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Google releases Gemma 4 open models

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Re: Google releases Gemma 4 open models

#181

Post by melodyogonna »

nabakin wrote: post #98
chrislattner wrote: post #67

If you want the fastest open source implementation on Blackwell and AMD MI355, check out Modular's MAX nightly. You can pip install it super fast, check it out here: https://www.modular.com/blog/day-zero-launch-fastest-perform... -Chris Lattner (yes, affiliated with Modular :-)

Faster than TensorRT-LLM on Blackwell? Or do you not consider TensorRT-LLM open source because some dependencies are closed source?

I reviewed the TensorRT-LLM commit history from the past few days and couldn't find any updates regarding Gemma 4 support. By contrast, here is the reference for MAX:https://github.com/modular/modular/commit/57728b23befed8f3b4...

Re: Google releases Gemma 4 open models

#182

Post by lostmsu »

culi wrote: post #171
simonw wrote: post #77

I ran these in LM Studio and got unrecognizable pelicans out of the 2B and 4B models and an outstanding pelican out of the 26b-a4b model - I think the best I've seen from a model that runs on my laptop. https://simonwillison.net/2026/Apr/2/gemma-4/ The gemma-4-31b model is completely broken for me - it just spits out "---\n" no matter what prompt I feed it. I got a pelican out of it via the AI Studio API hosted model…

Do you have a single gallery page where we can see all the pelicans together. I'm thinking something similar to https://clocks.brianmoore.com/ but static.

Not exactly what you asked for but try https://pelicans.borg.games/

Re: Google releases Gemma 4 open models

#183

Post by refulgentis »

scrlk wrote: post #15

Comparison of Gemma 4 vs. Qwen 3.5 benchmarks, consolidated from their respective Hugging Face model cards: | Model | MMLUP | GPQA | LCB | ELO | TAU2 | MMMLU | HLE-n | HLE-t | |----------------|-------|-------|-------|------|-------|-------|-------|-------| | G4 31B | 85.2% | 84.3% | 80.0% | 2150 | 76.9% | 88.4% | 19.5% | 26.5% | | G4 26B A4B | 82.6% | 82.3% | 77.1% | 1718 | 68.2% | 86.3% | 8.7% | 17.2% | | G4 E4B |…

Reversing the X and Y axis, adding in a few other random models, and dropping all the small Qwens makes this worse than useless as a Qwen 3.5 comparison, it’s actively misleading. If you’re using AI, please don’t rush to copy paste output :/

EDIT: Lordy, the small models are a shadow of Qwen's smalls. See https://huggingface.co/Qwen/Qwen3.5-4B versus https://www.reddit.com/r/LocalLLaMA/comments/1salgre/gemma_4...

Re: Google releases Gemma 4 open models

#184

Post by gigatexal »

nateb2022 wrote: post #167
meatmanek wrote: post #142

Earlier quoted context omitted.

The Unsloth llama.cpp guide[1] recommends building the latest llama.cpp from source, so it's possible we need to wait for LM Studio to ship an update to its bundled llama.cpp. Fairly common with new models. 1. https://unsloth.ai/docs/models/gemma-4#llama.cpp-guide

LM Studio shipped this update. Under settings make sure you update your runtimes.

Thank you both!!

Re: Google releases Gemma 4 open models

#185

Post by osti »

WarmWash wrote: post #49
antirez wrote: post #10

Featuring the ELO score as the main benchmark in chart is very misleading. The big dense Gemma 4 model does not seem to reach Qwen 3.5 27B dense model in most benchmarks. This is obviously what matters. The small 2B / 4B models are interesting and may potentially be better ASR models than specialized ones (not just for performances but since they are going to be easily served via llama.cpp / MLX and front-ends). Also…

I am unable to shake that the Chinese models all perform awfully on the private arc-agi 2 tests.

But is arc-agi really that useful though? Nowadays it seems to me that it's just another benchmark that needs to be specifically trained for. Maybe the Chinese models just didn't focus on it as much.

Re: Google releases Gemma 4 open models

#186

Post by nolist_policy »

DeepYogurt wrote: post #162
flux3125 wrote: post #155

Earlier quoted context omitted.

That’s not what it means. "-it" just indicates the model is instruction-tuned, i.e. trained to follow prompts and behave like an assistant. It doesn’t imply anything about whether thinking tokens like .... were included or excluded during training. Thats a separate design choice and varies by model.

What does that mean for a user of the model? Is the "-it" version more direct with solutions or something?

Use the it versions. The other versions are base models without post-training. E.g. base models are trained to regurgitate raw wikipedia, books, etc. Then these base models are post-trained into instruction-tuned models where they learn to act as a chat assistant.

Re: Google releases Gemma 4 open models

#187

Post by ezst »

ktimespi wrote: post #71
adamtaylor_13 wrote: post #22

Earlier quoted context omitted.

What sort of tasks are you using self-hosting for? Just curious as I've been watching the scene but not experimenting with self-hosting.

For me, receipt scanning and tagging documents and parts of speech in my personal notes. It's a lot of manual labour and I'd like to automate it if possible.

Have you tried paperless-ngx, a true and tested open source solution that's been filling this niche successfully for decades now?

Re: Google releases Gemma 4 open models

#189

Post by jorl17 »

polishdude20 wrote: post #132
evilelectron wrote: post #57

Earlier quoted context omitted.

Daniel, your work is changing the world. More power to you. I setup a pipeline for inference with OCR, full text search, embedding and summarization of land records dating back 1800s. All powered by the GGUF's you generate and llama.cpp. People are so excited that they can now search the records in multiple languages that a 1 minute wait to process the document seems nothing. Thank you!

Hey in really interested in your pipeline techniques. I've got some pdfs I need to get processed but processing them in the cloud with big providers requires redaction. Wondering if a local model or a self hosted one would work just as well.

Seconded, would also love to hear your story if you would be willing

Re: Google releases Gemma 4 open models

#190

Post by pentagrama »

danielhanchen wrote: post #2

Thinking / reasoning + multimodal + tool calling. We made some quants at https://huggingface.co/collections/unsloth/gemma-4 for folks to run them - they work really well! Guide for those interested: https://unsloth.ai/docs/models/gemma-4 Also note to use temperature = 1.0, top_p = 0.95, top_k = 64 and the EOS is " ". " thought\n" is also used for the thinking trace!

Hey, I tried to use Unsloth to run Gemma 4 locally but got stuck during the setup on Windows 11.

At some point it asked me to create a password, and right after that it threw an error. Here’s a screenshot: https://imgur.com/a/sCMmqht

This happened after running the PowerShell setup, where it installed several things like NVIDIA components, VS Code, and Python. At the end, PowerShell tell me to open a http://localhost URL in my browser, and that’s where I was prompted to set the password before it failed.

Also, I noticed that an Unsloth icon was added to my desktop, but when I click it, nothing happens.

For context, I’m not a developer and I had never used PowerShell before. Some of the steps were a bit intimidating and I wasn’t fully sure what I was approving when clicking through.

The overall experience felt a bit rough for my level. It would be great if this could be packaged as a simple .exe or a standalone app instead of going through terminal and browser steps.

Are there any plans to make something like that?

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