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Google releases Gemma 4 open models

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Re: Google releases Gemma 4 open models

#41

Post by Imustaskforhelp »

danielhanchen wrote: post #37
Imustaskforhelp wrote: post #26

Earlier quoted context omitted.

Daniel, I know you might hear this a lot but I really appreciate a lot of what you have been doing at Unsloth and the way you handle your communication, whether within hackernews/reddit. I am not sure if someone might have asked this already to you, but I have a question (out of curiosity) as to which open source model you find best and also, which AI training team (Qwen/Gemini/Kimi/GLM) has cooperated the most with…

Thanks a lot for the support :) Tbh Gemma-4 haha - it's sooooo good!!! For teams - Google haha definitely hands down then Qwen, Meta haha through PyTorch and Llama and Mistral - tbh all labs are great!

Now you have gotten me a bit excited for Gemma-4, Definitely gonna see if I can run the unsloth quants of this on my mac air & thanks for responding to my comment :-)

Re: Google releases Gemma 4 open models

#42

Post by kejaed »

vunderba wrote: post #34
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.

Not OP but one example is that recent VL models are more than sufficient for analyzing your local photo albums/images for creating metadata / descriptions / captions to help better organize your library.

Any pointers on some local VLMs to start with?

Re: Google releases Gemma 4 open models

#45

Post by kpw94 »

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 |…

Wild differences in ELO compared to tfa's graph: https://storage.googleapis.com/gdm-deepmind-com-prod-public/...

(Comparing Q3.5-27B to G4 26B A4B and G4 31B specifically)

I'd assume Q3.5-35B-A3B would performe worse than the Q3.5 deep 27B model, but the cards you pasted above, somehow show that for ELO and TAU2 it's the other way around...

Very impressed by unsloth's team releasing the GGUF so quickly, if that's like the qwen 3.5, I'll wait a few more days in case they make a major update.

Overall great news if it's at parity or slightly better than Qwen 3.5 open weights, hope to see both of these evolve in the sub-32GB-RAM space. Disappointed in Mistral/Ministral being so far behind these US & Chinese models

Re: Google releases Gemma 4 open models

#46

Post by greenavocado »

wg0 wrote: post #40
chasd00 wrote: post #33

Earlier quoted context omitted.

Not sure why you're being downvoted, the other thing Google has is Google. They just have to spend the effort/resources to keep up and wait for everyone else to go bankrupt. At the end of the day I think Google will be the eventual LLM winner. I think this is why Meta isn't really in the race and just releases open weight models, the writing is on the wall. Also, probably why Apple went ahead and signed a deal with G…

I don't know why I am downvoted but Google has data, expertise, hardware and deep pockets. This whole LLM thing is invented at Google and machine learning ecosystem libraries come from Google. I don't know how people can be so irrational discounting Google's muscle. Others have just borrowed data, money, hardware and they would run out of resources for sure.

This remains true so long as advertisers give Google money.

Re: Google releases Gemma 4 open models

#47

Post by danielhanchen »

Imustaskforhelp wrote: post #41
danielhanchen wrote: post #37

Earlier quoted context omitted.

Thanks a lot for the support :) Tbh Gemma-4 haha - it's sooooo good!!! For teams - Google haha definitely hands down then Qwen, Meta haha through PyTorch and Llama and Mistral - tbh all labs are great!

Now you have gotten me a bit excited for Gemma-4, Definitely gonna see if I can run the unsloth quants of this on my mac air & thanks for responding to my comment :-)

Thanks! Have a super good day!!

Re: Google releases Gemma 4 open models

#48

Post by daemonologist »

heraldgeezer wrote: post #39

Gemma vs Gemini? I am only a casual AI chatbot user, I use what gives me the most and best free limits and versions.

Gemma will give you the most, Gemini will give you the best. The former is much smaller and therefore cheaper to run, but less capable.

Although I'm not sure whether Gemma will be available even in aistudio - they took the last one down after people got it to say/do questionable stuff. It's very much intended for self-hosting.

Re: Google releases Gemma 4 open models

#49

Post by WarmWash »

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.

Re: Google releases Gemma 4 open models

#50

Post by matja »

fooker wrote: post #28

What's a realistic way to run this locally or a single expensive remote dev machine (in a vm, not through API calls)?

I'm running Gemma 4 with the llama.cpp web UI.

https://unsloth.ai/docs/models/gemma-4 > Gemma 4 GGUFs > "Use this model" > llama.cpp > llama-server -hf unsloth/gemma-4-31B-it-GGUF:Q8_0

If you already have llama.cpp you might need to update it to support Gemma 4.

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