Looks like a big pivot on target audience from developers to regular users, at least on the homepage https://ollama.com/ as a product. Before, it was all about the CLI versions of Ollama for devs, now it's not even mentioned. At the bottom of the blog post it says:
> For pure CLI versions of Ollama, standalone downloads are available on Ollama’s GitHub releases page.
Nothing against that, just an observation.
Previously I tested several local LLM apps, and the 2 best ones to me were LM Studio [1] and Msty [2]. Will check this one out for sure.
One missing feature that the ChatGPT desktop app has and I think is a good idea for these local LLM apps is a shortcut to open a new chat anytime (Alt + Space), with a reduced UI. It is great for quick questions.
Its very strange, but they do have a Linux client that they refuse to mention in their blog post. I have no idea if this is a simple slip-up or if it was for some reason intentional.
I just updated and a bit annoying by default gemma3:4b was selected that I don't have on my local. I guess would be nicer to default to one of the models that are present.
It was nice it started downloading it but also there was no indication I don't have that model before hand until I opened drop-down to see download buttons.
The need to start a chat for a model that is not currently downloaded in order to initiate a download confused me for a minute the first time I tried it out. A more intuitive approach (which is the first thing I tried to do before I figured it out) might be to make the download icons in the model list clickable, to initiate a download. Then you could display a download progress bar in the list, and when models have been downloaded show a little "info" icon that is also clickable to display the model card, surface other model specific options, and enable deletion. Love the new UI, kudos!
Thanks for including it. Ollama is very good at what it does. Including the feature is showing mindful growth in helping ollama be that skateboard, scooter, car, etc that the developer needs for LLM at that time. Making it appeal to casual/hobbyist is the right approach.
PS totally running windows here and using kesor/ollama-proxy if I need to make it externally available.
do you know why ollama hasn't updated its models in over a month while many fantastic models have been released in that time, most recently GLM 4.5? It's forcing me to use LM Studio which I for whatever reason absolutely do not prefer.
thank you guys for all your work on it, regardless
You know that if you go to hugging face and find a gguf page, you can click on Deploy and select ollama. It comes with “run” but whatever—just change to pull. Has a jacked name, but works.
Also, if you search on ollama’s models, you’ll see user ones that you can download too
GLM 4.5 has a new/modified architecture. From what I understand, MLX was really one of the only frameworks that had support for it as of yesterday. LM Studio supports MLX as one backend. Everyone else was/is still developing support for it.
Ollama has the new 235B and 30B Qwen3 models from this week, so it’s not as if they have done nothing for a month.
We work closely with majority of research labs / model creates directly. Most of the times we will support models on release day. There are sometimes where the release window for major models are fairly close - and we just have to elect to support models where we believe will better support a majority of users.
Nothing out of spite, and purely limited by the amount of effort required to support these models.
We are hopeful too -- where users can technically add models to Ollama directly. Although there is definitely some learning curve.
Seems that Google intend it to be that way - https://ai.google.dev/gemma/docs/capabilities/function-calli... . I suppose they are saying that the model is good enough that if you put the tool call format in prompt it should be able to handle any formats.
I use PetrosStav/gemma3-tools and it seems that it only works half of the time - the rest the model call the tool but it doesn't get properly parsed by Ollama.
unfortunately, I don't think gemma 3 supports tool calling well. It's not trained into the model, and the 'support' for tool calling is post model training.
We are working with Google, and trying to give the feedback on improving tool calling capabilities for future Gemma models. Fingers crossed!
Are there any plans to improve observability toolset for developers? There is myriad of various AI chat apps, and there is no clear reason why another one from Ollama would be better. But Ollama is uniquely positioned to provide the best observability experience to its users because it owns the whole server stack, any other observability tool (eg Langfuse) may only treat it as a yet another API black box.
Does the new app make it easier for users to expose the Ollama daemon on the network (and mdns discovery )? It’s still trickier than needed for Home Assistant users to get started with Ollama (which tends to run on a different machine).
In the app settings now, there is a toggle for "Expose Ollama to the network" - it allows for other devices or services on the network to access Ollama.
This caught me out yesterday. I was trying to move models onto external disk, and it seems to require re-installation? but there was no sign of the simple CLI option that was previously presented and I gave up.
As a developer feature request, it would be great if ollama could support more than one location at once, so that it is possible to keep a couple models 'live' but have the option to plug in an external disk with extra models being picked up auto-magically based on the ollama_models path please. Or maybe the server could present a simple html interface next to the API endpoint?
And just to say thanks for making these models easily accessible. I am agAInst AI generally, but it is nice to be able to have a play with these models locally. I havent found one that covers Zig, but appreciate the steady stream of new models to try. Thanks.
I just symbolically link the default model directory to a fast and cheap external drive. I agree that it would be nice to support multiple model directories.
I think having a bash script as the linux installation is more of a stop-gap measure than truly supporting Linux. And ollama is FOSS compared to LM Studio and Msty (as someone who switched from ollama to LM Studio; I'm very happy to see the frontend development of ollama and an easier method of increasing the context length of a model).
this is actually positive even for devs. The more users have ollama installed then you can release some desktop ai app for them and don't have to bundle additional models in your own app. Easier to provide to such user free or cheaper subscription because you don't have additional costs. Latest Qwen30B models area really powerful.
Would be even better if there was a installation template that checks if Ollama is installed and if not download it as sub installation first checking user computer specs if enough RAM and fast enough CPU/GPU. Also API to prompt user (ask for permission) to install specific model if haven't been installed.
> Would be even better if there was a installation template that checks if Ollama is installed and if not download it as sub installation first..... Also API to prompt user (ask for permission) to install specific model if haven't been installed.
That's actually what we've done for our own App [1]. It checks if Ollama and other dependencies are installed. No model is bundled with it. We prompt user to install a model (you pick a model, click a button and we download the model; similar if you wish to remove a model). The aim is to make it quite simple for non-technical folks to use.
I may be too picky, and on reflection I probably shouldn't be - it was just my first thought when I saw what the project actually is for the first time.
What I meant is the "Py" prefix is typically used for Python APIs/libraries, or Python bindings to libraries in other languages. Sometimes as a prefix for dev tool names like PyInstaller or PyEnv. It's just less often used for standalone apps, only to indicate the project was developed in Python.
> One missing feature that the ChatGPT desktop app has and I think is a good idea for these local LLM apps is a shortcut to open a new chat anytime (Alt + Space), with a reduced UI. It is great for quick questions.
I’d heard of Msty and briefly tried it before. I checked the website again and it looks quite feature rich. I hadn’t known about LM Studio, and I see that it allows commercial use for free (which Matt doesn’t).
How would you compare and contrast between the two? My main use would be to use it as a tool with a chat interface rather than developing applications that talk to models.
I use Msty all the time and I love it. It just works and it's got all features I want now, including generating alternate responses, swapping models mid-chat, editing both sent messages and responses, ...
I also tried LM Studio a few months back. The interface felt overly complex and I got weird error messages which made it look like I'd have to manually fix errors in the underlying python environment. Would have been fine if it was for work, but I just wanted to play around with LLMs in my spare time so I couldn't be bothered.
Msty (msty.app). Currently they're working on Msty Studio which is only accessible to people with a license, but the desktop app is pretty good, it just doesn't have tool (MCP) support.
That feature is available in HugstonOne with a new tab, among other features :)
Edit: Is incredible how unethical are all the other developers with their crappie spam unrelated. Ollama is a great app and pioneer of AI, cudos and my best thanks.
I am somewhat surprised that this app doesn't seem to offer any way to connect to a remote Ollama instance. The most powerful computer I own isn't necessarily the one I'm running the GUI on.
This. This. A thousand times this. I hate Windows / MacOS but love their desktops. I love Linux / BSD but hate their desktops. So my most expensive most powerful workstation is always a headless Linux machine that I ssh into from a Windows or MacOS toy computer. Unfortunately most developers do not understand this. Every time I run a command in the terminal and it tries to open a browser tab without printing the URL, it makes me want to scream and shout and retire from tech forever to be a plumber.
You can replace the xdg-open command (or whichever command is used on your linux system) with your own. Just program it to fire over the url to a waiting socket on your windows box, and have it automatically open there. The details are pretty easy to work out, and the result will be seamless.
I usually do this with a port forward (ip or Unix socket) over SSH. This way my server just sends data to ~/.tunnel/socket, and my SSH connection handles getting it to my client.
(It’s a bit more complicated with starting a listening server in my laptop, making sure the port forwarded file doesn’t exist, etc, but this is the basic idea.)
Or just display the URL in terminal. I spent 5 years of my life ricing my Linux machine to get it as I want it to be only to realise that, at least for my needs and likes, nothing matches MacOS’s DE, compositor and font rendering.
Not a bash on Linux desktop users, just my experience.
You can work around this by using SSH port forwarding (ssh -L 11434:localhost:11434 user@remote) to connect to a remote Ollama instance, though native support would definitely be better.
But it seems like the GUI already connects over the network, no? In that case, why do you need to do user research for adding what is basically a command line option, at its simplest? It would probably take less time to add that than to write the comment.
They will have to support auth if they are adding support for connecting with remote host. It's not difficult but it's not as trivial as you suggested.
It's definitely coming, there is no way they would leave such an important feature on the table. My guess is they are waiting so they can announce connections to their own servers.
Heads up, there’s a fair bit of pushback (justified or not) on r/LocalLLaMA about Ollama’s tactics:
Vendor lock-in: AFAIK it now uses a proprietary llama.cpp fork and builts its own registry on ollama.com in a kind of docker way (I heard docker ppl are actually behind ollama) and it's a bit difficult to reuse model binaries with other inference engines due to their use of hashed filenames on disk etc.
Closed-source tweaks: Many llama.cpp improvements haven’t been upstreamed or credited, raising GPL concerns. They since switched to their own inference backend.
Mixed performance: Same models often run slower or give worse outputs than plain llama.cpp. Tradeoff for convenience - I know.
Opaque model naming: Rebrands or filters community models without transparency, biggest fail was calling the smaller Deepseek-R1 distills just "Deepseek-R1" adding to a massive confusion on social media and from "AI Content Creators", that you can run "THE" DeepSeek-R1 on any potato.
Difficult to change Context Window default: Using Ollama as a backend, it is difficult to change default context window size on the fly, leading to hallucinations and endless circles on output, especially for Agents / Thinking models.
---
If you want better, (in some cases more open) alternatives:
llama.cpp: Battle-tested C++ engine with minimal deps and faster with many optimizations
ik_llama.cpp: High-perf fork, even faster than default llama.cpp
llama-swap: YAML-driven model swapping for your endpoint.
LM Studio: GUI for any GGUF model—no proprietary formats with all llama.cpp optimizations available in a GUI
Open WebUI: Front-end that plugs into llama.cpp, ollama, MPT, etc.
“I heard docker people are behind Ollama” um yes it’s founded by ex docker people and has raised multiple rounds of VC funding. The writing is on the wall - this is not some virtuous community project, it’s a profit driven startup and at the end of the day that is what they are optimizing for.
“Justified or not” — is certainly a useful caveat when giving the same credit to a few people who complain loudly with mostly unauthentic complaints.
> Vendor lock-in
That is, probably the most ridiculous of the statements. Ollama is open source, llama.cpp is open source, llamafiles are zip files that contain quantized versions of models openly available to be run with numerous other providers. Their llama.cpp changes are primarily for performance and compatibility. Yes, they run a registry on ollama.com for pre-packed, pre-quantized versions of models that are, again, openly available.
> Closed-source tweaks
Oh so many things wrong in a short sentence. Llama.cpp is MIT licensed, not GPL license. A proprietary fork is perfectly legitimate use. Also.. “proprietary“? The source code is literally available, including the patches, on GitHub in ollama/ollama project, in the “llama” folder with a patch file as recent as yesterday?
> Mixed Performance
Yes, almost anything suffers degraded performance when the goal is usability instead of performance. It is why people use C# instead of Assembly or punch cards. Performance isn’t the only metric, which makes this a useless point.
> Opaque model name
Sure, their official models have some ambiguities sometimes. I don’t know know that is the “problem” that people make it out to be when ollama is designed for average people to run models, and so a decision like “ollama run qwen3” not being the absolutely maximum best option possible rather than the option most people can run makes sense. Do really think it is advantageous or user friendly, when Tommy wants to try out “Deepseek-r1” on his potato laptop that a 671b parameter model too large to fit on almost anything consumer computer is the right choice and that it is instead meant as a “deception”? That seems…disingenuous. Not to mention, they are clearly listed as such on ollama.com, where in black and white it says the deep seek-r1 by default refers with the qwen model, and that the full model is available as deep seek-r1:671b
> Context Window
Probably the only fair and legitimate criticism of your entire comment.
I’m not an ollama defender or champion, couldn’t care about the company, and I barely use ollama (mostly just to run qwen3-8b for embedding). It really is just that most of these complaints you’re sharing from others seem to have TikTok-level fact checking.
For all of Electron's promise in being cross-platform, "I'll just press this button and ship this Electron app on Linux and everything will be fine" is not the current state of things. A lot of it is papercuts like glibc version aggravation, but GPU support is persistently problematic.
The Element app on Linux is currently broken (if you want to use encryption, so basically for everyone) due to an issue with Electron. Luckily it still works in a regular browser. I'm really baffled by how that can happen.
I believe power users or developers can already use this from CLI in Linux. This new app for Windows and MacOS shows this is intended for regular users.
I gave the Ollama UI a try on Windows after using the CLI service for a while.
- I like the simplicity. This would be perfect for setting up a non-technical friend or family member with a local LLM with just a couple clicks
- Multimodal and Markdown support works as expected
- The model dropdown shows both your local models and other popular models available in the registry
I could see using this over Open WebUI for basic use cases where one doesn't need to dial in the prompt or advanced parameters. Maybe those will be exposed later. But for now - I feel the simplicity is a strength.
Small update: thinking models also work well. I like that it shows the thinking stream in a fainter style while it generates, then hides it to show the final output when it's ready. The thinking output is still available with a click.
Another commenter mentioned not being able to point the new UI to a remote Ollama instance - I agree, that would be super handy for running the UI on a slow machine but inferring on something more powerful.
I've been on something of a quest to find a really good chat interface for LLMs.
Most import feature for me is that I want to be able to chat with local models, remote models on my other machines, and cloud models (OpenAI API compatible). Anything that makes it easier to switch between models or query them simultaneously is important.
Here's what I've learned so far:
* Msty - my current favorite. Can do true simultaneous requests to multiple models. Nice aesthetic. Sadly not open source. Have had some freezing issues on Linux.
* Jan.ai - Can't make requests to multiple models simultaneously
* LM Studio - Not open source. Doesn't support remote/cloud models (maybe there's a plugin?)
* GPT4All - Was getting weird JSON errors with openrouter models. Have to explicitly switch between models, even if you're trying to use them from different chats.
Still to try: Librechat, Open WebUI, AnythingLLM, koboldcpp.
I've been in the same quest for a while. Here's my list, not a recommendation or endorsement list, just a list of alternative clients I've considered, tried or am still evaluating:
- chatbox - https://github.com/chatboxai/chatbox - free and OSS, with a paid tier, supports MCP and local/remote, has a local KB, works well so far and looks promising.
- macai - https://github.com/Renset/macai simple client for remote APIs, does not support image pasting or MCP or anything really, very limited, crashes.
- typingmind.com - web, with a downloadable (if paid) version. Not OSS, but one-time payment, indie dev. One of the first alt chat clients I've ever tried, not using it anymore. Somewhat clunky gui, but ok. Supports MCP, haven't tried it it.
- Open WebUI - deployed for our team so that we could chat through many APIs. Works well for a multi-user web-deployment, but image generation hasn't been working. I don't like it as a personal client though, buggy sometimes but gets frequent fixes fortunately.
- jan.ai - it comes with popular models pre-populated listed, which makes it harder to plug into custom or local model servers. But it supports local model deployment within the app (like what ollama is announcing) which is good for people who don't want to deal with starting a server. I haven't played with it enough, but I personally prefer to deploy a local server (ie ollama, litellm...) and then just have the chat gui app give me a flexible endpoint configuration for adding custom models to it.
I'm also wary of evil actors deploying chat GUIs just to farm your API keys. You should be too. Use disposable api keys, watch usage, refresh with new keys once in a while after trying clients.
do you have any screenshots? the home page shows a picture of a tamagotchi but none of the actual chat interface, which makes me wonder if I’m outside of the target audience
Last I tried OpenWebUI (A few months ago), it was pretty painful to connect non-OpenAI externally hosted models. There was a workaround that involved installing a 3rd party "function" (or was it a "pipeline"?), but it didn't feel smooth.
Is this easier now? Specifically, I would like to easily connect anthropic models just by plugging in my API key.
No, still the same, otoh, it works perfectly fine for Claude, and that is the only one I use. I just wished they would finally add native support for this ...
CherryStudio is a power tool for this case https://github.com/CherryHQ/cherry-studio -- has MCP, search, personas, and reasoning support too. i use it heavily with llama.cpp + llama-swap
I've been using AnythingLLM for a couple months now and really like it. You can organize different "Workspaces" which are models + specific prompts and it supports Ollama along with the major LLM providers.
I have it running in a docker container on a raspberry pi and then I use Tailscale to make it accessible anywhere. It looks good on mobile too so it's pretty seamless.
I use that and Raycast's Claude extension for random questions and that's pretty much does everything I want.
I like webUI but it’s weird and conplicated how you have to set up the different models (via text files in the browser, the instructions contains a lot of confusing terms). Librechat is nice but I can’t get it to not log me out every 5 min which makes it unusable. I’ve been told it keeps you logged in when using https but I use tailscale so that is difficult (when doing multiple services on a single host).
Build your own! It's a great way to learn, keeps you interested in the latest developments. Plus you get to try out cool UX experiments and see what works. I built my own interface back in 2023 and have been slowly adding to it since. I added local models via MLX last month. I'm surprised more devs aren't rolling their own interface, they are easy to make and you learn a lot.
Open WebUI is definitely what you want. Supports any OpenAI-compatible provider, lets you manually configure your model list and settings for each model in a very user-friendly way, switching between models is instant, and it lets you send the same prompt to multiple models simultaneously in the same chat and displays them side by side.
gptel in emacs does this. You can run the same prompt against different models in separate emacs windows (local or via api w/ keys) at the same time to compare outputs. I highly recommended it. https://github.com/karthink/gptel
Our team has been using openwebui as the interface for our stack of open source models we run internally at work and it’s been fantastic! It has a great feature set, good support for MCPs, and is easy to stand up and maintain.
Not surprising; Ollama is set on becoming the standard interface for companies to deploy "open" models. The focus on "local" is incidental, and likely not long term. I'm sure Ollama is going to announce a plan to use "open" models through their own cloud-based API using this app.
Strongly disagree with this. It is the default go-to for companies that cannot use cloud-based services for IP or regulatory reasons (think of defense contractors). Isn't that the main reason to use "open" models, which are still weaker than closed ones?
> Ollama is set on becoming the standard interface for companies to deploy "open" models.
That's not what I've been seeing, but obviously my perspective (as anyone's) is limited. What I'm seeing is deployments of vLLM, SGLang, llama.cpp or even HuggingFace's Transformers with their own wrapper, at least for inference with open weight models. Somehow, the only place where I come across recommendations for running Ollama was on HN and before on r/LocalLlama but not even there as of late. The people who used to run Ollama for local inference (+ OpenWebUI) now seem to mostly be running LM Studio, myself included too.
Likewise. I use Ollama as the API server and CLI interface for local models, and use OpenWebUI when I want a web interface (which TBH, isn't that often) and it's a fine combination. Honestly, the idea of Ollama adding their own chat interface UI never even occurred to me. It feels a little bit... unnecessary?
Still choices are good, to props to the Ollama team!
It's a phony BSD license, with an attempt to pass it off as the real thing with some verbiage. It's neither within the letter nor the spirit of the real BSD license.
I don't really care about that as a user. Maybe for FOSS purists it's important but copyright is a thing I as techy care nothing about. I can it for free and i can see all the source code. I'm not going to build a fork so the rest doesn't matter.
If you’re a power user of these LLMs and have coding experience, I actually recommend just whipping together your own bespoke chat UI that you can customize however you like. Grab any OpenAI compatible endpoint for inference and a frontend component framework (many of which have added standard Chat components) - the rest is almost trivial. I threw one together in a week with Gemini’s assistance and now I use it every day. Is it production ready? Hell no but it works exactly how I want it to and whenever I find myself saying “I wish it could do XYZ…” I just add it.
Kinda odd to be so dismissive of this mindset given this websites title. Whipping up your own chatui really is not that hard and is a pretty fun exercise. Knowing how your tools work and being able to tweak them to your specific usecases kinda rules!
There is a big difference between fun exercise and actually creating something that competes with the apps you can download. Building something on par with Claude Desktop, ChatGPT Desktop, etc. would be a lot of work. And I don't think the payoff would be there for most people.
Most people aren't hackers. Thanks to LLMs and vibe coding, even they can now take a can-do attitude to life that feels empowering. There's no longer any excuse to languish in helpless misery and negativity. You can just build things.
I've only been lucky enough to find one opportunity in my entire twenty-seven year career to write something novel and new. Most of the time we're reinventing the wheel. What separates the winners from the losers is whether or not it's your wheel.
I have other things to do with my day than vibe-coding yet another stupid chat app with fewer features than one I can just download and get running in minutes. It’s not helplessness or misery, it’s just the finite number of hours I have in a day and the fact that other things are more interesting than that. I don’t grow my own wheat or maintain my own OS, either.
Yeah, ok, don't do it then. That doesn't mean because you do not want to bother, the suggestion is invalid for everyone here. There are a lot of people who just love to do their own thing, tinker with whatever they have on hand and then use the stuff they have created themselves.
its ok to let other people have fun programming and code dumb tools. you can decide yourself what you want to or not to work on, doesn't mean you should be so negative towards the idea of people who do want to code these things
I only did it once some 15 years back (in a happy memory) using LFS. It took about a week to get to a functional system with basic necessities. A code finetuned model can write a functional chat UI with all common features and a decent UX in under a minute.
I have been exploring AI and LLMs. I built my own AI chat bot using Python [1], and then [2] AI SDK from Vercel and OpenAI compatible API endpoints. And eventually build a product around it.
this is not coder
this help typing instructions. Coding is different. For example look at my repository and tell me how refactorizing it, write a new function etc.
In my opinion You must change name.
Yeah, I have one which lets me read a pdf and chat side by side, one which is integrated into my rss feed, one with insanely aggressive memory features (experimental) etc etc :)
Tell me you're not in charge of young kids without telling me you're not in charge of young kids
(I'm just jealous. I miss my old hacking time something fierce, and have sacrificed other important things to keep a shred of it alive. I don't know if parenting hits the "developer-tinkerer class" harder than others, but damn.)
> I don't know if parenting hits the "developer-tinkerer class" harder than others, but damn.
I sort of suspect so? Devs of parenting age trend towards being neurospicy, and dev work requires sustained attention with huge penalties for interruptions.
I’ve been building a Swift app [1], compatible with OpenAI APIs, easy model switching across providers, and with hotkeys for OS integration to capture text and images. It’s far more minimal than most other LLM frontends I’ve tried, but it’s been sticky for me.
I have been happy using Ollama via the command line and via API, but I am sold on their new UI for coding. I was just using the newly updated qwen3:30b model for coding, and I like the <copy> button in the too right corner of generated code listings - a simple thing but useful.
I don't understand this move. A frontend desktop application is the opposite of what I and anyone else I know uses Ollama for. It's a local LLM backend. It's been around long enough now that any long term users have found, created and/or adjusted to their own front end interface.
I'm comfy, but some of the cutting edge local LLMs have been a little bit slow to be available recently, maybe this frontend focus is why.
I will now go and look at other options like Ollama that have either been fully UI integrated since the start, or that is committed to just being a headless backend. If any of them seem better, I'll consider switching, I probably should have done this sooner.
I hope this isn't the first step in Ollama dropping the local CLI focus, offering a subscription and becoming a generic LLM interface like so many of these tools seem to converge on.
Rightful worry, and we had the same doubts before we embarked on this. Ollama serves developers, there is no doubt about that. The CLI isn’t getting dropped, in fact, what we’ve learned in building it is having the interface interacting with Ollama is a great way for us to dogfood Ollama while building it.
There are so many choices for having an interface, and as a developer you should have a choice in selecting the UI you want. It will all continue to work with Ollama. Nothing about that changes.
Thanks for the response, appreciated. It confirms my feelings though: there are already so many choices for an interface, why are you - a team of people who built a backend LLM - now spending your time doing front end stuff under the same backend product name?
This is sending a very loud message that your focus is drifting away from why I use your product. If it was drifting away into something new and original that supplements my usage of your product, I could see the value, but like you said: there's already so many choices of good interface. Now you're going to have to play catchup against people whose first choice and genuine passion is LLM frontend UIs.
Sorry! I will still use ollama, and thank you so much for all the time and effort put in. I probably wouldn't have had a fraction of the local LLM fun I've had if it wasn't for ollama, even if my main usage is through openwebui. Ultimately, my personal preference is software that does 1 thing and does it well. Others prefer the opposite: tightly integrated all-bells-and-whistles, and I'm sure those people will appreciate this more than me - do what works for you, it's worked so far:)
I know, I often do that, but it's still not enough. E.g. things like SmolLM3 which required some llama ccp tweaks wouldn't work via guff for the first week after it had been released.
I just can't see a user-focused benefit for a backend service provider to start building and bundling their own frontend when there's already a bunch of widely used frontends available.
There's also Jan AI, which supports Linux, MCP, any Vulkan GPU, any Llama.cpp-compatible model, and optionally multiple cloud models as well. That seems like a better solution than this.
Choice is good but here is why prefer Ollama over others (I'm biased because I work on Ollama).
Supporting multiple backends is HARD. Originally, we thought we'd just add multiple backends to Ollama - MLX, ROCm, TRT-LLM, etc. It sounds really good on paper. In practice, you get into the lowest common denominator effect. What happens when you want to release Model A together with the model creator, and backend B doesn't support it? Do you ship partial support? If you do, then you start breaking your own product experience.
Supporting Vulkan for backwards compatibility on some hardware seems simple right? What if I told you in our testing, there is a portion of the supported hardware matrix getting -20% decrease in performance. What about just cherry picking which hardware to use Vulkan vs ROCm vs CUDA, etc? Do you start managing a long and tedious support matrix, where each time a driver is updated, the support may shift?
Supporting flash attention sounds simple too right? What if I told you over 20% of the hardware and for specific models, enabling it will cause non-trivial amount errors pertaining to specific hardware/model combinations? We are almost in a spot, where we can selectively enable flash attention per type of model architecture and hardware architecture.
It's so easy to add features, and hard to say no, but given any day, I will stand for a better overall product experience (at least to me since it's very subjective). No is temporary and yes is forever.
Ollama focuses on running the model the way the model creators intended. I know we get a lot of negativity on naming but often times, it's what we work with the model creators on naming (which surprisingly may or may not be how another platform named it on release). Overtime, I think this means more focus on top models to optimize more and add capabilities to augment the models.
Sure, those are all difficult problems. Problems that single devs are dealing with every day and figuring out. Why is it so hard for Ollama?
What seems to be true is that Ollama wants to be a solution that drives the narrative and wants to choose for its users rather than with them. It uses a proprietary model library, it built itself on llama.cpp and didn't upstream its changes, it converted the standard gguf model weights into some unusable file type that only worked with itself, etc.
Sorry but I don't buy it. These are not intractable problems to deal with. These are excuses by former docker creators looking to destroy another ecosystem by attempting to coopt it for their own gain.
^^^ absolutely spot on. There’s a big element of deception going on. I could respect it (and would trust the product more) if they were upfront about their motives and said “yes we are a venture backed startup and we have profit aspirations, but here’s XYZ thing we can promise. Instead it’s all smoke and mirrors … super sus.
Started with ollama, am at the stage of trying llama.ccp and realising there RPC just works, and ollama's promises of distributed runs is just hanging in the air, so indeed the convenience of ollama is starting to lose its appeal.
So, questions: what are the changes that they didn't upstream, is this listed somewhere? what is the impact? are they also changes in ggml? what was the point of the gguf format change?
> Supporting multiple backends is HARD. Originally, we thought we'd just add multiple backends to Ollama - MLX, ROCm, TRT-LLM, etc. It sounds really good on paper. In practice, you get into the lowest common denominator effect. What happens when you want to release Model A together with the model creator, and backend B doesn't support it? Do you ship partial support? If you do, then you start breaking your own product experience.
You conceptually divide your product to "universal experience" and "conditional experience". You add platform-specific things to the conditional experience, while keeping universal experience unified. I mean, do you even have a choice? The backend limits you, the only alternative you have is to change the backend upstream, which often times is the same as no alternative.
The only case where this is a real problem is when the backends are so different that the universal experience is not the main experience. But I don't think this is the case here?
Makes total sense. You cannot be constrained by the CLI when do much of what models do is multimodal and graphical. I don't think this dilutes their efforts in running the models or the CLI. In fact it's a huge enhancement and helps them penetrate the enterprise market in the long term. And the reality is, when you take VC funding for an open source tool, your customer basis is going to be the enterprise and your inevitable goal is to become a profitable business. Do not let any of the delusions of Docker fool you. Build a thing, take VC money, you need to return that investment with profit. Unfortunately free things and Dev centric tooling often make it very difficult to establish that business model. So for Ollama to take this UI approach potentially let's them then monetize a lot of things around the GUI and leave the CLI tool free.
Honestly to be expected with a 4b model. 12b/14b+ is the minimum in my experience to get decent results, unless you have a specific use-case for the 4b ones and fine-tune it to your use.
I have been experimenting many LLMs in Ollama, but the opensource models are still behind paid versions like Cohere. Any model which gives onpar performance and quality of result compared to Cohere , please let me know
Aren't cohere's models pretty dated now? They don't even show up on leaderboards (synthetic or real) these days. What about GLM 4.5, Qwen 3 235b 2507 or even just Qwen 3 32b 2507 etc...
I tried Ollama once but immediately removed it, when I couldn't easily install models that are outside of the models they "support". LM Studio is by far the best tool out there in my humble opinion.
I need more than text.
I need recognise audio to text (not only english) longest than 30s. I need generate audio. And generate image. This is important. text is trivial
Off-topic I suppose but the llama artwork looks quite good, and stylistically consistent between pieces. I wonder if it was done by a human artist or if generative models are just that good now.
Until now I've been able to reliably distinguish generated artwork from human authored artwork with ~90% accuracy. Of course, it's always getting better, but my initial research tells me the main logo has existed since Jan 2024: https://github.com/ollama/ollama/issues/2152
I don't think it was generated. (on the basis that this can't be some cutting-edge new model whose output I haven't seen yet)
Im surprised it took this long. I vibe coded the same interface last year using electron... just not Ollama because there are just better architectures/pipelines...
does anyone have a suggestion on running LLMs locally on a windows PC and then accessing them (thru an app / gui) on mac? My windows PC is a gaming PC with a pretty good GPU and I'd like to take advantage of that.
Ben, we've had private conversations about this previously. I don't see any VC money grab nor am I aware of any.
Building a product that we've dreamed of building is not wrong. Making money does not need to be evil. I, and the folks who worked tirelessly to make Ollama better will continue to build our dreams.
This doesn't appear to indicate whether the model is running locally, so I assume it's not. I'll continue to run Ollama locally in my terminal on the rare occasions that I see a use for it.
Well, they gotta do what they gotta do. But as a developer, this kills the positioning and trust it had for me. I do not see it as a developer tool project anymore.
I installed this last night on one of my cheaper computers. Ran gemma3:4b on a 16GB Ram laptop, I know HN loves specifics, so it's this exact computer ( with an upgraded 2 TB SSD).
ASUS - Vivobook S 14 - 14" OLED Laptop - Copilot+ PC - Intel Core Ultra 5 - 16GB Memory - 512GB SSD - Neutral Black
It's a bit slower than o4-mini and probably not as smart, but I feel more secure in asking for a resume review. The GUI really makes pasting in text significantly easier. Yeah I know I could just use the cli app and postman previously, but I didn't want to set that up.
if im being honest i care more about multiple local ai apps on my desktop all hooking into the same ollama instance rather than all downloading their own models as part of the app so i have like multiple 10s of gbs of repeated weights all over the place because apps dont talk to each other
I haven't used a local model in a while but ollama was the only one I've seen convert models into a different format. (I think for reduplication). You should be able to say download a gguf file and point a bunch of frontends to that same file.
completely useless move. there are already tons of good clients for Ollama. The Ollama devs need to focus on being a better llama.cpp, not building clients.
Ollama is a VC funded company that ultimately needs a revenue model they serve investors, not open source developers. Llama.cpp is a means to an end to them, not the goal. It's hard to monetize open source libraries. But a good chat client might lead to paying enterprise users.
Running good enough models locally is appealing to a lot of people and kind of hard if you are not a developer. If you are it's easy (been there done that). That's the core premise of the company. Their tech is of course widely used and for a while they've been focusing just on getting it to that stage. But that's never going to add up to revenue. So, they need to productize what they have.
No one should use ollama. A cursory search of r/localllama gives plenty of occassions where they've proven themselves bad actors. Here's a 'fun' overview
There are multiple (far better) options - eg LM studio if you want GUI, llama.cpp if you want the CLI that ollama ripped off. IMO the only reason ollama is even in the conversation is it was easy to get running on macOS, allowing the SV MBP set to feel included
/r/LocalLlama is a very circle-jerky subreddit. There's a very heavy "I am new to GitHub and have a lot of say"[0] energy. This is really unfortunate because there's also a lot of people doing tons of good work there and posting both cool links and their own projects. The "just give me an EXE types" will brigade causes they do not understand and white knight projects and attack others for no informed logic reason. They're not really a good barometer for the quality of any project, on the whole.
I literally just turned a fifteen year old MacPro5,1 into an Ollama terminal, using an ancient AMD VEGA56 GPU running Ubuntu 22... and it actually responds faster than I can type (which surprised me considering the age of this machine).
No former Linux experience, beyond basic Mac OS Terminal commands. Surprisingly simple setup... and I used an online LLM to hold my hand as we walked through the installation / setup. If I wanted to call the CLI, I'd have to ask an online LLM what that code even is (something something ollama3.2).
>ollama is probably the easiest tool ... to experiment with LLMs locally.
Seems quite simple so far. If I can do it (blue collar electrician with no programming experience) than so can you.
Wow, is it a coincidence that every comment that says anything negative about ollama gets downvoted/flagged into oblivion? what is going on in this thread?
Barely any comments in the thread are flagged. The comment by swyx has a positive score.
Some comments have been downweighted for being generic or off-topic, which is standard moderation; our role as moderators is to keep the discussion threads on-topic. But the comment that was left at the top of the thread after I'd done that seemed at least somewhat negative/critical towards the Ollama team.
I'm sad this post is greyed out. I think it's a fair take.
Other critical takes say the same thing, but wrapped in far more variations of: "definitely not judging/criticising/being negative, but I don't like this."
This is clearly a new direction for Ollama, but I can't find anything at the link explaining or justifying why they're doing it, and that makes me uncomfortable as an existing regular Ollama user.
I think this move does deserves firmer feedback like yours.
Shameless plug: I’ve been building a native AI chat client called BoltAI[0] for the last 3 years. It’s native, feature-rich, and supports multiple AI services, including Ollama and LM Studio.
> For pure CLI versions of Ollama, standalone downloads are available on Ollama’s GitHub releases page.
Nothing against that, just an observation.
Previously I tested several local LLM apps, and the 2 best ones to me were LM Studio [1] and Msty [2]. Will check this one out for sure.
One missing feature that the ChatGPT desktop app has and I think is a good idea for these local LLM apps is a shortcut to open a new chat anytime (Alt + Space), with a reduced UI. It is great for quick questions.
[1] https://lmstudio.ai/
[2] https://msty.app/
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