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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

#331

Its image processing is terrible. I ran several tests against it against Qwen 3.5 0.8b (yes, 7% the size) and Qwen beat it every time with Gemma often getting things entirely wrong. I even gave it a plain image saying "This is a test" and it thought for 6 minutes trying to analyze it and failed. Qwen 3.5 0.8b confidently got it in under a second . It may be that the Q6 quant I got is borked (or my LM Studio is), but…

Sounds like you're doing it wrong, to be honest.

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

#332

Earlier quoted context omitted.

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…

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.

Gemma 4 31B is enormously impressive. You get 1000 requests/day for free on Google's API and another 1000/day off OpenRouter. Only problem is you get 503 like crazy.

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

#335

Earlier quoted context omitted.

> For 16GB laptops, Qwen 3.5 9B is the undisputed champ. You seem like the guy to ask. For a laptop with 12GB VRAM (RTX 5070) and 32 GB system RAM, what is a good multilingual (English, Hebrew, Greek) model for conversing with personal notes in Org mode format? I don't care how long updating the model or rag takes, and even inference can be reasonably slow, but the results of the query as they relate to my personal n…

Joins us over on Reddit at r/LocalLlaMA to get 10 different opinions on that

[deleted]

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

#337
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…

>The result is decent, but it had a few bizzare/trivial syntax errors I had to fix manually

Can you instruct it to use a lsp?

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

#338

Earlier quoted context omitted.

> For 16GB laptops, Qwen 3.5 9B is the undisputed champ. You seem like the guy to ask. For a laptop with 12GB VRAM (RTX 5070) and 32 GB system RAM, what is a good multilingual (English, Hebrew, Greek) model for conversing with personal notes in Org mode format? I don't care how long updating the model or rag takes, and even inference can be reasonably slow, but the results of the query as they relate to my personal n…

You may like https://www.llmfit.org/ (not recommendation, I've not used it .. yet)

Just tried it and honestly it's a terrible experience lacking any sort of intent or reason.

Which is unsurprising in the AI space.

You get a wall of text showing you various random fine-tuned models by random people, and that is basically it.

Actual sane default requirements like "just give me the normal AI labs", "please filter for dense only" and "I want this exact context size at this quant" are not part of the tool, apparently. Neither is "compare these quants for me for the same model".

Or maybe it's just hidden enough that I did not find them before I've stopped caring.

Conway's law is at it again.

____

Edit:

I have since then had qwen3.6 ponder the codebase and think about my complaints.

Seems to require a major data model overhaul to actually fix those, so they're legit. Which I didn't doubt, but nice to have some extra fabricated confirmation after it initially refused and said "nooooo the readme says otherwise nooo hypfer is just a hater noo"

___

Edit 2:

It gets worse the longer I stare at it. This could've been a web calculator.

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

#339
post #330

Earlier quoted context omitted.

The 6-bit versions + 8-bit KV cache seems to save a good bit of memory without a significant loss of quality. The Qwen 35B is pretty fast in my testing, but MiniMax M2.7 230B is in some ways faster (way fewer tokens to arrive at an answer) even though it is much larger.

What hardware do you need to run MiniMax M2.7 230B locally?

Ryzen 395 is what I'm using, anything with 128GB+ of RAM accessible to the GPU should work fine for a 4 bit version of the model (so Spark or Mac Studio should be ok too).

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

#340

Earlier quoted context omitted.

> For 16GB laptops, Qwen 3.5 9B is the undisputed champ. You seem like the guy to ask. For a laptop with 12GB VRAM (RTX 5070) and 32 GB system RAM, what is a good multilingual (English, Hebrew, Greek) model for conversing with personal notes in Org mode format? I don't care how long updating the model or rag takes, and even inference can be reasonably slow, but the results of the query as they relate to my personal n…

Any Gemma 4 model, they are great at translations, multilingual

While Gemini 4 seems fine, Gemma 4 does not do Hebrew well. I've replaced it with Aya Expanse and am getting much better results, but there is still much improvement to be had.

I'm not doing translations, rather querying Hebrew text with a Hebrew prompt.

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