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Gemma 4 12B: A unified, encoder-free multimodal model

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Re: Gemma 4 12B: A unified, encoder-free multimodal model

#381

Post by spider-mario »

goobatrooba wrote: post #165
minimaxir wrote: post #2

The big story here is the encoder-free part, which I still don't fully understand. > Vision: We replaced Gemma 4’s vision encoder with a lightweight embedding module consisting of a single matrix multiplication, positional embedding and normalizations. That's technically encoding, just without using a dedicated model for it like SigLIP? The Developer's Guide elaborates, it's still a 35M layer which I am curious is ro…

Either Google changed the text or you editorialised it a tiny bit - just for all others that got excited, they mean 16GB V RAM. So a premium graphics card requiring a >2500€ device is the minimum to run this. Still progress, but not quite democratic yet. Weird though that Google might be cannibalising it's own AI subscription service?

Or a MacBook Air with unified memory?

Re: Gemma 4 12B: A unified, encoder-free multimodal model

#382

Post by nialse »

briansm wrote: post #357

Strange that they are feeding raw audio in. Even in humans, there is a hardware transform to the frequency domain (the cochlea) before data is fed to the brain, effectively doing this part in the LLM seems inefficient.

The FFT is essentially just a matrix multiplication, or two. No need for fancy conversions. Just a huge amount of training data and a very large array.

Re: Gemma 4 12B: A unified, encoder-free multimodal model

#383

Post by mchusma »

__mharrison__ wrote: post #252
mchusma wrote: post #139

Earlier quoted context omitted.

I think its even more puzzling because you can't even run Gemma 31b on google cloud, they only let you test it with a rate limit. No way (I can find) to actually pay them to use it. We saw great results in our usecase using google direct. Moved to Openrouter because google wouldn't let us use it beyond a test. Then Openrouters performance looked worse, not sure if there was a quantized version or something. So we ins…

I'm using it for one of my use cases (ocr) on openrouter right now.

It’s on openrouter. We just noticed performance was worse in a specific agentic app usecase. It’s possible we made an implementation mistake, my main point though is Google is really silly not hosting their own models.

Re: Gemma 4 12B: A unified, encoder-free multimodal model

#384

Post by khimaros »

thangalin wrote: post #266
kajecounterhack wrote: post #229

Earlier quoted context omitted.

Have you found Gemma 4 31B better than Qwen 3.6 27B Q8? I just started using Qwen + Pi agent and it's great, but "which model works best" is still totally crowdsourced and I was going off of peoples' opinions on reddit. Would love to hear more opinions if people have them.

Yes. I'm using Gemma-4 31B (gemma-4-31B-it-assistant.Q4_K_M.gguf) with llama.cpp to attribute quotations throughout chapters of my sci-fi novel. I started with Qwen3, but couldn't get it to work. Qwen3 TTS Voice Design, on the other hand, is incredible (Qwen3-TTS-12Hz-1.7B-VoiceDesign). I'm using both for an audiobook generator that produces a variety of voices. Screens: * https://i.ibb.co/TBBV5nJk/kl-01.png (voice d…

building something similar: https://github.com/khimaros/autiobook

Re: Gemma 4 12B: A unified, encoder-free multimodal model

#385

Post by plagiarist »

alfiedotwtf wrote: post #349
dotancohen wrote: post #344

Earlier quoted context omitted.

I read there regularly. I find little value there between the memes. I was hoping to ask a knowledgeable person here.

/r/localllama for a while now seems to prefer Gemma 4 E4B for creative writing (especially the uncensored GGUFs).

Do they prefer E4B over the larger models or is it a matter of what fits their machine? I assume 4B isn't large enough to get interesting writing but I don't know anything about it.

Re: Gemma 4 12B: A unified, encoder-free multimodal model

#386

Post by dwroberts »

lxgr wrote: post #60

Am I missing something or are the Ollama versions of this ( https://ollama.com/library/gemma4/tags ) text-only for now?

Highly recommend just dropping Ollama. You can download binary releases of llama.cpp for every platform and run them trivially in 5 seconds. Ollama serves no purpose other than to take open source work and rebadge as its own, while providing inferior functionality

Re: Gemma 4 12B: A unified, encoder-free multimodal model

#387

Post by eggplantemoji69 »

asim wrote: post #137

We are now entering the closed loop game. Google doesn't need anyone else to accelerate their models. This is their bread and butter. I'm both shocked but also not surprised that they continue to develop such efficiencies. Honestly it's like silicon and CPU architecture advancement. We kept shrinking it and shrinking it and it kept getting more and more powerful and here we are with AI and it's only going to be 100x…

Seems like they’re trying to put open ai, anthropic, grok out of business by releasing their open source models, as google actually has massive profitable arms of their business outside ai, and be there to scoop up any remaining demand for huge models run in the cloud as a monopoly of sorts.

Re: Gemma 4 12B: A unified, encoder-free multimodal model

#388

Post by sgt101 »

0xbadcafebee wrote: post #206
senko wrote: post #120

I ran the Q4 quant (used with llama.cpp) though my "minesweeper" vibe-coding benchmark: https://senko.net/vibecode-bench/2026/minesweeper-gamma-4-12... The result is decent, but it had a few bizzare/trivial syntax errors I had to fix manually: it would do an extra closing bracket or paren a few times, and wanted to separate function definitions with comma. Not sure what that was about, but otherwise the output run ju…

It was almost certainly not trained for coding, as it's got both audio and vision input, is only 12B, and nowhere in the announcement is coding mentioned. It will likely not have good performance on coding in general, compared to other small models like Qwen 3.6 35B A3B, Gemma 4 26B A4B, Nvidia Nemotron 3 Nano 30B-A3B, gpt-oss-20b. For 16GB laptops, Qwen 3.5 9B is the undisputed champ. Gemma 4 31B is the top dog at s…

31B won't run in 48GB for me - it needs 54.

Re: Gemma 4 12B: A unified, encoder-free multimodal model

#390

Post by amelius »

senko wrote: post #120

I ran the Q4 quant (used with llama.cpp) though my "minesweeper" vibe-coding benchmark: https://senko.net/vibecode-bench/2026/minesweeper-gamma-4-12... The result is decent, but it had a few bizzare/trivial syntax errors I had to fix manually: it would do an extra closing bracket or paren a few times, and wanted to separate function definitions with comma. Not sure what that was about, but otherwise the output run ju…

> it would do an extra closing bracket or paren a few times

I had this with Gemini: in the middle of a C++ program it once said RParen instead of using )

It was easy to fix of course, but it makes you question what is going on inside its head.

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