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🚨 Google Just Made OpenClaw Free (GEMMA 4): 0:00 - Why Gemma 4 matters 0:48 - #3 open model in the world 1:24 - What Gemma 4 actually does 2:01 - What this means for OpenClaw 3:03 - How to set up Gemma 4 3:58 - My honest take... show more

Sharbel

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368,986 views • 3 months ago •via X (Twitter)

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Gemma 4 just hit 200M downloads in only 2.5 months! For context, total downloads across the entire Gemma family of models were at 100M when we launched Gemma 3. The community's acceleration is incredible. Thank you to everyone building with Gemma. Watch how developers are driving real-world impact:

Gemma 4 just hit 200M downloads in only 2.5 months! For context, total downloads across the entire Gemma family of models were at 100M when we launched Gemma 3. The community's acceleration is incredible. Thank you to everyone building with Gemma. Watch how developers are driving real-world impact:

Google Gemma

217,823 views • 19 days ago

I was wrong about Hermes Agent: 0:00 - intro 0:25 - openclaw vs hermes 1:26 - hermes agent 2:16 - the self-improving skill loop 3:06 - openclaw 3:45 - how to use both strengths 4:56 - final verdict

I was wrong about Hermes Agent: 0:00 - intro 0:25 - openclaw vs hermes 1:26 - hermes agent 2:16 - the self-improving skill loop 3:06 - openclaw 3:45 - how to use both strengths 4:56 - final verdict

Sharbel

21,286 views • 2 months ago

It’s happened. Mac Studio is here. Gemma 4 31b Google DeepMind installed, chatting with my main OpenClaw🦞 for $0 in token expenses now... I've burned $5-6k on tokens on my crazy ideas over past few months, so this mac studio should pencil out for me within 3 months or so 🤓

It’s happened. Mac Studio is here. Gemma 4 31b Google DeepMind installed, chatting with my main OpenClaw🦞 for $0 in token expenses now... I've burned $5-6k on tokens on my crazy ideas over past few months, so this mac studio should pencil out for me within 3 months or so 🤓

Jesse Genet

850,283 views • 3 months ago

We just released Gemma 4 — our most intelligent open models to date. Built from the same world-class research as Gemini 3, Gemma 4 brings breakthrough intelligence directly to your own hardware for advanced reasoning and agentic workflows. Released under a commercially permissive Apache 2.0 license so anyone can build powerful AI tools. 🧵↓

We just released Gemma 4 — our most intelligent open models to date. Built from the same world-class research as Gemini 3, Gemma 4 brings breakthrough intelligence directly to your own hardware for advanced reasoning and agentic workflows. Released under a commercially permissive Apache 2.0 license so anyone can build powerful AI tools. 🧵↓

Google

7,738,762 views • 3 months ago

What does it take to run 3, 5, or even 10 concurrent instances of Gemma 4 locally? We've open-sourced a demo letting you run multiple models side-by-side on your hardware. Gemma 4 26B A4B easily runs 10+ concurrent requests on a MacBook Pro M4 Max at 18 tokens/sec per request.

What does it take to run 3, 5, or even 10 concurrent instances of Gemma 4 locally? We've open-sourced a demo letting you run multiple models side-by-side on your hardware. Gemma 4 26B A4B easily runs 10+ concurrent requests on a MacBook Pro M4 Max at 18 tokens/sec per request.

Google Gemma

912,664 views • 2 months ago

i tested a fully local ai coding setup: gemma4 from Google DeepMind running through LM Studio, paired with pi which is a minimal open source coding harness this is part 1 of a two part series. here we cover the why and the complete hands-on setup 0:00 - Running a coding agent fully local 0:47 - Why Pi as the coding agent harness 1:39 - Why Gemma 4 and which variant to pick 2:44 - Architecture: Pi, LM Studio and Gemma 4 3:45 - LM Studio setup and model download 5:01 - Starting the local server 5:19 - API sanity check with curl 6:08 - Installing the Pi coding agent 6:20 - Configuring models.json for local models 8:20 - First run: selecting the model in Pi 8:58 - Fixing the context length error 10:16 - Testing the working setup 10:50 - What is coming in Part 2

i tested a fully local ai coding setup: gemma4 from Google DeepMind running through LM Studio, paired with pi which is a minimal open source coding harness this is part 1 of a two part series. here we cover the why and the complete hands-on setup 0:00 - Running a coding agent fully local 0:47 - Why Pi as the coding agent harness 1:39 - Why Gemma 4 and which variant to pick 2:44 - Architecture: Pi, LM Studio and Gemma 4 3:45 - LM Studio setup and model download 5:01 - Starting the local server 5:19 - API sanity check with curl 6:08 - Installing the Pi coding agent 6:20 - Configuring models.json for local models 8:20 - First run: selecting the model in Pi 8:58 - Fixing the context length error 10:16 - Testing the working setup 10:50 - What is coming in Part 2

Nidhi Singh

16,289 views • 1 month ago

The AI Agent That Got Me YouTube Monetized (With OpenClaw): 0:00 - Intro 1:06 - Problem 2:35 - Solution 2:44 - Step 1: Outliers 4:08 - Step 2: Voice 4:47 - Step 3: Interview 6:40 - Step 4: Titles 7:50 - Step 5: Scripts 8:59 - Results 10:56 - GitHub Repo 11:41 - How To Install

The AI Agent That Got Me YouTube Monetized (With OpenClaw): 0:00 - Intro 1:06 - Problem 2:35 - Solution 2:44 - Step 1: Outliers 4:08 - Step 2: Voice 4:47 - Step 3: Interview 6:40 - Step 4: Titles 7:50 - Step 5: Scripts 8:59 - Results 10:56 - GitHub Repo 11:41 - How To Install

Sharbel

143,024 views • 3 months ago

🗓️ Release Week Recap Big week. mlx-audio and mlx-vlm are now among some of the fastest-growing OSS projects. Here’s what we shipped last week. Gemma 4 on Apple Silicon Two awesome releases by our partner Google DeepMind & Google Gemma : > Gemma 4 12B — their new dense, unified multimodal model. It uses an encoder free audio path and simplified vision encoder. > Gemma 4 QAT — quantization-aware training checkpoints, optimized to run locally on consumer GPUs and edge devices, compressing the model while preserving the quality you expect from Gemma 4. On the audio 🎧 side we added support for 15+ new TTS, ASR & VAD models, faster long-form transcription, and an expanded OpenAI-compatible audio server. All local on Apple Silicon. Huge thanks to every contributor and my co-maintainer Lucas Newman. 🙏🏽

🗓️ Release Week Recap Big week. mlx-audio and mlx-vlm are now among some of the fastest-growing OSS projects. Here’s what we shipped last week. Gemma 4 on Apple Silicon Two awesome releases by our partner Google DeepMind & Google Gemma : > Gemma 4 12B — their new dense, unified multimodal model. It uses an encoder free audio path and simplified vision encoder. > Gemma 4 QAT — quantization-aware training checkpoints, optimized to run locally on consumer GPUs and edge devices, compressing the model while preserving the quality you expect from Gemma 4. On the audio 🎧 side we added support for 15+ new TTS, ASR & VAD models, faster long-form transcription, and an expanded OpenAI-compatible audio server. All local on Apple Silicon. Huge thanks to every contributor and my co-maintainer Lucas Newman. 🙏🏽

Prince Canuma

11,731 views • 1 month ago

#라이즈 챌린지 모음 0:00 댓츠노노 0:48 굿보이 1:44 Ode to love 2:27 캐치캐치 3:03 캐치캐치2 3:58 잇츠미 4:41 잇츠미2 5:26 최애의 아이 6:01 한번만 안아줘 6:50 한번만 안아줘2

#라이즈 챌린지 모음 0:00 댓츠노노 0:48 굿보이 1:44 Ode to love 2:27 캐치캐치 3:03 캐치캐치2 3:58 잇츠미 4:41 잇츠미2 5:26 최애의 아이 6:01 한번만 안아줘 6:50 한번만 안아줘2

𝗯𝟭𝗮𝗰𝗸

372,344 views • 1 month ago

i spent the afternoon experimenting with Gemma 4's vision capabilities made an app that uses roboflow RF-DETR for a first pass of object detections and Gemma to summarize the scene in one sentence for fun i asked Gemma to "describe what you see as if you were a medieval bard" all made with free local AI models (running via webgpu in the browser thanks to transformers js) lots more possibilities to explore with this

i spent the afternoon experimenting with Gemma 4's vision capabilities made an app that uses roboflow RF-DETR for a first pass of object detections and Gemma to summarize the scene in one sentence for fun i asked Gemma to "describe what you see as if you were a medieval bard" all made with free local AI models (running via webgpu in the browser thanks to transformers js) lots more possibilities to explore with this

AA

700,459 views • 3 months ago

This afternoon I picked up a new Nvidia DGX Spark computer with the goal of trying to run Gemma 4 31b (4bit) on it locally as a server. Just 1.5 hours later, it’s working! Using Open WebUI on my MacBook as the interface and it’s connecting to my DGX Spark running as a Gemma 4 server.

This afternoon I picked up a new Nvidia DGX Spark computer with the goal of trying to run Gemma 4 31b (4bit) on it locally as a server. Just 1.5 hours later, it’s working! Using Open WebUI on my MacBook as the interface and it’s connecting to my DGX Spark running as a Gemma 4 server.

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138,489 views • 3 months ago

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Sharbel

20,300 views • 2 months ago

You can run Google new Gemma 4 on mobile easily. I am using Gemma 4 version E2B on my Pixel 10 Pro. Here is all you need to do: - Go to the App Store and install Google AI Edge Gallery. If you already have it, just update it. - From there, you can install the model directly and start using it. Still exploring what this small but powerful model can do :)

You can run Google new Gemma 4 on mobile easily. I am using Gemma 4 version E2B on my Pixel 10 Pro. Here is all you need to do: - Go to the App Store and install Google AI Edge Gallery. If you already have it, just update it. - From there, you can install the model directly and start using it. Still exploring what this small but powerful model can do :)

AshutoshShrivastava

226,336 views • 3 months ago

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Hermes Agent Full Setup Guide (Does It Actually Beat OpenClaw?): 0:00 - What is Hermes Agent 1:07 - What Makes It Different? 1:49 - Install Hermes 6:11 - The Mistake I Made 7:02 - Anthropic OAuth 8:45 - Live Demo 10:34 - Honest Verdict vs OpenClaw 12:26 - Best Workflow

Sharbel

64,736 views • 3 months ago

How to earn $KURO in Kuroro Wilds Kuroro is a monster catching RPG with action rpg features. A must play game on Ronin. Timestamps 0:01 What is Kuroro? 0:58 Free to play - Join 1:24 Menu Overview 1:50 Earning tickets in quest 3:00 Earning $KURO Gacha 4:00 Unlocking Ancient Forest content 4:44 Completing Mission 1 Walkthrough

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cagy.ron | youtube/cagyjan

61,507 views • 1 year ago

21’: 🇹🇿 0-1 🇳🇬 22’: 🇹🇿 1-1 🇳🇬 30’: 🇹🇿 1-2 🇳🇬 37’: 🇹🇿 1-3 🇳🇬 52’: 🇹🇿 2-3 🇳🇬 58’: 🇹🇿 3-3 🇳🇬 60’: 🇹🇿 4-3 🇳🇬 72’: 🇹🇿 4-4 🇳🇬 79’: 🇹🇿 4-5 🇳🇬 WHAT A #TotalEnergiesAFCONU17 OPENING GAME IN 2019! 😍

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Sharbel

370,717 views • 3 months ago

Parameter scaling just broke in front of me. I gave 90 math problems as images to 10 local vision models, 3 runs each, only consistent answers across all 3 runs counted. Two findings: > Gemma 4 was the most consistent family, 31B took the crown at 89.6%. > But Qwen 3.5 4B came 2 answers behind it. A 4B. Ranked 2nd out of 10. Vision-math isn't one skill, it's two: reading the image, then solving it. The real lesson for anyone running local: small ≠ weak. If you're building agentic workflows, finding the right model for each task matters more than reaching for the biggest one. In this test, the 4B ran far faster because of its size, scored higher, and left VRAM free for the rest of your stack. Full results: 🥇 Gemma 4 31B — 242/270 (89.6%) 🥈 Qwen 3.5 4B — 240/270 (88.9%) 🥉 Gemma 4 E4B — 222/270 (82.2%) 🥉 Qwen 3.6 27B — 222/270 (82.2%) 5. Gemma 4 26B A4B — 216/270 (80.0%) 6. Qwen 3.5 2B — 201/270 (74.4%) 7. Gemma 4 E2B — 192/270 (71.1%) 8. Qwen 3.6 35B A3B — 192/270 (71.1%) 9. Qwen 3.5 9B — 168/270 (62.2%) 10. Qwen 3.5 0.8B — 45/270 (16.7%) All GGUF + mmproj, Unsloth's Q6_K_XL quant.

Parameter scaling just broke in front of me. I gave 90 math problems as images to 10 local vision models, 3 runs each, only consistent answers across all 3 runs counted. Two findings: > Gemma 4 was the most consistent family, 31B took the crown at 89.6%. > But Qwen 3.5 4B came 2 answers behind it. A 4B. Ranked 2nd out of 10. Vision-math isn't one skill, it's two: reading the image, then solving it. The real lesson for anyone running local: small ≠ weak. If you're building agentic workflows, finding the right model for each task matters more than reaching for the biggest one. In this test, the 4B ran far faster because of its size, scored higher, and left VRAM free for the rest of your stack. Full results: 🥇 Gemma 4 31B — 242/270 (89.6%) 🥈 Qwen 3.5 4B — 240/270 (88.9%) 🥉 Gemma 4 E4B — 222/270 (82.2%) 🥉 Qwen 3.6 27B — 222/270 (82.2%) 5. Gemma 4 26B A4B — 216/270 (80.0%) 6. Qwen 3.5 2B — 201/270 (74.4%) 7. Gemma 4 E2B — 192/270 (71.1%) 8. Qwen 3.6 35B A3B — 192/270 (71.1%) 9. Qwen 3.5 9B — 168/270 (62.2%) 10. Qwen 3.5 0.8B — 45/270 (16.7%) All GGUF + mmproj, Unsloth's Q6_K_XL quant.

stevibe

22,882 views • 1 month ago