm fine with local use, but sometimes it's just more cost effective to offload the cost of hardware to someone else. But it's not an all-or-nothing decision.
Yep, if you just want to play one or two games at 4k HDR etc. it's a lot cheaper to pay 22€ for GeForce Now Ultimate vs. getting a whole-ass gaming PC capable of the same.
Any more information on "Privacy first"? It seems pretty thin if just not retaining data.
For Draw Things provided "Cloud Compute", we don't retain any data too (everything is done in RAM per request). But that is still unsatisfactory personally. We will soon add "privacy pass" support, but still not to the satisfactory. Transparency log that can be attested on the hardware would be nice (since we run our open-source gRPCServerCLI too), but I just don't know where to start.
I see no privacy advantage to working with Ollama, which can sell your data or have it subpoenaed just like anyone else.
In theory, "privacy pass" should help, as you can subpoena content, but cannot know who made these. But that is still thin (and Ollama not doing that too anyway).
I don't see a privacy policy and their desktop app is closed source. So, not encouraging.
[full disclosure I am working on something with actual privacy guarantees for LLM calls that does use a transparency log, etc.]
I’d love to learn more about your project. I’m using socialized cloud regions for AI security and they really lag the mainstream. Definitely need more options here.
Edit: emailed the address on the site in your profile, got an inbox does not exist error.
I would pay more if they let you run the models in Switzerland or some other GDPR respecting country, even if there was extra latency. I would also hope everything is being sent over SSL or something similar.
I had to do a double take here. Switzerland surely isn’t in the GDPR, so you mean their own privacy laws or GDPR in the EU?
What could be the benefit of paying $20 to Ollama to run inferior models instead of paying the same amount of money to e.g. OpenAI for access to sota models?
I feel the primary benefit of this Ollama Turbo is that you can quickly test and run different models in the cloud that you could run locally if you had the correct hardware.
This allows you to try out some open models and better assess if you could buy a dgx box or Mac Studio with a lot of unified memory and build out what you want to do locally without actually investing in very expensive hardware.
Certain applications require good privacy control and on-prem and local are something certain financial/medical/law developers want. This allows you to build something and test it on non-private data and then drop in real local hardware later in the process.
> quickly test and run different models in the cloud that you could run locally if you had the correct hardware.
I feel like they're competing against Hugging Face or even Colaboratory then if this is the case.
And for cases that require strict privacy control, I don't think I'd run it on emergent models or if I really have to, I would prefer doing so on an existing cloud setup already that has the necessary trust / compliance barriers addressed. (does Ollama Turbo even have their Trust center up?)
I can see its potential once it gets rolling, since there's a lot of ollama installations out there.
Me at home: $20/mo while I wait for a card that can run this or dgx box? Decisions, decisions.
Quickly test… the two models they support? This is just another subscription to quantized models.
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I'm not sure the major models will remain at $20. Regardless, I support any and all efforts to keep the space crowded and competitive.
Running models without a filter on it. OpenAI has an overzealous filter and won’t even tell you what you violated. So you have to do a dance with prompts to see if it’s copyright, trademark or whatever. Recently it just refused to answer my questions and said it wasn’t true that a civil servant would get fired for releasing a report per their job duties. Another dance sending it links to stories that it was true so it could answer my question. I want a LLMs without training wheels.
I think its the data privacy is the main point and probably more usage before you hit limits? But mainly data privacy i guess
I run a lot of mundane jobs that work fine with less capable models, so I can see the potential benefit. It all depends on the limits though.
Groq seems to do okay with a similar service but I think their pricing is probably better.
Groq's moat is speed, using their custom hardware.
Yeah, the NAZI sex not will be great for business!
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Privacy, I guess. But at this point it’s just believing that they won’t log your data.
nothing lmao. this is just ollama trying to make money.
Called it.
It's very unfortunate that the local inference community has aggregated around Ollama when it's clear that's not their long term priority or strategy.
Its imperative we move away ASAP
Llama.cpp (library which ollama uses under the hoods) has its own server, and it is fully compatible with open-webui.
I moved away from ollama in favor of llama-server a couple of months ago and never missed anything, since I'm still using the same UI.
totally respect your choice, and it's a great project too. Of course as a maintainer of Ollama, my preference is to win you over with Ollama. If it doesn't meet your needs, it's okay. We are more energized than ever to keep improving Ollama. Hopefully one day we will win you back.
Ollama does not use llama.cpp anymore; we do still keep it and occasionally update it to remain compatible for older models for when we used it. The team is great, we just have features we want to build, and want to implement the models directly in Ollama. (We do use GGML and ask partners to help it. This is a project that also powers llama.cpp and is maintained by that same team)
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Fully compatible is a stretch, it's important we dont fall into a celebrity "my guy is perfect" trap. They implement a few endpoints.
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I won't use `ollama` on principle. I use `llama-cli` and `llama-server` if I'm not linking `ggml`/`gguf` directly. It's like, two extra commands to use the one by the genius that wrote it and not the one that the guys just jacked it.
The models are on HuggingFace and downloading them is `uvx huggingface-cli`, the `GGUF` quants were `TheBloke` (with a grant from pmarca IIRC) for ages and now everyone does them (`unsloth` does a bunch of them).
Maybe I've got it twisted, but it seems to be that the people who actually do `ggml` aren't happy about it, and I've got their back on this.
It’s unfortunate that llama.cpp’s code is a mess. It’s impossible to make any meaningful contributions to it.
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Interesting, admittedly, I am slowly getting to the point, where ollama's defaults get a little restrictive. If the setup is not too onerous, I would not mind trying. Where did you start?
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Isn't the open-webui maintainer heavily against MCP support and tool calling?
hmm, how so? Ollama is open and the pricing is completely optional for users who want additional GPUs.
Is it bad to fairly charge money for selling GPUs that cost us money too, and use that money to grow the core open-source project?
At one point, it just has to be reasonable. I'd like to believe by having a conscientious, we can create something great.
First, I must say I appreciate you taking the time to be engaged on this thread and responding to so many of us.
What I'm referring to is a broader pattern that I (and several) others have been seeing. Of the top of my head: not crediting llama.cpp previously, still not crediting llama.cpp now and saying you are using your own inference engine when you are still using ggml and the core of what Georgi made, most importantly why even create your own version - is it not better for the community to just contribute to llama.cpp?, making your own propreitary model storage platform disallowing using weights with other local engines requiring people to duplicate downloads and more.
I dont know how to regard these other than being largely motivated out of self interest.
I think what Jeff and you have built have been enormously helpful to us - Ollama is how I got started running models locally and have enjoyed using it for years now. For that, I think you guys should be paid millions. But what I fear is going to happen is you guys will go the way of the current dogma of capturing users (at least in mindshare) and then continually squeezing more. I would love to be wrong, but I am not going to stick around to find out as its risk I cannot take.
Everyone just wants to solarpunk this up.
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I believe that is what https://github.com/containers/ramalama set out to do.
Huggingface also offers a cloud product, but that doesn’t take away from downloading weights and running them locally.
Oh no this is a positively diabolical development, offering...hosting services tailored to a specific use case at a reasonable price ...
They can’t keep getting away with this.
Yes, better to get free sh*t unsustainably. By the way, you're free to create an open source alternative and pour your time into that so we can all benefit. But when you don't — remember I called it!
What? The obvious move is to never have switched to Ollama and just use Llama.cpp directly, which I've been doing for years. Llama.cpp was created first, is the foundation for this product, and is actually open source.
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> Its imperative we move away ASAP
Why? If the tool works then use it. They’re not forcing you to use the cloud.
There are many, many FOSS apps that use Ollama as a dependency. If Ollama rugs, then all those projects suffer.
Its a tale we seen played out many times. Redis is the most recent example.
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Local inference is becoming completely commoditized imo. These days even docker has a local models you can launch with a single click (or command).
i was trying to remove it but noticed they've hidden the uninstall away. It amounts to doing a rm - which is a joke.
happy sglang user here :)
I stopped using them when they started doing the weird model naming bullshit stuck with lmstudio since
I am so so so confused as to why Ollama of all companies did this other than an emblematic stab at making money-perhaps to appease someone putting pressure on them to do so. Their stuff does a wonderful job of enabling local for those who want it. So many things to explore there but instead they stand up yet another cloud thing? Love Ollama and hope it stays awesome
The problem is that OSS is free to use but it is not free to create or maintain. If you want it to remain free to use and also up to date, Ollama will need someone to address issues on GitHub. Usually people want to be paid money for that.
money is great! I like money! but if this is their version of buy me a coffee I think there’s room to run elsewhere for their skillset/area of expertise
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So much that is interesting about this
For one of the top local open model inference engines of choice - only supporting OSS out of the gate feels like an angle to just ride the hype knowing OSS is announced today "oh OSS came out and you can use Ollama Turbo to use it"
The subscription based pricing is really interesting. Other players offer this but not for API type services. I always imagine that there will be a real pricing war with LLMs with time / as capabilities mature, and going monthly pricing on API services is possibly a symptom of that
What does this mean for the local inference engine? Does Ollama have enough resources to maintain both?
It says “usage-based pricing” is coming soon. I think that is the sweet spot for a service like this.
I pay $20 to Anthropic, so I don’t think I’d get enough use out of this for the $20 fee. But being able to spin up any of these models and use as needed (and compare) seems extremely useful to me.
I hope this works out well for the team.
> It says “usage-based pricing” is coming soon. I think that is the sweet spot for a service like this.
Agreed, though there are already several providers of these new OpenAI models available, so I'm not sure what ollama's value add is there (there are plenty of good chat/code/etc interfaces available if you are bringing your own API keys).
A flat fee service for open-source LLMs is somewhat unique, even if I don't see myself paying for it.
Usage-based pricing would put them in competition with established services like deepinfra.com, novita.ai, and ultimately openrouter.ai. They would go in with more name-recognition, but the established competition is already very competitive on pricing
I mean $20/month for API access is definitely new.
A subscription fee for API usage is definitely an interesting offering, though the actual value will depend on usage limits (which are kept hidden).
we are learning the usage patterns to be able to price this more properly.
Man, busy day in the world of AI announcements! This looks coordinated with OpenAI, as it launches with `gpt-oss-20b` and `gpt-oss-120b`
Yep, on the ollama home page (https://ollama.com/) it says
> OpenAI and Ollama partner to launch gpt-oss
I do hope Ollama got a good paycheck from that, as they are essentially help OpenAI to oss-wash their image with the goodwill that Ollama has built up.
That'll be an uphill battle on value proposition tbh. $20 a month for access to a widely available MoE 120B with ~5B active parameters at unspecified usage limits?
I guess their target audience values convenience and easy of use above all else so that could play well there maybe.
> Turbo includes hourly and daily limits to avoid capacity issues. Usage-based pricing will soon be available to consume models in a metered fashion.
Doesn't look that much better than a ChatGPT Plus subscription.
In case the website isn't clear, this seems to be a paid-hosted service for models.
Does this mean we can access Ollama APIs for $20/mo and test them without running the model locally? I'm not hardware-rich, but for some projects, I'd like a reliable pricing.
Distractions like this probably the reason they still, over a year now, do not support sharded GGUF.
https://github.com/ollama/ollama/issues/5245
If any of the major inference engines - vLLM, Sglang, llama.cpp - incorporated api driven model switching, automatic model unload after idle and automatic CPU layer offloading to avoid OOM it would avoid the need for ollama.
That’s just llama-swap and llama.cpp
Interesting - it does indeed seem like llama-server has the needed endpoints to do the model swapping and llama.cpp as of recently also has a new flag for the dynamic CPU offload now.
However the approach to model swapping is not 'ollama compatible' which means all the OSS tools supporting 'ollama' Ex Openwebui, Openhands, Bolt.diy, n8n, flowise, browser-use etc.. aren't able to take advantage of this particularly useful capability as best I can tell.
For production use of open weight models I'd use something like Amazon Bedrock, Google Vertex AI (which uses vLLM), or on-prem vLLM/SGLang. But for a quick assessment of a model as a developer, Ollama Turbo looks appealing. I find Google GCP incredibly user hostile and a nightmare to navigate quotas and stuff.
More than one year in and Ollama still doesn't support Vulkan inference. Vulkan is essential for consumer hardware. Ollama is a failed project at this point: https://news.ycombinator.com/item?id=42886680
There's an open pull request https://github.com/ollama/ollama/pull/9650 but it needs to be forward ported/rebased to the current version before the maintainers can even consider merging it.
Also realistically, Vulkan Compute support mostly helps iGPU's and older/lower-end dGPU's, which can only bring a modest performance speed up in the compute-bound preprocessing phase (because modern CPU inference wins in the text-generation phase due to better memory bandwidth). There are exceptions such as modern Intel dGPU's or perhaps Macs running Asahi where Vulkan Compute can be more broadly useful, but these are also quite rare.
That pull request has been open for more than a year. The owner rebased multiple times but eventually gave up because Ollama devs just don't care.
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Is there an evaluation of such services available anywhere. Looking for recommendations for similar services with usage based pricing and pro-and-cons.
ps: looking for most economic one to play around with as long as it a decent enough experience (minimal learning curve). buy, happy to pay too
OpenRouter is great. Less privacy I guess, but you pay for usage and you have access to hundreds of models. They have free models too, albeit rate-limited.
"All hardware is located in the United States."
If I use local/OSS models it's specifically to avoid running in a country with no data protection laws. It's a big close miss here.
I think what matters more here is "All hardware is located outside of China". Located in the US means little because that's not good enough for many regulated industries even within the US.
All things considered though, Europe is getting confusing. They have GDPR but now pushing to backdoor encryption within the EU? [1]
At least there isn't a strong movement in the US trying to outlaw E2E encryption.
[1] https://www.eff.org/deeplinks/2025/06/eus-encryption-roadmap...
Which brings up the point are truly private LLMs possible? Where the input I provide is only meaningful to me, but the LLM can still transform it without gaining any contextual value out of it? Without sharing a key? If this can be done, can it be done performantly?
I would feel safer if the hardware was located in China than in the US.
Maybe I hit a nerve with the EU part? I thought it was a fair observation, but I'm open to being corrected if there's more nuance I missed.
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Even the backdoor is an American lobby. Ashton Kutcher and Demi Moore's Thorn.
Then don't use it and keep using models locally?
No I think the point is to choose the best jurisdiction to have cloud hosted data where your data is best protected from access by very wealthy entities via intelligence services bribery. That’s still hands down the USA.
Any evidence for this claim that e.g. Mossad has less penetration into digital systems of USA than it does RF or PRC?
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Open router competition?
This is super exciting. Congratulations on the launch!
Looks like Docker's "offload" product, but with less functionality and more vendor lock-in, the simple pricing both excites and worries me.
If these are FP4 like the other ollama models then I'm not very interested. If I'm using an API anyway I'd rather use the full weights.
OpenAI has only provided MXFP4 weights. These are the same weights used by other cloud providers.
Oh, I didn't know that. Weird!
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Seems like an easy way to run gpt-oss for development environments on laptops. Probably necessary if you plan to self-host in production.
Can anyone explain why this is a bad thing?
Is it because they developed s new ollama which isn't open and which doesn't use llama.cpp?
I build an app against the Ollama API. If this will let me test all Ollama models, I'm so in.
The 'Sign In' link on the Ollama Mac App when you click Turbo doesn't work...
It should open ollama.com/connect – sorry about that. Feel free to message me jeff@ollama.com if you keep seeing issues
Does anyone know who or what ollama is in terms of people and company?
at this point, can i purchase the subscription directly from the model provider or hugging face and use it? or is this ollama attempt to become a provider like them.
20$ ... for the openai opensource models in preview only?
Does anyone know if this is like like OpenRouter?
Often the math works out that you get a lot more for $20 a month if you settle for smaller sized but capable models (8b-30b). I don’t see how it’s better other than Ollama can “promise” they don’t store your data where as OpenRouter is dependent on which host you choose (and there’s no indicator on OpenRouter exposing which ones do or don’t).
In a universe where everything you say can be taken out of context, things like OpenAi will be a data leak nightmare.
Need this soon:
https://arxiv.org/abs/2410.02486
Watching ollama pivot from a somewhat scrappy yet amazingly important and well designed open source project to a regular "for-profit company" is going to be sad.
Thankfully, this may just leave more room for other open source local inference engines.
we have always been building in the open, and so is Ollama. All the core pieces of Ollama are open. There are areas where we want to be opinionated on the design to build the world we want to see.
There are areas we will make money, and I wholly believe if we follow our conscious we can create something amazing for the world while making sure we can keep it fueled to keep it going for the long term.
Some of the ideas in Turbo mode (completely optional) is to serve the users who want a faster GPU, and adding in additional capabilities like web search. We loved the experience so much that we decided to give web search to non-paid users too. (Again, it's fully optional). Now to prevent abuse and make sure our costs don't go out of hand, we require login.
Can't we all just work together and create a better world? Or does it have to be so zero sum?
I wanted to try web search to increase my privacy but it wanted to do login.
For Turbo mode I understand the need for paying but the main poing of running a local model with web search is browsing from my computer without using any LLM provider. Also I want to get rid of the latency to US servers from Europe.
If ollama can't do it, maybe a fork.
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I'm sorry but your words don't match your actions.
I think this offering is a perfectly reasonable option for them to make money. We all have bills to pay, and this isn't interfering with their open source project, so I don't see anything wrong with it.
> this isn't interfering with their open source project
Wait until it makes significant amounts of money. Suddenly the priorities will be different.
I don’t begrudge them wanting to make some money off it though.
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Their FOSS local inference service didn't go anywhere.
This isn't Anaconda, they didn't do a bait and switch to screw their core users. It isn't sinful for devs to try and earn a living.
Another perspective:
If you earn a living using something someone else built, and expect them not to earn a living, your paycheck has a limited lifetime.
“Someone” in this context could be a person, a team, or a corporate entity. Free may be temporary.
Yet. Their FOSS local inference service hasn't go anywhere ... yet.
You can build this and go build something else as well. You don't need to morph the thing you built. That's underhanded
>> Watching ollama pivot from a somewhat scrappy yet amazingly important and well designed open source project to a regular "for-profit company" is going to be sad.
if i could have consistent and seamless local-cloud dev that would be a nice win. everyone has to write things 3x over these days depending on your garden of choice, even with langchain/llamaindex
I don't blame them. As soon as they offer a few more models available with the Turbo mode I plan on subscribing to their Turbo plan for a couple of months - a buying them a coffee, or keeping the lights on kind of thing.
The Ollama app using the signed-in-only web search tool is really pretty good.
> important and well designed open source project
It was always just a wrapper around the real well designed OSS, llama.cpp. Ollama even messes up the names of models by calling distilled models the name of the actual one, such as DeepSeek.
Ollama's engineers created Docker Desktop, and you can see how that turned out, so I don't have much faith in them to continue to stay open given what a rugpull Docker Desktop became.
I wouldn't go as far as to say that llama.cpp is "well designed" (there be demons there), but I otherwise agree with the sentiment.
I remember them pivoting from being infra.hq
It was always a company
Same, was just after a small lightweight solution where I can download, manage and run local models. Really not a fan of boarding the enshittification train ride with them.
Always had a bad feeling when they didn't give ggerganov/llama.cpp their deserved credit for making Ollama possible in the first place, if it were a true OSS project they would have, but now makes more sense through the lens of a VC-funded project looking to grab as much marketshare as possible to avoid raising awareness for alternatives in OSS projects they depend on.
Together with their new closed-source UI [1] it's time for me to switch back to llama.cpp's cli/server.
[1] https://www.reddit.com/r/LocalLLaMA/comments/1meeyee/ollamas...
ollama is YC and VC backed, this was inevitable and not surprising.
All companies that raise outside investment follow this route.
No exceptions.
And yes this is how ollama will fall due to enshittification, for lack of a better word.
[flagged]
"Please don't post shallow dismissals, especially of other people's work. A good critical comment teaches us something."
https://news.ycombinator.com/newsguidelines.html
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> Repackaging existing software while literally adding no useful functionality was always their gig.
Developers continue to be blind to usability and UI/UX. Ollama lets you just install it, just install models, and go. The only other thing really like that is LM-Studio.
It's not surprising that the people behind it are Docker people. Yes you can do everything Docker does with Linux kernel and shell commands, but do you want to?
Making software usable is often many orders of magnitude more work than making software work.
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This is not true.
No inference engine does all of:
- Model switching
- Unload after idle
- Dynamic layer offload to CPU to avoid OOM
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sorry that you feel the way you feel. :(
I'm not sure which package we use that is triggering this. My guess is llama.cpp based on what I see on social? Ollama has long shifted to using our own engine. We do use llama.cpp for legacy and backwards compatibility. I want to be clear it's not a knock on the llama.cpp project either.
There are certain features we want to build into Ollama, and we want to be opinionated on the experience we want to build.
Have you supported our past gigs before? Why not be more happy and optimistic in seeing everyone build their dreams (success or not).
If you go build a project of your dreams, I'd be supportive of it too.
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Yes everyone should just write cpp to call local LLMs obviously
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Why does everything AI-related have to be $20? Why can't there be tiers? OpenAI setting the standard of $20/m for every AI application is one of the worst things to ever happen.
https://openai.com/chatgpt/pricing/ - $0 / $20 / $200 / $25 (team) / custom enterprise pricing / on-demand API pricing
https://www.anthropic.com/pricing - $0 / $17 (if billed annually) / $20 (if billed monthly) / $100 / $25 (team) / custom enterprise pricing / on-demand API pricing
Sounds like tiers to me.
I should have specified less expensive tiers (below the $20 standard). A tier <= $10 would be great. Anything over $10 for casual use seems excessive (or at least from my perspective)
Tokens are expensive and nobody is making any money.
yep. this is the 2nd half of why the AI bubble is going to pop.
My guess is that’s the lowest price point that provides a modicum of profitability — LLMs are quite expensive to run, and even more so for providers like Ollama, which are entering the market and don’t have idle capacity.
Claude has $20, $100 and $200, ChatGPT $20, and $200, Google has $20 and $250. Those all have free tiers as well, and metered APIs. Grok has $30 and $300 it looks like, the list probably goes on and on.
I strongly recommend together.ai, which allows you to use a lot of different open source models and charges for usage, not a monthly fee.
> What is Turbo?
> Turbo is a new way to run open models using datacenter-grade hardware.
What? Why not just say that it is a cloud-based service for running models? Why this language?
Why use meaningful words in place of allegories like clouds, you ask?
Daily limits yawn
Ah, vague "limits". Hard pass.
No thanks, Ollama. I'd rather give the money to anyone but you grifters.
No matter if a project is "open source" as long as they announce that they have raised millions amount of dollars from investors...
It is completely compromised, especially if it is an AI company.
How do you think ollama was able to provide the open source AI models to everyone for free?
I am pretty sure ollama was losing money on every pull of those images from their infrastructure.
Those that are now angry at ollama charging money or not focusing on privacy should have been angry when they raised money from investors.
It was fun because it was open. Now it's just another brand seeking dollars.
Ollama at its core will always be open. Not all users have the computer to run models locally, and it is only fair if we provide GPUs that cost us money and let the users who optionally want it to pay for it.
I think it’s the logical move to ensure Ollama can continue to fund development. I think you will probably end up having to add more tiers or some way for users to buy more credits/gpu time. See anthropic’s recent move with Claude code due to the usage of a number of 24/7 users.
I’m not throwing the towel on Ollama yet. They do need dollars to operate, but still provide excellent software for running models locally and without paying them a dime.
^ this. As a developer, Ollama has been my go-to for serving offline models. I then use cloudflare tunnels to make them available where I need them.
Although it is open, its really just all code borrowed from llama.cpp.
If you want to see where the actual developers do the actual hard work, go use llama.cpp instead.
I like how the landing page (and even this HN page until this point) completely miss any reference to Meta and Facebook. The landing page promises privacy but anyone who knows how FB used VPN software to spy on people, knows that as long as the current leadership is in place, we shouldn't assume they've all of a sudden became fans of our privacy.
Ollama isn’t connected to Meta besides offering Llama as one of the potential models you can run.
There is obviously some connection to Llama (the original models giving rise to llama.cpp which Ollama was built on) but the companies have no affiliation.