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 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.
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.
`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
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.
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 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.
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.
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!
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.
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.
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.
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.
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 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.
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.
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’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.
extr|6 months ago
- 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.
coderatlarge|6 months ago
[1] https://californiarecorder.com/sam-altman-requires-ai-privil...
wkat4242|6 months ago
jnmandal|6 months ago
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.
mchiang|6 months ago
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.
steren|6 months ago
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.
romperstomper|6 months ago
miki123211|6 months ago
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.
moralestapia|6 months ago
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.
mrs6969|6 months ago
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.
benreesman|6 months ago
freedomben|6 months ago
am17an|6 months ago
jasonjmcghee|6 months ago
Aurornis|6 months ago
I'm also interested to see if that small minority of people are willing to pay for a service like this.
threetonesun|6 months ago
liuliu|6 months ago
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.
pagekicker|6 months ago
jmort|6 months ago
[full disclosure I am working on something with actual privacy guarantees for LLM calls that does use a transparency log, etc.]
pogue|6 months ago
jacekm|6 months ago
daft_pink|6 months ago
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.
rapind|6 months ago
adrr|6 months ago
michelsedgh|6 months ago
unknown|6 months ago
[deleted]
ibejoeb|6 months ago
_--__--__|6 months ago
AndroTux|6 months ago
vanillax|6 months ago
dcreater|6 months ago
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
tarruda|6 months ago
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.
mchiang|6 months ago
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.
sitkack|6 months ago
janalsncm|6 months ago
idiotsecant|6 months ago
mrcwinn|6 months ago
Aurornis|6 months ago
Why? If the tool works then use it. They’re not forcing you to use the cloud.
prettyblocks|6 months ago
unknown|6 months ago
[deleted]
fud101|6 months ago
jcelerier|6 months ago
cchance|6 months ago
captainregex|6 months ago
janalsncm|6 months ago
ahmedhawas123|6 months ago
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?
timmg|6 months ago
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.
ac29|6 months ago
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).
wongarsu|6 months ago
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
Aeolun|6 months ago
paxys|6 months ago
mchiang|6 months ago
turnsout|6 months ago
sambaumann|6 months ago
> OpenAI and Ollama partner to launch gpt-oss
hobofan|6 months ago
Havoc|6 months ago
I guess their target audience values convenience and easy of use above all else so that could play well there maybe.
selcuka|6 months ago
Doesn't look that much better than a ChatGPT Plus subscription.
factorialboy|6 months ago
llmtosser|6 months ago
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.
jychang|6 months ago
zacian|6 months ago
leopoldj|6 months ago
buyucu|6 months ago
zozbot234|6 months ago
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.
santa_boy|6 months ago
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
splittydev|6 months ago
satellite2|6 months ago
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.
bangaladore|6 months ago
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?
impulser_|6 months ago
riazrizvi|6 months ago
domatic1|6 months ago
aglazer|6 months ago
radioradioradio|6 months ago
irthomasthomas|6 months ago
mchiang|6 months ago
philip1209|6 months ago
_giorgio_|6 months ago
Is it because they developed s new ollama which isn't open and which doesn't use llama.cpp?
scosman|6 months ago
unknown|6 months ago
[deleted]
unknown|6 months ago
[deleted]
rohansood15|6 months ago
jmorgan|6 months ago
st3fan|6 months ago
jp1016|6 months ago
cchance|6 months ago
orliesaurus|6 months ago
ivape|6 months ago
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
smlacy|6 months ago
Thankfully, this may just leave more room for other open source local inference engines.
mchiang|6 months ago
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?
shepardrtc|6 months ago
smeeth|6 months ago
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.
TuringNYC|6 months ago
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
mark_l_watson|6 months ago
The Ollama app using the signed-in-only web search tool is really pretty good.
satvikpendem|6 months ago
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.
user-|6 months ago
dangoodmanUT|6 months ago
mythz|6 months ago
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...
colesantiago|6 months ago
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.
otabdeveloper4|6 months ago
computegabe|6 months ago
paxys|6 months ago
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.
colesantiago|6 months ago
thimabi|6 months ago
furyofantares|6 months ago
joecot|6 months ago
agnishom|6 months ago
> 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?
owebmaster|6 months ago
yahoozoo|6 months ago
ochronus|6 months ago
unknown|6 months ago
[deleted]
fud101|6 months ago
colesantiago|6 months ago
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.
decide1000|6 months ago
mchiang|6 months ago
thimabi|6 months ago
DiabloD3|6 months ago
If you want to see where the actual developers do the actual hard work, go use llama.cpp instead.
hanifbbz|6 months ago
tuckerman|6 months ago
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.