AI Judge changed title after evaluation, original title: "Google releases Gemma 4 12B, a unified open multimodal model that outperforms the larger Gemma 3 27B"
The model runs locally on laptops with 16GB VRAM.
Armand Joulin#874
Meet Gemma 4 12B!
A unified, encoder-free multimodal model designed to bring high-performance intelligence directly to your laptop, and released under an Apache 2.0 license.
Bridging the gap between edge efficiency and advanced reasoning. Here is what’s new with Gemma 4 12B: 👇
Many users praised Gemma 4 12B's unified multimodal architecture and local laptop performance for delivering strong open capabilities, while others called it basic or unsuitable for tasks like ASR.
Today we’re introducing Gemma 4 12B — our latest open model that brings advanced agentic reasoning, vision and audio directly to your laptop.
It delivers performance nearing our larger Gemma models with a much smaller total memory footprint, while being small enough to run locally with just 16GB of VRAM. It’s open and accessible for everyone to use under a permissive Apache 2.0 license.
This is all made possible by our new, unified architecture that removes separate multimodal encoders. Here’s how we did it 🧵
Gemma 4 12B can now run locally on just 8GB RAM via Dynamic GGUFs.
Google's new model, Gemma 4 12B Unified supports image, audio and 256K context.
You can run and train the model via Unsloth Studio.
GGUF: https://huggingface.co/unsloth/gemma-4-12b-it-GGUF Guide: https://unsloth.ai/docs/models/gemma-4
Meet Gemma 4 12B!
A unified, encoder-free multimodal model designed to bring high-performance intelligence directly to your laptop, and released under an Apache 2.0 license.
Bridging the gap between edge efficiency and advanced reasoning. Here is what’s new with Gemma 4 12B: 👇
Our new Gemma 4 12B model hits a sweet spot between size + performance: it can run locally on a laptop, while enabling powerful multi-step reasoning and agentic workflows. Can’t wait to see what the community does with this one!
Celebrating the milestone of a massive 150+ million downloads of Gemma 4 with the release of the new Gemma 4 12B model! It's incredibly powerful for such a small model and it’s tiny enough to run locally on a laptop with just 16GB VRAM. Apache 2.0 license - happy building!
Unlock local, agentic workflows with Gemma 4 12B and Google AI Edge, directly on your laptop. Experience 100% on-device AI:
• Generate code in AI Edge Gallery (new to Mac) • Dictate and edit text via AI Edge Eloquent (new to Mac) • Serve Gemma 4 12B locally with LiteRT-LM
Dive in: http://goo.gle/4uQlVfq
2-bit Gemma 4 12B GGUF, only 4.66 GB on disk, managed to cite 15 sites from a single prompt.
Try this locally on >6GB RAM via Unsloth Studio.
GitHub: https://github.com/unslothai/unsloth
Gemma 4 12B can now run locally on just 8GB RAM via Dynamic GGUFs.
Google's new model, Gemma 4 12B Unified supports image, audio and 256K context.
You can run and train the model via Unsloth Studio.
GGUF: https://huggingface.co/unsloth/gemma-4-12b-it-GGUF Guide: https://unsloth.ai/docs/models/gemma-4
Super excited to introduce Gemma 4 12B! 💎
- Multimodal: audio, image, video, and text input - Novel architecture: we removed the multimodal encoders for a unified, streamlined arch - New MacOS desktop app powered by LiteRT - MTP support
Excited to see what you build with it!
🚀 Gemma 4 12B is here!
We partnered with @GoogleDeepMind to bring and optimize their new dense and unifed multimodal model for Apple Silicon.
◈ 12B dense · 256K context ◈ Thinking mode (built-in reasoning) ◈ Vision: dynamic res, OCR, UI + charts ◈ Native audio: ASR + speech translation ◈ Function calling for agents ◈ Text + image + audio, interleaved
Runs local. Get started now ⚡
> uv pip install -U mlx-vlm
https://github.com/Blaizzy/mlx-vlm
Meet Gemma 4 12B!
A unified, encoder-free multimodal model designed to bring high-performance intelligence directly to your laptop, and released under an Apache 2.0 license.
Bridging the gap between edge efficiency and advanced reasoning. Here is what’s new with Gemma 4 12B: 👇
Celebrating the milestone of a massive 150+ million downloads of Gemma 4 with the release of the new Gemma 4 12B model! It's incredibly powerful for such a small model and it’s tiny enough to run locally on a laptop with just 16GB VRAM. Apache 2.0 license - happy building!
Meet Gemma 4 12B!
A unified, encoder-free multimodal model designed to bring high-performance intelligence directly to your laptop, and released under an Apache 2.0 license.
Bridging the gap between edge efficiency and advanced reasoning. Here is what’s new with Gemma 4 12B: 👇
For the past years my research focus was on unifying models and training paradigms across modalities. Today I'm excited that we're releasing our latest model aligned with this theme:
Gemma 4 12B, a dense encoder-free model which processes raw text, image, and audio inputs!
1/
Gemma 4 12B is here!
Dense, mid-sized Gemma that fits right on your laptop - released by @google under Apache 2.0
Available now in LM Studio https://lmstudio.ai/models/google/gemma-4-12b
We’re launching Gemma 4 12B: Our unified, encoder-free model that brings powerful multimodal intelligence straight to your laptop 🚀
The model bridges the gap between our mobile E4B model and larger 26B MoE models, packaging frontier-class reasoning and native audio into a highly optimized footprint, all under a permissive Apache 2.0 license.
Here’s what makes it unique:
+ Encoder-Less Architecture: We removed the multimodal encoders. The vision and audio inputs flow directly into the LLM backbone. + Agentic Performance (16GB VRAM): Run complex, multi-step workflows locally, with performance nearing our 26B model.
I have 256 applications for this
Meet Gemma 4 12B!
A unified, encoder-free multimodal model designed to bring high-performance intelligence directly to your laptop, and released under an Apache 2.0 license.
Bridging the gap between edge efficiency and advanced reasoning. Here is what’s new with Gemma 4 12B: 👇
Check out our Gemma 4 12B model: it's a super capable open weights model that can run directly on your laptop.
Meet Gemma 4 12B!
A unified, encoder-free multimodal model designed to bring high-performance intelligence directly to your laptop, and released under an Apache 2.0 license.
Bridging the gap between edge efficiency and advanced reasoning. Here is what’s new with Gemma 4 12B: 👇
Congrats to the @googlegemma team on the Gemma 4 12B launch 🎉 Day-0 support on vLLM is ready to go.
It's an encoder-free unified multimodal model — text, image, audio, and video all project straight into the LLM's embedding space, no separate vision or audio towers. 256K context, built-in thinking, native tool calling.
Reasoning + tool parsers (`gemma4`), vision, and audio all served through the OpenAI-compatible API.
🔗 Recipe: http://recipes.vllm.ai/Google/gemma-4-12B-it
Meet Gemma 4 12B!
A unified, encoder-free multimodal model designed to bring high-performance intelligence directly to your laptop, and released under an Apache 2.0 license.
Bridging the gap between edge efficiency and advanced reasoning. Here is what’s new with Gemma 4 12B: 👇
We just launched a Gemma 4 12B! Our first mid-sized model with native audio inputs. Gemma 4 12 B is a unified, encoder-free multimodal model.
🧠 vision and audio directly into the LLM. 💻 Just need 16GB of memory. 📊 Benchmark nearing 26B. 📄 Apache 2.0.
✨ Introducing @GoogleGemma 4 12B, a unified open model bringing high-performance agentic multimodal intelligence directly to your laptop.
Bridging the gap between edge efficiency and advanced reasoning, nearing 26B MoE at <50% the memory footprint.
Woah the mad men did it and keep dropping
Absolute banger at 12b
That’s probably the sweet spot for small local GPUs
Meet Gemma 4 12B!
A unified, encoder-free multimodal model designed to bring high-performance intelligence directly to your laptop, and released under an Apache 2.0 license.
Bridging the gap between edge efficiency and advanced reasoning. Here is what’s new with Gemma 4 12B: 👇
Gemma 4 12B shipped today under the label "encoder-free."
A local 12b model that shows really good results. I'm a big fan of Gemma Gemma 4 12B is out: a dense, fully open model (Apache 2.0) that runs on a 16GB laptop and does agentic reasoning, vision and audio at a quality Google puts near its 26B model.
The reason a 12B can pull this off: Google removed the separate vision and audio encoders and feeds both straight into the model, which keeps the memory footprint small enough for consumer GPUs.
For on-device assistants and private coding agents, that lowers the bar a lot. always look forward to the updates. 12b is a good sweet spot in terms of size.
a few facts:
Vision: the 550M encoder (27 transformer layers) is now a 35M embedder, one matmul on 48x48 pixel patches. Roughly 15x smaller. Audio: the 300M encoder (12 conformer layers) is gone. Raw 16kHz audio cut into 40ms frames, projected straight into the LLM. So encoding didn't vanish, it collapsed into the backbone. The payoff is real: one shared set of weights, so you LoRA-tune vision, audio and text in a single pass.
Today we’re introducing Gemma 4 12B — our latest open model that brings advanced agentic reasoning, vision and audio directly to your laptop.
It delivers performance nearing our larger Gemma models with a much smaller total memory footprint, while being small enough to run locally with just 16GB of VRAM. It’s open and accessible for everyone to use under a permissive Apache 2.0 license.
This is all made possible by our new, unified architecture that removes separate multimodal encoders. Here’s how we did it 🧵
Google dropped Gemma-4 12B, it's a beast 🔥
> unified: audio + image go straight into model, no encoder > multimodal + tool calling > dense 12B with 256K context, comes with assistants for MTP (faster!⚡️) > day-0 in transformers, llama.cpp & MLX > A2.0 🤗
Cool multimodal architecture. Raw images and audio are patchified and slices respectively with a single linear projection into the same space as text tokens.
Would be cool if anyone can turn it into a psuedo-realtime interaction model
Meet Gemma 4 12B!
A unified, encoder-free multimodal model designed to bring high-performance intelligence directly to your laptop, and released under an Apache 2.0 license.
Bridging the gap between edge efficiency and advanced reasoning. Here is what’s new with Gemma 4 12B: 👇
