@googlegemma
The official home of Google's Gemma. Lightweight, state-of-the-art open models by Google DeepMind, built on Gemini tech. What will you build? 🚀💻
"DiffusionGemma as Jev" showcases the power of non-autoregressive architectures. While Jev demonstrates the value of rapid decision models, running DiffusionGemma in this paradigm leverages canvas diffusion to evaluate structured choices in a single parallel pass: ⚡ ️Massive Parallelism: Denoises across an open canvas in a single step instead of sequential autoregressive token generation (~0.2s on a DGX spark). 🧠 Full Bidirectional Attention: Allows every option to attend to the full context concurrently, yielding well-calibrated decision distributions. 👁️ Multimodal Grounding: Inherits Gemma 4's spatial vision capabilities for complex visual and text decisions. Read more about this approach here: t.co/hCEg276mzA t.co/vRLhy6KECT
Matt Mastracci@mmastrac·I ran some real, live evals on Jev vs DiffusionGemma-as-Jev (my patch for vLLM!) DiffusionGemma comes out as the winner, I think. Headlines: Is Jev faster than DiffusionGemma? No ❌ (API vs DGX Spark) Is Jev smarter than DiffusionGemma? No ❌ (they're roughly tied!)
We prototyped a tactile desk robot using LEGO, a Raspberry Pi, and a hybrid LLM setup: ✨ Gemma 4 runs locally for instant, private zero-cost chat ✨ Auto-escalates to Gemini Flash for complex reasoning & code Here’s how we wired and coded DinoDesk AI: dev.to/googleai/how-w…
We prototyped, a tactile desk robot using LEGO, a Raspberry Pi, and a hybrid LLM setup: ✨ Gemma 4 runs locally for instant, private zero-cost chat ✨ Auto-escalates to Gemini Flash for complex reasoning & code Here’s how we wired and coded DinoDesk AI: dev.to/googleai/how-w…
We prototyped, tactile desk robot using LEGO, a Raspberry Pi, and a hybrid LLM setup: ✨ Gemma 4 runs locally for instant, private zero-cost chat ✨ Auto-escalates to Gemini Flash for complex reasoning & code Here’s how we wired and coded DinoDesk AI: dev.to/googleai/how-w…
Looking for a better local model that runs on a MacBook Air? Our latest update brings full Gemma 4 12B support to Google AI Edge Gallery app on Mac. ✨ Multimodal: Vision & Audio inputs 🎛️ Configurable vision token budgets ⚡️ MTP for blazing-fast inference 💻 Optimized to run on 16GB Macs! Download it today: t.co/Zl7qtarGVm
Access the updated Gemma 4 12B file: huggingface.co/litert-communi… Quickly try Gemma using LiteRT-LM CLI: ai.google.dev/edge/litert-lm… Learn more about building with LiteRT-LM: developers.google.com/edge/litert-lm…
Standup Pulse: an open-source project running async Slack standups using Gemma 4 26B-A4B (GGUF via llama.cpp) on an Apple M5 Max. It pairs Mastra for typed tool selection with CopilotKit Channels for restrained Slack Block Kit (Slack's native layout format) interactions while keeping all model inference, standup records, and traces local in SQLite. This architecture is a great demonstration of how to connect Slack to a project without exposing the local server! 🔗 Blog: t.co/N74B7xRPU2 🔗 Repo: t.co/COiKqsCzSg
Running AI in space requires strict power and bandwidth management. Satlyt is deploying Gemma directly on satellites to analyze telemetry and diagnose faults locally. Running Gemma 3 1B onboard cuts diagnostic data payloads by over 64%, turning raw system logs into compact summaries before they are sent back to Earth. Next launch target: Gemma 4 E2B on NVIDIA Jetson Orin Nano to provide further reasoning and vision capabilities at the edge… of space.
Read the full case study: deepmind.google/models/gemma/g…
Sign language AI should not depend on Wi-Fi or expect Deaf folks to do all the adapting. Meet KawanIsyarat, a local-first mobile tool bridging BISINDO and spoken Indonesian offline using Gemma 4. Gemma 4 handles all vision, audio, and text processing directly on-device. Congrats to the team on their Cactus category win for the Gemma 4 Good Hackathon.
Read the technical write-up to see how the team deployed Gemma 4 E2B fully offline using the Cactus SDK: kaggle.com/competitions/g…
You don't need to be a command-line expert to run local AI. t.co/emHfVbIFAH wraps the heavy lifting of llama.cpp into a clean UI, making it simple to deploy and manage models like Gemma 4. Instead of dealing with config files, you get one-click model downloads, clear memory estimates, and no coding required! Watch the video to see Gemma 4 in action as it parses tables from receipts, streams reasoning logs, and connects to MCP for web search.
Original post by @mervenoyann: lnkd.in/p/e2p9q7xM
Stitching AI video is easy; keeping the story coherent is hard. This new ComfyUI sampler enables longer videos by processing them in chunks (saving VRAM). To keep scenes consistent, Gemma 4 runs under the hood to write the continuous prompts to keep characters, backgrounds and camera movements consistent between chunks.
Try the ComfyUI-HR-Endless-Sampler node here: github.com/hradec/ComfyUI… And check out original post by @aisearchio here:
AI Search@aisearchio·This HR Endless Sampler lets you generate much longer videos with MiniMax H3, even with low vram. It works by breaking the video into smaller chunks so it uses less memory, then uses Gemma 4 to write a new prompt for each next chunk so the whole video stays consistent. t.co/BNFTnWxvAg
Deploying AI at the edge makes local public service tools practical and accessible. PreVillage connects citizens in Nepal to government services over WhatsApp. Powered by Gemma via llama.cpp on a Raspberry Pi, it cleans raw speech transcripts, reasons through user intent, and retrieves verified public sources directly on-device. Congrats on the llama.cpp prize winner for the Gemma 4 Good Hackathon!
Read the technical write-up to explore their self-healing RAG pipeline and Raspberry Pi deployment: kaggle.com/competitions/g…
Gemma is only as powerful as the community building with it. We launched awesome-gemma to highlight amazing community-made tools, research, and applications in the ecosystem. What have you built? Drop a link below or submit a PR to get featured: github.com/google-gemma/a…
Great news for app developers who want to code on the go! Gemma 4 is now the recommended local model provider in Android Studio! Make code changes completely offline in agent mode with zero token quotas. With a local AI coding agent, your code never leaves your machine!
Download Android Studio today! developer.android.com/studio?gclsrc=…
Running Gemma 4 26B A4B on a Mac just got 2x faster! The developer community has been grinding on the mlx.fast leaderboard, pushing Apple Silicon to its limits.
Read the full details in the original post by @pratikg here:
Pratik Gandhi@pratikg·JUST IN: Gemma 4 26B A4B runs 2x faster on Mac MLX work by humans pointing GPT-5.6, Claude Qwen3, MiniMax at an open t.co/uFpHiT9o9m leaderboard on @YukonResearch. jacklightChen did the hard part and got it to 99.8%. I turned up 24 mins later, added 0.33%. (me on the leaderboard again!) Open frontier research accelerates open intelligence.
The latest technology should be accessible to the elderly, empowering them to navigate a changing world on the devices they already own. Powered by LiteRT-LM, Google AI Edge’s high-performance framework for running AI models locally on edge devices, Gilbeot (길벗) brings multimodal AI directly to Android phones. To run efficiently even on older devices like the Galaxy S10e, the developers directly grafted custom speech LoRAs into the model bundle, delivering real-time, offline voice navigation without costly hardware upgrades. Watch the project video:
Read the full write-up to see how the team built the app: kaggle.com/competitions/g…
Gemma 4 E2B running fully locally on an 8GB NVIDIA Jetson Orin Nano. Using native image/audio input and function calling, this edge setup is capable of vision, voice interaction, and camera control, all within an 8GB memory footprint!
Check out the full project breakdown and demo from @ilhamfputra:
ilham@ilhamfputra·Can Gemma run locally on an 8GB Jetson Orin Nano, with eyes, ears, a voice, and control of its camera? Last weekend I found out: Yes :) Gemma 4 E2B is the only open-weight model I found that fits this 8GB stack with native image/audio input and function calling Take a look👇 x.com/ivanleomk/stat…
Addressing the world's most pressing challenges requires robust solutions. These Gemma 4 Good projects fine-tuned models to address key challenges in anticipating and mitigating problems that affect our environment and society. This Global Resilience Prize winner, Acuífero·Vigía, provides an offline disaster response system for early flood warnings in Argentina. Powered by Gemma 4 E2B running entirely locally on Raspberry Pi and Android phones, it fuses real-time visual camera data with local citizen voice reports to track water rise and issue critical alerts without relying on cloud connectivity. Watch the project video: t.co/rHbt664MY6
OceanGuard AI brings agentic marine debris detection directly on-device using Gemma 4 E2B. By processing data locally, it empowers conservation efforts in remote ocean environments where internet connectivity is severely limited or non-existent. Watch the project video: t.co/8kdQDIyCwc
3,431 tokens/s on Gemma 4 31B! Recent benchmarks on NVIDIA's Groq 3 LPX accelerator show a median output of ~3,400 tokens/s across both 10k and 100k input sequences, the fastest 100k-context speed recorded for the model to date.
See the full benchmark results: NVIDIA's Groq 3 LPX announcement: nvidianews.nvidia.com/news/nvidia-gr…
Artificial Analysis@ArtificialAnlys·Artificial Analysis has measured 3,431 tokens/s on Gemma 4 31B via a private demonstration endpoint for NVIDIA Groq 3 LPX - the highest 100k-context output speed we have measured for Gemma 4 31B on either a private or public endpoint @nvidia announced today that the Groq 3 LPX ‘interactive AI inference’ rack is in full-scale production and will enter operation later this year. NVIDIA granted us early access to a private deployment of the rack serving Gemma 4 31B for benchmarking purposes We ran the standard 1k, 10k and 100k input sequence length prompts that we use for benchmarking serverless API providers. At both the 10k and 100k input sequence lengths, the endpoint delivered a median output speed of approx. 3,400 tokens/s, measured over 50 sequential (single-concurrency) requests. Output speed was maintained between the 10k and 100k input sequence lengths tested, indicating robust long-context inference performance Congratulations to the @nvidia team on the launch!
Fast and local voice typing with Gemma 4. Phonon demonstrates the utility of lightweight, on-device models for privacy-preserving workflows. This open-source voice typing tool runs Gemma 4 (E2B 4-bit) locally via MLX to process audio and screen context without cloud routing.
Original post by @elliotarledge Resources: - GitHub Repo: github.com/Infatoshi/phon… - Gemma 4 (MLX): huggingface.co/mlx-community/…
Elliot Arledge@elliotarledge·Introducing Phonon! Fast, local, open-source voice typing with parakeet and gemma 4. Uses OCR for screen context and stays minimal so you can focus on expressing your thoughts to models. Download at phonon.sh and repo below!
The wait is over. 🏆 We challenged you to use Gemma 4 to tackle real-world problems for the Gemma 4 Good Hackathon. Your submissions set a new standard for technical excellence and real-world impact. Meet the innovators who took home the top prizes.
🥇 1st Place: GEM-4 (Gemma Embodied 4 Physical Assistance) This amazing project uses Gemma 4-E2B to power a wearable Vision-Language-Action (VLA) robotic assistant. Acting as a "second arm" for individuals with visual or upper-limb impairments, it assists with unpredictable daily tasks like opening doors or retrieving objects. Watch the project video: t.co/27ckg51SjY
You don't always need a frontier model. A recent benchmark found that Gemma 4 31B matches Sonnet 5 on answer quality at ~40x lower cost. With high cost-efficiency and low latency, Gemma unlocks high-volume use cases that are uneconomical with larger models.
Read the full article from AlphaSense: alpha-sense.com/resources/prod…
Tonight we’re gathering in SF to celebrate 1 BILLION Gemma downloads! While we can only fit a few of you in the room, we’ll be raising a glass to the millions of developers worldwide who are driving the Gemmaverse forward. 🥂 To celebrate, we rounded up some of the most out of this world ways you're using Gemma. From space operations to breakthroughs in medicine, plus a new GitHub repo to help you build! Check it out: t.co/aDLLR8JqvU
What if your notebook could write back ✍️ Check out this interactive journal running locally on an iPad. Powered by Gemma and Apple MLX, it features real-time text, dynamic visuals, and audio, all processed at the edge.
Check out original post by @ivanfioravanti here:
Ivan Fioravanti ᯅ@ivanfioravanti·MLX: Tom Riddle's diary running locally on an iPad powered by Apple MLX with Gemma 4 E4B behind the scene. Children can go crazy for something like this, no? 🔥
At 100 mph, there is no room for lag! Google Developer Experts built a real-time AI Race Coach at Sonoma Raceway. By running Gemma 4 locally on the Pixel 10, they delivered split-second, zero-latency audio coaching directly to the driver while out on track.
See how Gemma 4 and Google Antigravity turned live racing data into real-time track advice. Read the full story: developers.googleblog.com/bridging-the-d…
Bringing open models into the physical world. Check out this vibrant local assistant build from the Gemma 4 Good Hackathon. YANVI runs Gemma 4 locally on edge hardware, featuring a physical presence, an expression engine, and full desktop autonomy.
Original post and build by @HeyYanvi:
Raghu · Founder, Yanvi Robotics@HeyYanvi·AI doesn't belong in a tab. I submitted YANVI to the Gemma 4 Good Hackathon: local Gemma 4 E2B running through llama.cpp on edge hardware, wrapped in a physical AI presence with expression engine, screen awareness, and desktop autonomy. Powered by Hermes. Kickstarter in October.
Ever wonder what makes Gemma 4 12B so unique? In this 2 minute overview series, learn what an encoder-free model is and how Gemma 4 12B processes image and audio inputs differently from the rest of the Gemma family!
Ready to dive deeper into Encoder-Free Gemma 4? Check out these resources to get started: - Hugging Face: huggingface.co/google/gemma-4… - GitHub: github.com/google-gemma/g… - Visual Guide (via @MaartenGr): newsletter.maartengrootendorst.com/p/a-visual-gui…
Can a $175 board power an offline robot voice assistant? 🤖 It’s cool to see Gemma 4 E2B powering the Reachy Mini robot entirely locally on a Raspberry Pi 5. Inference powered by LiteRT, it handles low latency voice, vision (YOLO) and robot movement completely offline. With text generation 2x normal human speech (~300 words per minute) on just 1.5GB of memory, the Pi 5 + Gemma 4 + LiteRT combo is a demonstration of how lean edge AI can be!
Time to build physical agents with zero cloud dependencies 🙌. What’s your first project? Read the full announcement here: developers.googleblog.com/en/mastering-e…
🎉 1 BILLION DOWNLOADS 🎉 To celebrate this exciting milestone, we’re hosting an exclusive evening in SF on Aug 20 dedicated to YOU, the open-source builders, researchers, and contributors driving the Gemmaverse forward. Space is limited. Apply for your spot here: t.co/xmVMbm8g5d
The complete DiffusionGemma technical report is officially live! We're sharing our full process and insights to help the community explore the incredible potential of text diffusion. We’re excited to see how this approach drives new research and applications.
Link to tech report: arxiv.org/abs/2608.00146
Check out this interesting demo from the latest Gemma 4 hackathon. This live meeting copilot runs at 1,000+ tok/s, turning spoken conversations into working prototypes before the meeting even ends.
Original post and build by @igorls: x.com/igorls1/status…
Meet the Gemma Translator! A fully offline device powered by Gemma 4 E2B built with @Antigravity. Running entirely on a Raspberry Pi 5 with a connected microphone and speaker, this highly portable prototype is housed inside a custom, 3D-printed case.
Want to recreate this? All code (and even the .stl files for printing) are open-sourced: github.com/google-gemma/g…
Wonder what the “E” stands for in E2B and E4B models? Look no further! Learn more about these “effective” parameters, Per-Layer Embeddings (PLE), and how they boost a model's power without increasing the actual parameters used during computation in this 2-minute overview.
Ready to dive deeper into Per-Layer Embeddings? Check out these resources to get started: - Hugging Face: huggingface.co/google/gemma-4… - GitHub: github.com/google-gemma/g… - Visual Guide (via @MaartenGr): newsletter.maartengrootendorst.com/p/a-visual-gui…
Gemma 4 running on an iPhone with just ~500 MB of RAM! User Antikythera on r/LLMDevs shared their calibration-aware quantization approach to shrink Gemma 4 keeping speed and accuracy on an iPhone. They demoed it using an offline assistant that manages calendar actions with just ~516 MB of active RAM.
Hugging Face: huggingface.co/fraQtl/Gemma-4… Read the full breakdown to understand the goal of “smarter bits, not more bits”: reddit.com/r/LLMDevs/comm…
Running Gemma 4 26B locally with zero GPUs? Very cool. Running it on a 13-year-old Xeon CPU? Wild! It just shows us how far you can push older gear. It’s a great reminder that you don't need modern hardware to try the latest models.
Here are a couple of great articles: neomindlabs.com/2026/06/08/run… by NeoMind Labs point.free/blog/gemma-4-o… by @cafkafk
Ambient, real-world context is the future of AI! 🕶️ Check out this Gemma 4 hackathon demo: it captures input via smart glasses, processes context through a custom engine, and runs lightning-fast inference on high-performance hardware. See it in action!
Built by @sinain_hud Watch the demo: youtu.be/fI1ucW0dyHI?si… See the original post: x.com/sinain_hud/sta…
Ever thought about running your own personal AI assistant? It's great to see Gemma 4 26B stepping in to power these kinds of everyday workflows. This tutorial walks through setting up OpenClaw, showing how a local Gemma model can take on 90% of the daily task load.
Read Alan Williamson’s walkthrough on configuring OpenClaw, optimizing memory, and building custom skills for a local agent here: alan.is/2026/07/15/ope…
Know someone who needs to get up to speed with Gemma 4? Send them this 2 minute crash course! With 5 different model sizes (E2B all the way to 31B) and 4 unique architectures, Gemma 4 is a great model for your local use cases.
Ready to dive deeper? Check out these resources to get started: - Hugging Face: huggingface.co/collections/go… - Github: github.com/google-gemma - Docs: ai.google.dev/gemma/docs/core - Visual Guide (via @MaartenGr): newsletter.maartengrootendorst.com/p/a-visual-gui…
Hybrid models efficiently route complex tasks to larger cloud models, but how do you go about creating one? 🤔 Cactus solved this by post-training Gemma 4 to return a confidence score for every prompt. Process the prompt locally when confidence is high, route to a larger model when confidence is low. Routing only happens 15%-55% of time based on domain benchmarks.
Cactus Hybrid is open-weights, is based on Gemma 4 E2B and is ready to run on MLX, llama.cpp, transformers, and Cactus. Explore the code and models: - GitHub: github.com/cactus-compute… - Hugging Face: huggingface.co/collections/Ca…
Explore a new community-built playground allowing you to try Gemma models right in your browser, no installation needed! You no longer need to jump between repositories. Explore an interactive timeline of our models, then switch over to the playground to test them securely on-device! Powered by WebGPU & Transformers.js, test 10+ models and explore the interactive "Gemma Journey" timeline.
Try it out: web-gemma.vercel.app GitHub repository: github.com/NSTiwari/WebGe… Built by @NSTiwari21
This week, Gemma surpassed 900 million downloads! 🎉 All the way from Gemma 1 and ShieldGemma to MedGemma and Gemma 4, we'll keep supporting open source. More to come!
What happens when you put Gemma 4 into the hands of developers across 20+ countries? So much innovation! Like this app that turns an image prompt into a working web app in seconds, running on-device! Want to get involved? Join or host an event!
Everything you need to get started: Find a hackathon in your area: luma.com/gemma-naek Apply for sponsorship: goo.gle/build-with-gem… Original hackathon project post: x.com/theShawwwn/sta…
Gemma 4 just crossed 300 million downloads. Thank you to the developers, researchers, and open-source community building with us. Your work and feedback drive this project forward. Let's keep building!
Racing into the future at Goodwood Festival of Speed!🏎️⚡️ We teamed up with Formula E to showcase a next-gen onboard AI assistant, powered by Gemma open models! Here is a look at the tech stack built by the Formula E team:
- @Raspberry_Pi streams telemetry directly to the Pixel 10 Pro for local database storage - Pixel 10 Pro processes telemetry via AICore (ML Kit) for handling real-time driver voice queries - Gemma 4 E2B/E4B optimized to run on <1.45GB VRAM - Gemma operates as a local ADK-powered agent, syncing via A2A with a @googlecloud agent for post-race analytics
Extremely fast multimodal inference! Damage Scout uses Gemma 4 on @cerebras running at an impressive 2,300+ toks/s! It analyzes rental car walkaround videos and generates annotated damage reports with box coordinates in <6 seconds.
Built on the blazing fast infrastructure over at @Cerebras! Watch the full demo and breakdown here: x.com/cerebras/statu…
Voice AI without the wait! ⏱️ Thanks to Hugging Face and Cerebras, developers can now use the Gemma 4 31B model as the brain for voice AI at ultra-fast inference speeds. Add it to a fully open-source, cascaded speech-to-speech stack that can be used to power existing voice apps! 🗣️
Try the demo by @andimarafioti and team: huggingface.co/spaces/smolage… Read the blog: huggingface.co/blog/cerebras-…
Build with Gemma community hackathons are going on now in over 20 countries. Join a hackathon near you to create awesome AI applications with Gemma 4, or apply to host your own!
Find an event near you: luma.com/gemma-naek Apply for sponsorship: goo.gle/build-with-gem…
Ready to customize Gemma, but not sure how? Have your agents assist you by using the gemma-trainer skill! It helps agents set your training configs, manage training runs and evaluate results. Let’s make fine-tuning Gemma 4 possible for everyone!
You can find more information at the links before: - Gemma Skills repo: github.com/google-gemma/g… - Blog post: dev.to/googleai/maste…
Every millisecond counts for voice agents. Introducing Gemma 4 31B on LiveKit Inference! Optimized for real-time voice agents: - 354ms time to first audio - 192ms time to first token - Beats GPT-4.1 in agentic tool use (31B achieves 76.9% on tau2bench) Fast, capable, and efficient!
Learn more and test the integration right here: livekit.com/products/infer…
We’re rolling out some big improvements to Gemma 4, fueled by incredible community feedback and contributions! Here is a breakdown of what’s being fixed and updated in this release: 🧵👇
🏎️ Flash Attention: We've enabled uniform Flash Attention 4 (FA4) support on NVIDIA Hopper GPUs! Expect prefill throughput to jump by 25-70% and time-to-first-token (TTFT) to drop by up to 31%. ⚡ (2/5)
An offline AI tutor, a medieval bard, and a real-world adventure game. What do they have in common? They were all built using Gemma 4! With MTP, our 12B Unified model, and QAT checkpoints, you get ultimate flexibility. Deploy anywhere from edge to workstation under Apache 2.0.
Read the full blog: blog.google/innovation-and…
Read the full article by @cerebras: cerebras.ai/blog/gemma-4-o…
