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Google releases Gemma 4 open models

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Re: Google releases Gemma 4 open models

#261

Post by petu »

swalsh wrote: post #199

I gave the same prompt (a small rust project that's not easy, but not overly sophisticated) to both Gemma-4 26b and Qwen 3.5 27b via OpenCode. Qwen 3.5 ran for a bit over an hour before I killed it, Gemma 4 ran for about 20 minutes before it gave up. Lots of failed tool calls. I asked codex to write a summary about both code bases. "Dev 1" Qwen 3.5 "Dev 2" Gemma 4 Dev 1 is the stronger engineer overall. They showed b…

Qwen 3.5 27B is dense, so (I think) should be compared to Gemma 4 31B.

Or Gemma-4 26B(-A4B) should be compared to Qwen 3.5 35B(-A3B)

Re: Google releases Gemma 4 open models

#262

Post by Wowfunhappy »

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!

Hi! Do you ever make quants of the base models? I'm interested in experimenting with them in non-chat contexts.

Re: Google releases Gemma 4 open models

#263

Post by Balinares »

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.

Absolutely hilarious that Qwen 3.5 had a far better clock than Opus 4.6 each time I looked.

Re: Google releases Gemma 4 open models

#264

Post by smallerize »

danielhanchen wrote: post #21
l2dy wrote: post #19

Earlier quoted context omitted.

FYI, screenshot for the "Search and download Gemma 4" step on your guide is for qwen3.5, and when I searched for gemma-4 in Unsloth Studio it only shows Gemma 3 models.

We're still updating it haha! Sorry! It's been quite complex to support new models without breaking old ones

Speaking of which, do you think Step 3.5 Flash is going to happen or should I stop holding my breath?

Re: Google releases Gemma 4 open models

#265

Post by mike_hearn »

whimblepop wrote: post #88
wg0 wrote: post #18

Google might not have the best coding models (yet) but they seem to have the most intelligent and knowledgeable models of all especially Gemini 3.1 Pro is something. One more thing about Google is that they have everything that others do not: 1. Huge data, audio, video, geospatial 2. Tons of expertise. Attention all you need was born there. 3. Libraries that they wrote. 4. Their own data centers and cloud. 4. Most of…

I recently canceled my Google One subscription because getting accurate answers out of Gemini for chat is basically impossible afaict. Whether I enable thinking makes no difference: Gemini always answers me super quickly, rarely actually looks something up, and lies to me. It has a really bad unchecked hallucination problem because it prioritizes speed over accuracy and (astonishingly, to me) is way more hesitant to…

My wife was amazed to discover that Gemini recommended to her a local business that turned out to be in another country, and then after she checked and corrected it, it recommended a second that was marked as permanently closed on Google Maps.

ChatGPT got it right first time. Baffling.

Re: Google releases Gemma 4 open models

#266

Post by retinaros »

lostmsu wrote: post #236
retinaros wrote: post #223

Earlier quoted context omitted.

what the sorcery is that https://static.simonwillison.net/static/2024/recraft-ai-peli... I tried their model and asking a few different svg of pelicans. it is INSANE.

AFAIK that model is pretty old, and it was explicitly trained for SVG generation. For other models the capability of generating SVGs of real stuff is accidental. Same as GPT-5.x and Sonnet 4.5+ being able to generate MIDI music.

is it a fine tune of some open source model?

Re: Google releases Gemma 4 open models

#267

Post by markab21 »

coder68 wrote: post #197
kcb wrote: post #165

Earlier quoted context omitted.

Nemotron 3 Super was released recently. That's a direct competitor to gpt-oss-120b. https://developer.nvidia.com/blog/introducing-nemotron-3-sup...

I gave it a whirl but was unenthused. I'll try it again, but so far have not really enjoyed any of the nvidia models, though they are best in class for execution speed.

I'll pipe in here as someone working on an agentic harness project using mastra as the harness.

Nemotron3-super is, without question, my favorite model now for my agentic use cases. The closest model I would compare it to, in vibe and feel, is the Qwen family but this thing has an ability to hold attention through complicated (often noisy) agentic environments and I'm sometimes finding myself checking that i'm not on a frontier model.

I now just rent a Dual B6000 on a full-time basis for myself for all my stuff; this is the backbone of my "base" agentic workload, and I only step up to stronger models in rare situations in my pipelines.

The biggest thing with this model, I've found, is just making sure my environment is set up correctly; the temps and templates need to be exactly right. I've had hit-or-miss with OpenRouter. But running this model on a B6000 from Vast with a native NVFP4 model weight from Nvidia, it's really good. (2500 peak tokens/sec on that setup) batching. about 100/s 1-request, 250k context. :)

I can run on a single B6000 up to about 120k context reliably but really this thing SCREAMS on a dual-b6000. (I'm close to just ordering a couple for myself it's working so well).

Good luck .. (Sometimes I feel like I'm the crazy guy in the woods loving this model so much, I'm not sure why more people aren't jumping on it..)

Re: Google releases Gemma 4 open models

#268

Post by drob518 »

jeffbee wrote: post #27
jwr wrote: post #3

Really looking forward to testing and benchmarking this on my spam filtering benchmark. gemma-3-27b was a really strong model, surpassed later by gpt-oss:20b (which was also much faster). qwen models always had more variance.

Does spam filtering really need a better model? My impression is that the whole game is based on having the best and freshest user-contributed labels.

He said it’s a benchmark.

Re: Google releases Gemma 4 open models

#269

Post by [deleted] »

matja wrote: post #50
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.

[deleted]

Re: Google releases Gemma 4 open models

#270

Post by petu »

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?

It means that model was tuned to to act as chat bot. So write a reply on behalf of assistant and stop generating (by inserting special "end of turn" token to signal inference engine to stop generation).

Base model (without instruction/chat tuning) just generates text non stop ("autocomplete on steroids") and text is not necessarily even formatted as chat -- most text in training data isn't dialogue, after all.

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