Image created with gemini-3.1-flash-image-preview with claude-sonnet-4-5. Image prompt: Using the provided reference image, preserve the left-anchored close-crop composition, deep blue-purple cinematic lighting, atmospheric smoke bleeding rightward, and emotional gravity, but replace the central subject with a cracked smartphone screen displaying notification badges, iridescent glitter catching in the fracture lines, misty haze dissolving into the right two-thirds with ‘mobile’ in thin lowercase white Helvetica Neue Light, maintaining the post-party melancholy aesthetic and HBO prestige drama mood.
Gemma 4 E2B on iPhone 17 Pro Max in AI Edge Gallery! Using skills to query wikipedia. 🔥 App link below. [cr: @mweinbach]
https://x.com/_philschmid/status/2041171039598543064
Insane I’m running Gemma 4 on my iPhone 16 pro max Vibe coded the app in under 1h Singularity is here
https://x.com/enjojoyy/status/2040563245925151229
Gemma 4 E4B is impressive for an on-device LLM. GPT-4ish quality, and expect hallucinations. Here is: “List five sociological theories starting with u and what they are. Then describe them in a rhyming verse” Its in real time, the last is a little bit of a stretch, but not bad!
https://x.com/emollick/status/2040851723774808310
There were some exceptionally cool demos from @ollama and omlx using MLX to run Qwen 3.5 and Gemma 4 on Apple silicon. The capabilities of local LLMs and the surrounding ecosystem have come a long way in the past couple years.
https://x.com/awnihannun/status/2042456446122803275
Gemma-4 finetuning 2B, 4B, 26B, 31B all work in Unsloth! We also fixed a few issues: 1. Grad accumulation no longer causes losses to explode 2. Index Error for 26B and 31B for inference 3. use_cache=False had gibberish for E2B, E4B 4. float16 audio -1e9 overflows on float16
https://x.com/danielhanchen/status/2041516671119327590
Introducing Gemma 4, our series of open weight (Apache 2.0 licensed) models, which are byte for byte the most capable open models in the world! Gemma 4 is build to run on your hardware: phones, laptops, and desktops. Frontier intelligence with a 26B MOE and a 31B Dense model!
https://x.com/OfficialLoganK/status/2039735606268314071
People underestimate the level of collaboration that needs to happen for a model such as Gemma 4 to land Before the launch, we worked with HF, VLLM, llama.cpp, Ollama, NVIDIA, Unsloth, Cactus, SGLang, Docker, CloudFlare, and so many others This ecosystem is amazing 🔥
https://x.com/osanseviero/status/2041154555530932578
Gemma 4 31B, quantized and evaluated. Instruction following evals are live on our NVFP4 and FP8-block model cards. Results look great. Reasoning and vision evals coming later this week. NVFP4:
https://t.co/GIc7y1Abkc FP8:
https://x.com/RedHat_AI/status/2040766645480628589
Gemma 4 is #1 on @huggingface!
https://x.com/ClementDelangue/status/2040911131108069692
Gemma 4 is a beast.
https://x.com/Yampeleg/status/2040495537598648357
Speculative decoding for Gemma 4 31B (EAGLE-3) A 2B draft model predicts tokens ahead; the 31B verifier validates them. Same output, faster inference. Early release. vLLM main branch support is in progress (PR #39450). Reasoning support coming soon.
https://x.com/RedHat_AI/status/2042660544797110649
Gemma 4 is the #1 trending model on @huggingface 🤗
https://x.com/GlennCameronjr/status/2040529333794824456
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