Image created with gemini-3.1-flash-image-preview with claude-opus-4.7. Image prompt: A 16:9 flat matte op-art cover in the style of Julio Le Parc, the word LOCAL centered in bold letters built from concentric ROYGBIV rainbow bands with violet outermost stepping inward to red, a single continuous banded rainbow ribbon arching over the letters to form a simple pitched house roof and chimney enclosing the word, on a clean off-white background with generous negative space, crisp screen-printed edges, no shadows or gradients.
Introducing Gemma 4 12B
https://blog.google/innovation-and-ai/technology/developers-tools/introducing-gemma-4-12B/
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
https://x.com/Google/status/2062203526588088452
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://x.com/UnslothAI/status/2062470072179044447
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
https://x.com/vllm_project/status/2062228047324201166
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/
https://x.com/mtschannen/status/2062236357351579915
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://t.co/8cL321pVDh Guide:
https://x.com/UnslothAI/status/2062207258810053084
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: 👇
https://x.com/googlegemma/status/2062202706882883696
Our new unified architecture allows Gemma 4 12B to process multimodal inputs natively. Here’s how ⬇️ Traditional models rely on separate encoders for images and audio. This adds latency and increases memory usage. So we streamlined this: 👁️ Vision: We took a novel approach to
https://x.com/Google/status/2062203532351090824
Today we’re shipping our biggest MLX-VLM release yet: v0.6.0 …and we are raising 💸 This one’s about turning your Apple devices into real local agent machines. From your desk to your pocket. What’s new: ⚡ Speculative decoding everywhere — Gemma 4 EAGLE3 + DFlash, Qwen
https://x.com/Prince_Canuma/status/2061541992790683726
We released Gemma 4 12B yesterday. Here is a visual guide that explains the full architecture. → How encoders typically connect modalities to LLMs → Why Gemma 4 removed the vision and audio encoders → How a single 12B model can handle text, images, and audio without
https://x.com/_philschmid/status/2062546814075609413
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
https://x.com/googleaidevs/status/2062204432658386950
RTX spark running 120b parameter model locally. Ngl, pretty cool
https://x.com/kimmonismus/status/2061852979318427988
🌞This is big Local AI news! A new open-source Computer-Use LLM has just launched. Holo 3.1 is H Company’s (🇫🇷) new local computer-use agent model that beats Qwen3.5-397B, Kimi-K2.5, and Sonnet 4.6! Since it is built for local deployment → ⬩ Runs fully on your machine
https://x.com/TeksEdge/status/2061825310669332818
We’re brining local models that can run on your personal hardware inside Perplexity Computer. This will take advantage of the local hardware while giving you the privacy and token efficiency per watt, as well as access to the frontier models on the server side GPUs when
https://x.com/AravSrinivas/status/2061875858542096520
You can use Hermes Desktop with Ollama using local or cloud models. Get started 👇👇👇
https://x.com/ollama/status/2062011585355551231
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