Faster than light, @UnslothAI Gemma 4
GENERATIVE AI
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Installing and Running Llama.cpp with Gemma Model
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Just do this: brew install llama.cpp –HEAD Then; llama-server -hf ggml-org/gemma-4-26B-A4B-it-GGUF:Q4_K_M
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Google Releases Gemma 4 in Four Variants
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BREAKING : Google released Gemma 4 in 4 different variants: 31B, 26B MoE, 2B and 4B! Offline on-device AI apps got a huge upgrade!
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Music Creation and Sharing App Built with Replit Canvas
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An app to make and share your music anywhere Made with Replit Canvas
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Gamma 31b Unexpectedly Outperforms Qwen 3.5 397B Model
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Gamma 31b model outperforming Qwen 3.5 397B is nuts to me.
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Google Releases Gemma 4 Open-Source Models with Impressive Performance
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Here we go: Gamma 4 released: ""Outperforms models 20x its size" Google dropped Gemma 4 under Apache 2.0, full open-source, big licensing shift. Built on Gemini 3 tech, four sizes: E2B, E4B, 26B MoE, 31B Dense. Price-performance: 31B is #3 open model on Arena AI, 26B MoE is #6
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Perplexity Computer Now Helps Prepare Federal Tax Returns
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Perplexity Computer can now help prepare your federal tax return.
— Perplexity (@perplexity_ai) 2 avril 2026
Select “Navigate my taxes” on Computer to give it a shot. pic.twitter.com/XppQTXz4JWPerplexity Computer can now help prepare your federal tax return. Select “Navigate my taxes” on Computer to give it a shot.
→ View original post on X — @aravsrinivas, 2026-04-02 16:25 UTC
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Google Gemma 4: Most Capable Open Agentic Model Released
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Introducing Google Gemma 4, our most capable open agentic model. It supports high-quality offline code generation with long context and is trained on over 140 languages. Open-source Apache 2.0 licence.
→ View original post on X — @saboo_shubham_, 2026-04-02 16:24 UTC
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Google Releases Gemma 4 Open Source LLM Locally
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So happy to see Google release Gemma 4 today in apache 2.0 that gives you frontier capabilities locally. You can use it right away in all your favorite open agent platforms like openclaw, opencode, pi, Hermes by asking it to change your model to local gemma 4 with
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Gemma4 vindicated: dense models triumph over mixture of experts
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Gemma4 is amazing. You'll read that everywhere. Let's focus on what is HUGE here: the revenge of dense models…. Throw away your b200, not needed anymore, throw away the millions of lines of code we had to write to make MOEs faster, training stable etc… throw away your router-aware kernel, your EP DEEP GEMM, throw away the auxiliary loss function. Welcome to simplicity, dense is the new king. FINALLY hating MoEs is back to being chad. For those who know me: I was always a moe doomer
→ View original post on X — @jeremyphoward, 2026-04-02 16:23 UTC