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Netflix: surprise we just released our new AI model VOID on @huggingface. Capabilities of Netflix's VOID Model:
– Object Removal with Environmental Awareness.
– Physical Interaction Handling.
– Open-Weight Access. [Translated from EN to English]
→ View original post on X — @huggingface, 2026-04-03 13:20 UTC
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Netflix just dropped their first public model on @huggingface 👀 [Translated from EN to English]
→ View original post on X — @huggingface, 2026-04-03 09:04 UTC
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Google just re-entered the game 🔥🔥 They want to take the crown 👑 back from Chinese open source AI. And… Gemma 4 is FINALLY Apache 2.0 aka real-open-source-licensed. From what I've seen it's going to be a pretty significant model. But give it a try yourself today: brew install llama.cpp –HEAD if you have at least 24GB of RAM or VRAM, run the (very good) 26B MOE: llama-server -hf ggml-org/gemma-4-26B-A4B-it-GGUF:Q4_K_M if you have 16GB of RAM or VRAM, run the dense E4B: llama-server -hf ggml-org/gemma-4-E4B-it-GGUF:Q8_0
→ View original post on X — @huggingface, 2026-04-03 05:41 UTC
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This guy is BEYOND CRACKED. Gemma 4 already on MLX, bro has uploaded all models with quantization. 125 models uploaded in last few hours 🤯 New mlx-vlm repo also supports turbo-quant, and rf-detr too (among other things) If you are a mac dev, you better be jumping at this. Bookmark him, turn his notifications on, sponsor his work. Prince Canuma (@Prince_Canuma) mlx-vlm v0.4.3 is here 🚀 Day-0 support: 🔥 Gemma 4 (vision, audio, MoE) by @GoogleDeepMind 🦅 Falcon-OCR + Falcon Perception by @TIIuae 🪨 Granite Vision 4.0 by @IBMResearch New models: 🎯 SAM 3.1 with Object Multiplex by @facebook 🔍 RF-DETR detection & segmentation by @roboflow Infra: ⚡ TurboQuant (KV cache compression) 🖥️ CUDA support for vision models (Sam and RF-DETR) Get started today: > uv pip install -U mlx-vlm Leave us a star ⭐️ github.com/Blaizzy/mlx-vlm — https://nitter.net/Prince_Canuma/status/2039815307821199709#m
→ View original post on X — @huggingface, 2026-04-02 21:44 UTC
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Pro tip – hook your PC and Phone with Tailscale and enjoy fast and private inference on the go.
— Georgi Gerganov (@ggerganov) 2 avril 2026
Here is Gemma 4, hosted on Mac Studio, streaming to my iPhone.
No 3rd party apps. Same WebUI experience everywhere. pic.twitter.com/tkfaFDvzvb
Pro tip – hook your PC and Phone with Tailscale and enjoy fast and private inference on the go. Here is Gemma 4, hosted on Mac Studio, streaming to my iPhone. No 3rd party apps. Same WebUI experience everywhere.
→ View original post on X — @huggingface, 2026-04-02 20:38 UTC
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.@GoogleGemma 4 31B is up to 2.7X faster on RTX using llama.cpp. Thanks to @ggerganov for working with us to make this model fast.
→ View original post on X — @huggingface, 2026-04-02 19:30 UTC
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NVIDIA just released a quantized Gemma 4 31B on Hugging Face NVFP4 compression delivers 4x smaller weights with frontier-level accuracy. Runs on consumer GPUs with a 256K context window.
→ View original post on X — @huggingface, 2026-04-02 17:17 UTC
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Model weights are here: https://t.co/rQlfP51Db7! https://t.co/eHxkmXfwMt
— Hugging Face (@huggingface) 27 mars 2026
Model weights are here: https://
huggingface.co/chromadb/conte
xt-1
…!
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Seeing the worldwide demand we are kicking off global applications for Hugging Face Builders! If you're passionate about open AI and love bringing people together, this is your invitation to lead Learn more about the program and apply to become a Builder
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We are sponsoring Gemini hackathon with Cerebral Valley, see you this weekend! https://t.co/jt1tMVYhBb
— Hugging Face (@huggingface) 12 mars 2026
We are sponsoring Gemini hackathon with Cerebral Valley, see you this weekend!