Google releases Gemma 4 open models • Hacker News Board

Re: Google releases Gemma 4 open models

#421

Post by imtringued » Fri, Apr 03, 2026, 8:29 AM UTC

fc417fc802 wrote: post #391

neonstatic wrote: post #324

Earlier quoted context omitted.

Agree on all points! The difference between Gemma and Qwen here is that Qwen followed a much more detailed process - it consider leap years and seconds in its calculations (where Gemma used estimates like "roughly x years")

Turns out I wasn't reading closely enough. Notice that it first comes up with the number out of thin air prior to the math which is to "verify" it. Following this charade, the "precise check" using "common tools" (which it does not have access to) pulls an entirely different number out of thin air. It then asks if this new different number is correct, checks by "converting it back" with a utility it doesn't have acce…

There were research papers that showed that even just printing out dots in the thinking phase improves performance.

Re: Google releases Gemma 4 open models

#422

Post by [deleted] » Fri, Apr 03, 2026, 8:33 AM UTC

[deleted]

Re: Google releases Gemma 4 open models

#423

Post by zkmon » Fri, Apr 03, 2026, 8:37 AM UTC

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!

How does Gemma 4 26B A4B compare with Qwen3.5 35B A3B for same quants(4)

Re: Google releases Gemma 4 open models

#424

Post by [deleted] » Fri, Apr 03, 2026, 8:47 AM UTC

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!

[deleted]

Re: Google releases Gemma 4 open models

#425

Post by oblio » Fri, Apr 03, 2026, 8:59 AM UTC

How do these compare to Open AI OSS?

Re: Google releases Gemma 4 open models

#426

Post by davedx » Fri, Apr 03, 2026, 9:13 AM UTC

sillysaurusx wrote: post #396

danielhanchen wrote: post #395

Earlier quoted context omitted.

You might be right, but Google's recommendation was temp 1 etc primarily because all their benchmarks were used with these numbers, so it's better reproducibility for downstream tasks

Fair, though putting a note in the readme about temperature 0.7 couldn't hurt. I wonder why they do benchmarks with 1 instead of 0.7... that's strange. 0.7 or 0.8 at most gives noticeably better samples.

Reproducibility. They're benchmarks.

Re: Google releases Gemma 4 open models

#427

Post by sillysaurusx » Fri, Apr 03, 2026, 9:15 AM UTC

davedx wrote: post #426

sillysaurusx wrote: post #396

Earlier quoted context omitted.

Fair, though putting a note in the readme about temperature 0.7 couldn't hurt. I wonder why they do benchmarks with 1 instead of 0.7... that's strange. 0.7 or 0.8 at most gives noticeably better samples.

Reproducibility. They're benchmarks.

Reproducibility is a matter of using the same input seeds, which jax can do. 0.7 vs 1.0 would make no difference for that.

Without seeds, 0.7 would be less random than 1.0, so it'd be (slightly) more reproducible.

Re: Google releases Gemma 4 open models

#428

Post by kristopolous » Fri, Apr 03, 2026, 9:22 AM UTC

zozbot234 wrote: post #259

Computer0 wrote: post #256

Earlier quoted context omitted.

I use Claude Code. Codex and Opencode both work too. You could even do it with VScode Copilot.

These are typically coding oriented as opposed to general chat, so their system prompts may be needlessly heavy for that use case. I think the closest thing to a general solution is the emerging "claw" ecosystem, as silly as that sounds. Some of the newer "claws" do provide proper sandboxing.

This is actually a perfect use case of my llcat ... Using Unix philosophy for the llm era

https://github.com/day50-dev/llcat

I've got an interesting hack brewing for extremely hassle free tool orchestration - basically think along the lines of .bash_profile level simplicity... Maybe I'll get that out tomorrow

Re: Google releases Gemma 4 open models

#429

Post by VadimPR » Fri, Apr 03, 2026, 9:32 AM UTC

VadimPR wrote: post #307

snthpy wrote: post #125

Earlier quoted context omitted.

What's the easiest way to install these on an Android phone/Samsung?

I use LM Studio, but there's a comment here offering another tool as well.

LM Playground, not LM Studio.

Re: Google releases Gemma 4 open models

#430

Post by GaggiX » Fri, Apr 03, 2026, 9:35 AM UTC

nl wrote: post #375

Gemma-4-E4B-it scored 15/25 on my https://sql-benchmark.nicklothian.com/#all-data (agentic SQL generation). The naming is a bit odd - E4B is "4.5B effective, 8B with embeddings", so despite the name it is probably best compared with the 8B/9B class models and is competitive with them. Qwen3.5-9B also scores 15/25 in thinking mode for example. The best 9B model I've found is Qwen3.5-9B-Claude-4.6-Opus-Reasoning-Distil…

>so despite the name it is probably best compared with the 8B/9B

It runs much faster than a standard 8B/9B model, the name is given by the fact that it uses per-layer embedding (PLE).