Gemma
PulseAugur coverage of Gemma — every cluster mentioning Gemma across labs, papers, and developer communities, ranked by signal.
- developed by .google 100%
- developed by GOOGL 100%
- instance of Gemma 4 90%
- developed by DiffusionGemma 90%
- instance of large-language models 90%
- instance of Gemma 4: 26b 90%
- used by Qwen 2.5 90%
- instance of Google Gemma 90%
- instance of Pythia 90%
- developed by Gemma 4 70%
- used by vLLM 70%
- used by RTX 5090 70%
28 day(s) with sentiment data
-
Local LLMs struggle with coding tasks, raising proprietary platform concerns
A user found that locally hosted large language models (LLMs) like Qwen and Gemma performed poorly for coding tasks compared to free online models. Despite trying models ranging from 0.8B to 30B parameters, both speed a…
-
DeepSeek's DSpark system boosts LLM inference speed with novel parallel-sequential approach · 1 source tracked
DeepSeek has developed a new system called DSpark that significantly accelerates large language model inference. DSpark combines parallel and sequential processing techniques to improve the efficiency of speculative dec…
-
NagaTranslate builds low-resource language pipeline using LLMs, Whisper, VITS
A project called NagaTranslate is developing a translation and speech pipeline for low-resource languages in Nagaland, India, including Nagamese, Ao, and Sema. The system utilizes a commercial LLM API for text translati…
-
Guide to running open-source AI models locally on developer hardware
This guide provides a comprehensive overview for developers looking to run open-source AI models locally on their own hardware. It covers essential vocabulary, explains the trade-offs between local and cloud AI, and off…
-
Google AI accelerates on-device LLMs with new Multi-Token Prediction method
Google AI has developed a new method to accelerate on-device Large Language Models (LLMs) like Gemini Nano and Gemma, particularly for use on Google Pixel phones. This technique, called Multi-Token Prediction (MTP), ret…
-
Google's Gemma models reach 200M downloads in 2.5 months
Google DeepMind announced that its Gemma family of models has surpassed 200 million downloads in just two and a half months. This milestone highlights significant community adoption and rapid growth, with the number of …
-
Itheereum-Cybernetics claims Google's AI models lack permission for IP use
Itheereum-Cybernetics, a company led by CEO Stanislaus Kroppach, has stated that Google, Alphabet, and their AI models (Gemini, Gemma, Veo, Lyra) do not have permission to use its intellectual property. The company asse…
-
Open-source Ornith 1.0 coding models rival Opus 4.7-4.8
A new suite of open-weight coding models, named Ornith 1.0, has been released, featuring sizes ranging from 9 billion to 397 billion parameters. The largest model in this collection is reported to be competitive with An…
-
llama.cpp adds tensor split support for Intel GPUs, fixing model issues
A recent release of llama.cpp, version b9788, introduces support for tensor splitting on Intel GPUs. This feature aims to resolve issues previously encountered when using tensor split mode, particularly with models like…
-
Offline AI kiosk uses Gemma and Qdrant Edge for semantic search
A developer has created an offline retail kiosk system called "Smart Cart" that uses AI to understand customer queries semantically rather than relying on keyword matching. The system leverages Qdrant Edge, a local vect…
-
Run Google's Gemma LLM Locally with New Open-Source App
A new open-source application called Off Grid AI Desktop allows users to run Google's Gemma language models locally on their Mac or Windows computers. This approach prioritizes user privacy by keeping all prompts and da…
-
Gemma models run locally on MacBook Air via LM Studio
A user is discussing the feasibility of running AI models like Gemma locally on a MacBook Air using LM Studio. They note that while smaller, text-processing-focused models can be sufficient for many tasks, they are not …
-
Local AI models match and beat cloud offerings in game development test
A developer tested four AI models to build a playable game, with three running locally on a MacBook Pro M5 Max and one cloud-based model serving as a benchmark. All four models successfully generated a functional game, …
-
LLM intermediate layers reveal jailbreak signals, study finds · 3 sources tracked
Researchers have identified that the internal representations of large language models, specifically in their intermediate layers, contain signals related to jailbreak attacks. By analyzing token-level predictive entrop…
-
Unsloth Studio boosts GLM-5.2 support with 3x longer context
Unsloth has released version 0.1.471-beta, introducing support for GLM-5.2 and enhancing context length capabilities. The update features an auto-fit algorithm that allows for three times longer context windows, enablin…
-
Ollama API Guide: Mastering Local LLM Endpoints for Developers
This guide details how to effectively use all 14 API endpoints provided by Ollama, a platform for running large language models locally. It covers generating text, managing chat conversations, creating embeddings for se…
-
Hugging Face uses local models for free OpenClaw repo triage
Hugging Face demonstrated how to use local, open-weight models for triaging issues and pull requests in the OpenClaw repository. This approach leverages models like Gemma and Qwen within an agent harness, offering a cos…
-
LoRA fine-tuning matches full model performance with 1% of parameters
A developer details the process of using LoRA (Low-Rank Adaptation) to fine-tune large language models efficiently. LoRA allows for training only a small fraction of a model's parameters by introducing trainable adapter…
-
Google's Gemini and Gemma LLMs improve EQ-5D study identification in PubMed
Researchers have developed a novel framework using ensembles of Google's Gemini and Gemma large language models to automate the identification of EQ-5D studies within the PubMed database. This multi-phase approach integ…
-
New Gemma-based models for coding and agents released on Hugging Face
Two distinct models, huihui-ai/Huihui-gemma-4-12B-coder-fable5-composer2.5-v1-abliterated and yuxinlu1/gemma-4-12B-agentic-fable5-composer2.5-v2-3.5x-tau2-GGUF, have been released on Hugging Face. Both models are based …