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Posted by jeffmcjunkin 8 hours ago

Google releases Gemma 4 open models(deepmind.google)
979 points | 309 commentspage 4
popinman322 3 hours ago|
Does anyone know whether we'll be receiving transcoders for this batch of models? We got them for Gemma 3, but maybe that was a one-off.
bearjaws 5 hours ago||
The labels on the table read "Gemma 431B IT" which reads as 431B parameter model, not Gemma 4 - 31B...
whhone 6 hours ago||
The LiteRT-LM CLI (https://ai.google.dev/edge/litert-lm/cli) provides a way to try the Gemma 4 model.

  # with uvx
  uvx litert-lm run \
    --from-huggingface-repo=litert-community/gemma-4-E2B-it-litert-lm \
    gemma-4-E2B-it.litertlm
stephbook 5 hours ago||
Kind of sad they didn't release stronger versions. $dayjob offers strong NVidias that are hungry for models and are stuck running llama, gpt-oss etc.

Seems like Google and Anthropic (which I consider leaders) would rather keep their secret sauce to themselves – understandable.

darshanmakwana 7 hours ago||
This is awesome! I will try to use them locally with opencode and see if they are usable inreplacement of claude code for basic tasks
0xbadcafebee 5 hours ago||
Gemma 3 models were pretty bad, so hopefully they got Gemma 4 to at least come close to the other major open weights
nolist_policy 5 hours ago|
Bad at coding. Good for everything else.
flakiness 8 hours ago||
It's good they still have non-instruction-tuned models.
james2doyle 7 hours ago||
Hmm just tried the google/gemma-4-31B-it through HuggingFace (inference provider seems to be Novita) and function/tool calling was not enabled...
james2doyle 7 hours ago||
Yeah you can see here that tool calling is disabled: https://huggingface.co/inference/models?model=google%2Fgemma...

At least, as of this post

linolevan 7 hours ago||
Hosted on Parasail + Google (both for free, as of now) themselves, probably would give those a shot
gunalx 4 hours ago||
We didnt get deepseek v4, but gemma 4. Cant complain.
rvz 7 hours ago|
Open weight models once again marching on and slowly being a viable alternative to the larger ones.

We are at least 1 year and at most 2 years until they surpass closed models for everyday tasks that can be done locally to save spending on tokens.

echelon 7 hours ago|
> We are at least 1 year and at most 2 years until they surpass closed models for everyday tasks that can be done locally to save spending on tokens.

Until they pass what closed models today can do.

By that time, closed models will be 4 years ahead.

Google would not be giving this away if they believed local open models could win.

Google is doing this to slow down Anthropic, OpenAI, and the Chinese, knowing that in the fullness of time they can be the leader. They'll stop being so generous once the dust settles.

ma2kx 6 hours ago|||
I think it will be less of a local versus cloud situation, but rather one where both complement each other. The next step will undoubtedly be for local LLMs to be fast and intelligent enough to allow for vocal conversation. A low-latency model will then run locally, enabling smoother conversations, while batch jobs in the cloud handle the more complex tasks.

Google, at least, is likely interested in such a scenario, given their broad smartphone market. And if their local Gemma/Gemini-nano LLMs perform better with Gemini in the cloud, that would naturally be a significant advantage.

pxc 3 hours ago||||
If they pass what closed models today can do by much, they'll be "good enough" for what I want to do with them. I imagine that's true for many people.
jimbokun 6 hours ago||||
But at that point, won’t there be very few tasks left where the average user can discern the difference in quality for most tasks?
pixl97 7 hours ago|||
I mean, correct, but running open models locally will still massively drop your costs even if you still need to interface with large paid for models. Google will still make less money than if they were the only model that existed at the end of the day.
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