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It's a turducken of crap from everyone but ngxson and Hugging Face and llama.cpp in this situation. llama.cpp did have multimodal, I've been maintaining an int

It's a turducken of crap from everyone but ngxson and Hugging Face and llama.cpp in this situation. llama.cpp did have multimodal, I've been maintaining an integration for many moons now. (Feb 2024? Original LLaVa through Gemma 3) However, this was not for mere mortals. It was not documented and had gotten unwieldy, to say the least. ngxson (HF employee) did a ton of work to get gemma3 support in, and had to do it in a separate binary. They dove in and landed a refactored backbone that is presumably more maintainable and on track to be in what I think of as the real Ollama, llama.cpp's server binary. As you well note, Ollama is Ollamaing - I joked, once, that the median llama.cpp contribution from Ollama is a driveby GitHub comment asking when a feature will land in llama-server, so it can be copy-pasted into Ollama. It's really sort of depressing to me because I'm just one dude, it really wasn't that hard to support it (it's one of a gajillion things I have to do, I'd estimate 2 SWE-weeks at 10 YOE, 1.5 SWE-days for every model release), and it's hard to get attention for detailed work in this space with how much everyone exaggerates and rushes to PR. EDIT: Coming back after reading the blog post, and I'm 10x as frustrated. "Support thinking / reasoning; Tool calling with streaming responses" --- this is table stakes stuff that was possible eons ago. I don't see any sign of them doing anything specific in any of the code they link, the whole thing reads like someone carefully worked with an LLM to present a maximalist technical-sounding version of the llama.cpp stuff and frame it as if they worked with these companies and built their own thing. (note the very careful wording on this, e.g. in the footer the companies are thanked for releasing the models) I think it's great that they have a nice UX that helps people run llama.cpp locally without compiling, but it's hard for me to think of a project I've been more by turned off by in my 37 years on this rock.

rvz 1y ago
> As you well note, Ollama is Ollamaing - I joked, once, that their median llama.cpp contribution from Ollama is asking when a feature will land in llama-server so it can be copy-pasted into Ollama. Other than being a nice wrapper around llama.cpp, are there any meaningful improvements that they came up with that landed in llama.cpp? I guess in this case with the introduction of libmtmd (for multi-modal support in llama.cpp) Ollama waited and did a git pull and now multi-modal + better vision support was here and no proper credit was given. Yes, they had vision support via LLaVa models but it wasn't that great.
- refulgentis 1y ago
  There's been no noteworthy contributions, I'd honestly wouldn't be surprised to hear there's 0 contributions. Well it's even sillier than that: I didn't realize that the timeline in the llama.cpp link was humble and matched my memory: it was the test binaries that changed. i.e. the API was refactored a bit and such but its not anything new under the sun. Also the llama.cpp they have has tool and thinking support. shrugs The tooling was called llava but that's just because it was the first model -- multimodal models are/were consistently supported ~instantly, it was just your calls into llama.cpp needed to manage that,a nd they still do! - its just there's been some cleanup so there isn't one test binary for every model. It's sillier than that in it wasn't even "multi-modal + better vision support was here" it was "oh we should do that fr if llama.cpp is" On a more positive note, the big contributor I appreciate in that vein is Kobold contributed a ton of Vulkan work IIUC. And another round of applause for ochafik: idk if this gentleman from Google is doing this in his spare time or fulltime for Google, but they have done an absolutely stunning amount of work to make tool calls and thinking systematically approachable, even building a header-only Jinja parser implementation and designing a way to systematize "blessed" overrides of the rushed silly templates that are inserted into models. Really important work IMHO, tool calls are what make AI automated and having open source being able to step up here significantly means you can have legit Sonnet-like agency in Gemma 3 12B, even Phi 4 3.8B to an extent.
  - ochafik 1y ago
    Thanks for the kind words! I've indeed done all that on my spare time (still under Google copyright), very happy to see this used and appreciated :-) About to start a new job / unsure if I'll be able to contribute more, but it's been a lovely ride! (largely thanks to the other contributors and ggerganov@ himself!)
Patrick_Devine 1y ago
I worked on the text portion of gemma3 (as well as gemma2) for the Ollama engine, and worked directly with the Gemma team at Google on the implementation. I didn't base the implementation off of the llama.cpp implementation which was done in parallel. We did our implementation in golang, and llama.cpp did theirs in C++. There was no "copy-and-pasting" as you are implying, although I do think collaborating together on these new models would help us get them out the door faster. I am really appreciative of Georgi catching a few things we got wrong in our implementation.
nolist_policy 1y ago
For one Ollama supports interleaved sliding window attention for Gemma 3 while llama.cpp doesn't.[0] iSWA reduces kv cache size to 1/6. Ollama is written in golang so of course they can not meaningfully contribute that back to llama.cpp. [0] https://github.com/ggml-org/llama.cpp/issues/12637 https://github.com/ggml-org/llama.cpp/issues/12637
- noodletheworld 1y ago
  What nonsense is this? Where do you imagine ggml is from? > The llama.cpp project is the main playground for developing new features for the ggml library -> https://github.com/ollama/ollama/tree/27da2cddc514208f4e23539e00485b880e3e2191/ml/backend/ggml/ggml https://github.com/ollama/ollama/tree/27da2cddc514208f4e2353... (Hint: If you think they only write go in ollama, look at the commit history of that folder)
  - nolist_policy 1y ago
    llama.cpp clearly does not support iSWA: https://github.com/ggml-org/llama.cpp/issues/12637 https://github.com/ggml-org/llama.cpp/issues/12637 Ollama does, please try it.
  - imtringued 1y ago
    Dude, they literally announced that they stopped using llama.cpp and are now using ggml directly. Whatever gotcha you think there is, exists only in your head.
    - noodletheworld 1y ago
      I'm responding to this assertion: > Ollama is written in golang so of course they can not meaningfully contribute that back to llama.cpp. llama.cpp consumes GGML. ollama consumes GGML. If they contribute upstream changes, they are contributing to llama.cpp. The assertions that they: a) only write golang b) cannot upstream changes Are both, categorically, false. You can argue what 'meaningfully' means if you like. You can also believe whatever you like. However, both (a) and (b), are false. It is not a matter of dispute. > Whatever gotcha you think there is, exists only in your head. There is no 'gotcha'. You're projecting. My only point is that any claim that they are somehow not able to contribute upstream changes only indicates a lack of desire or competence, not a lack of the technical capacity to do so.

rvz 1y ago

> As you well note, Ollama is Ollamaing - I joked, once, that their median llama.cpp contribution from Ollama is asking when a feature will land in llama-server so it can be copy-pasted into Ollama. Other than being a nice wrapper around llama.cpp, are there any meaningful improvements that they came up with that landed in llama.cpp? I guess in this case with the introduction of libmtmd (for multi-modal support in llama.cpp) Ollama waited and did a git pull and now multi-modal + better vision support was here and no proper credit was given. Yes, they had vision support via LLaVa models but it wasn't that great.

refulgentis 1y ago
There's been no noteworthy contributions, I'd honestly wouldn't be surprised to hear there's 0 contributions. Well it's even sillier than that: I didn't realize that the timeline in the llama.cpp link was humble and matched my memory: it was the test binaries that changed. i.e. the API was refactored a bit and such but its not anything new under the sun. Also the llama.cpp they have has tool and thinking support. shrugs The tooling was called llava but that's just because it was the first model -- multimodal models are/were consistently supported ~instantly, it was just your calls into llama.cpp needed to manage that,a nd they still do! - its just there's been some cleanup so there isn't one test binary for every model. It's sillier than that in it wasn't even "multi-modal + better vision support was here" it was "oh we should do that fr if llama.cpp is" On a more positive note, the big contributor I appreciate in that vein is Kobold contributed a ton of Vulkan work IIUC. And another round of applause for ochafik: idk if this gentleman from Google is doing this in his spare time or fulltime for Google, but they have done an absolutely stunning amount of work to make tool calls and thinking systematically approachable, even building a header-only Jinja parser implementation and designing a way to systematize "blessed" overrides of the rushed silly templates that are inserted into models. Really important work IMHO, tool calls are what make AI automated and having open source being able to step up here significantly means you can have legit Sonnet-like agency in Gemma 3 12B, even Phi 4 3.8B to an extent.
- ochafik 1y ago
  Thanks for the kind words! I've indeed done all that on my spare time (still under Google copyright), very happy to see this used and appreciated :-) About to start a new job / unsure if I'll be able to contribute more, but it's been a lovely ride! (largely thanks to the other contributors and ggerganov@ himself!)

Patrick_Devine 1y ago

I worked on the text portion of gemma3 (as well as gemma2) for the Ollama engine, and worked directly with the Gemma team at Google on the implementation. I didn't base the implementation off of the llama.cpp implementation which was done in parallel. We did our implementation in golang, and llama.cpp did theirs in C++. There was no "copy-and-pasting" as you are implying, although I do think collaborating together on these new models would help us get them out the door faster. I am really appreciative of Georgi catching a few things we got wrong in our implementation.

nolist_policy 1y ago

For one Ollama supports interleaved sliding window attention for Gemma 3 while llama.cpp doesn't.[0] iSWA reduces kv cache size to 1/6. Ollama is written in golang so of course they can not meaningfully contribute that back to llama.cpp. [0] https://github.com/ggml-org/llama.cpp/issues/12637 https://github.com/ggml-org/llama.cpp/issues/12637

noodletheworld 1y ago
What nonsense is this? Where do you imagine ggml is from? > The llama.cpp project is the main playground for developing new features for the ggml library -> https://github.com/ollama/ollama/tree/27da2cddc514208f4e23539e00485b880e3e2191/ml/backend/ggml/ggml https://github.com/ollama/ollama/tree/27da2cddc514208f4e2353... (Hint: If you think they only write go in ollama, look at the commit history of that folder)
- nolist_policy 1y ago
  llama.cpp clearly does not support iSWA: https://github.com/ggml-org/llama.cpp/issues/12637 https://github.com/ggml-org/llama.cpp/issues/12637 Ollama does, please try it.
- imtringued 1y ago
  Dude, they literally announced that they stopped using llama.cpp and are now using ggml directly. Whatever gotcha you think there is, exists only in your head.
  - noodletheworld 1y ago
    I'm responding to this assertion: > Ollama is written in golang so of course they can not meaningfully contribute that back to llama.cpp. llama.cpp consumes GGML. ollama consumes GGML. If they contribute upstream changes, they are contributing to llama.cpp. The assertions that they: a) only write golang b) cannot upstream changes Are both, categorically, false. You can argue what 'meaningfully' means if you like. You can also believe whatever you like. However, both (a) and (b), are false. It is not a matter of dispute. > Whatever gotcha you think there is, exists only in your head. There is no 'gotcha'. You're projecting. My only point is that any claim that they are somehow not able to contribute upstream changes only indicates a lack of desire or competence, not a lack of the technical capacity to do so.