Google releases Gemma 4 with Apache 2.0 license, enabling unrestricted local AI on devices
19 Sources
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Google announces Gemma 4 open AI models, switches to Apache 2.0 license
Google's Gemini AI models have improved by leaps and bounds over the past year, but you can only use Gemini on Google's terms. The company's Gemma open-weight models have provided more freedom, but Gemma 3, which launched over a year ago, is getting a bit long in the tooth. Starting today,
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Google's Gemma 4 model goes fully open-source and unlocks powerful local AI - even on phones
From servers to smartphones, deployment just got much easier. Google announced today that its DeepMind AI research division is releasing Gemma 4, its latest generation of open large language models. The models are being released under the Apache 2.0 license, making them truly open source compared
[3]
Google battles Chinese open weights models with Gemma 4
Now with a more permissive license, multi-modality, and support for more than 140 languages Google on Thursday unleashed a wave of new open-weights Gemma models optimized for agentic AI and coding, under a more permissive Apache 2.0 license aimed at winning over enterprises. The launch comes
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Google's Gemma 4 AI can run on smartphones, no Internet required
Serving tech enthusiasts for over 25 years. TechSpot means tech analysis and advice you can trust. In a nutshell: Google has released the Gemma 4 open-weight AI model, designed to run locally on smartphones and other consumer devices. Built on Gemini 3, Gemma 4 comes in four versions optimized
[5]
Google has launched Gemma 4
Built from the same research as Gemini 3, the new family spans a 2B edge model that runs on a Raspberry Pi to a 31B dense model currently ranked third on the Arena AI open-model leaderboard. The Apache 2.0 licence is a significant shift from previous Gemma releases. Google has released Gemma 4,
[6]
Google launches open-source model Gemma 4: How to try it
Google just released the latest version of its open AI model, Gemma 4, on Thursday. Crucially, Gemma 4 is a fully open-source model licensed under Apache 2.0, which is typically not the case with frontier models. Open models can be run locally on users' devices, and Google says Gemma 4 can be run
[7]
Google releases Gemma 4 under Apache 2.0 -- and that license change may matter more than benchmarks
For the past two years, enterprises evaluating open-weight models have faced an awkward trade-off. Google's Gemma line consistently delivered strong performance, but its custom license -- with usage restrictions and terms Google could update at will -- pushed many teams toward Mistral or Alibaba's
[8]
Google Jumps Back Into the Open Source AI Race With Gemma 4 - Decrypt
U.S. open-source AI gets a needed boost, as Gemma 4 -- backed by DeepMind -- positions itself as the strongest American contender against DeepSeek, Qwen, and other Chinese leaders. Google's open AI ambitions got a lot more serious today. The company released Gemma 4, a family of four open-weight
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Gemma 4: Byte for byte, the most capable open models
We are releasing Gemma 4 in four versatile sizes: Effective 2B (E2B), Effective 4B (E4B), 26B Mixture of Experts (MoE) and 31B Dense. The entire family moves beyond simple chat to handle complex logic and agentic workflows. Our larger models deliver state-of-the-art performance for their sizes,
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Google's new Gemma 4 models bring complex reasoning skills to low-power devices - SiliconANGLE
Google's new Gemma 4 models bring complex reasoning skills to low-power devices Google LLC is upping the stakes for open-weights artificial intelligence models with the release of Gemma 4, its most advanced "open" model family so far. Built on the same architectural foundation as Gemini 3, the
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Google releases open-source AI model Gemma 4 for developers
Google released Gemma 4, a new open-source AI model, licensed under Apache 2.0, allowing developers to run it locally on numerous devices, including billions of Android devices and select laptop GPUs. This release marks a significant development in the availability of open AI models, offering
[12]
Google's New Open-Source Model Will Let Users Build AI Agents
The open-source model is capable of multi-step planning and deep logic Google, on Thursday, introduced Gemma 4 artificial intelligence (AI) model. The first in the Gemma 4 family comes with several improvements over its predecessors. While Gemma 3 focused on text and visual reasoning capabilities,
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Google rolls out Gemma 4: How different is it from Gemini? Key difference of AI model explained
Google's new Gemma 4 AI models are set to revolutionize tech by running advanced capabilities directly on devices like laptops and smartphones. This 'open' AI, built on Gemini's research, promises faster, more private AI experiences, enabling offline features and multi-tasking without heavy
[14]
Why Google's New Gemma 4 Uses 2.5X Fewer Tokens Than Competitors
Google's Gemma 4 series introduces a new benchmark in open source AI, combining advanced reasoning capabilities with practical efficiency. Released under the Apache 2.0 license, it offers four distinct models tailored to diverse needs, from the ultra-efficient 2B model for edge devices to the dense
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Google's Gemma 4 Model Can Now Be Deployed on NVIDIA's RTX GPUs, Delivering Optimized Performance for a 'Personalized' Agentic AI Environment
Google's newest open-source model, the Gemma 4, can now be deployed on NVIDIA's consumer-grade hardware, offering optimal performance for agentic AI workloads. [Press Release]: Open models are driving a new wave of on-device AI, extending innovation beyond the cloud to everyday devices. As these
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Google unveils Gemma 4, expands lightweight open model lineup for developers - The Economic Times
Google has introduced a new generation of its open AI models under the Gemma family, with the launch of Gemma 4. The development was confirmed by Google Deepmind chief executive Demis Hassabis in a post on X on Thursday. Google described Gemma 4 as its "most capable open model" to date. The
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Google Just Released Gemma 4: Why This Open-Source AI is a Game Changer
Google's release of Gemma 4 introduces a new era in AI development, combining advanced capabilities with open source accessibility. As highlighted by Sam Witteveen, this family of models is designed to address a diverse range of needs, from high-performance computing tasks to lightweight, on-device
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Meet Gemma 4: Google's New AI Model Built for Both Heavy Systems and Everyday Devices
Google Introduces Gemma 4: A New AI Model Family Designed to Power Both Data Centres and Smartphones! Google has introduced Gemma 4 on April 3, 2026. The latest AI model is designed to run on both powerful data centres and everyday smartphones. , the goal is to make advanced AI tools more
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Google launches Gemma 4 AI models: Features, capabilities and how to use
Gemma 4 comes in four different sizes: Effective 2B (E2B), Effective 4B (E4B), 26B Mixture of Experts (MoE) and 31B Dense. Google has announced Gemma 4, its newest family of open AI models. According to the tech giant, Gemma 4 models are its 'most intelligent open models to date' and provide an
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Google has launched Gemma 4, its latest generation of open-weight AI models, marking a significant shift to the Apache 2.0 license from its previous restrictive terms. The release includes four model variants optimized for everything from smartphones to enterprise servers, with the 31B model ranking third on the Arena AI leaderboard. This licensing change removes commercial deployment barriers and positions Gemma 4 as a domestic alternative to Chinese open-weight models.
Google Shifts Strategy with Fully Permissive Licensing
Google has released Gemma 4, its latest generation of open-weight AI models, under the Apache 2.0 license—a dramatic departure from the restrictive custom license that governed predecessor Gemma 3
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. This licensing shift grants developers and enterprises near-total freedom to use, modify, and redistribute the models for any purpose without royalty requirements, addressing long-standing frustrations with AI licensing restrictions2
. The move enables enterprise and commercial use without fear of Google terminating access, making Gemma 4 a viable option for organizations with strict data privacy and sovereignty requirements3
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Source: Ars Technica
Developed by Google DeepMind using the same research and technology that powers Gemini 3, Gemma 4 arrives as Chinese competitors like Moonshot AI, Alibaba, and Z.AI flood the market with open-weight models rivaling OpenAI's GPT-5
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. Google positions Gemma 4 as a domestic alternative that won't harvest sensitive corporate data to train future models, a critical consideration for healthcare providers and enterprises bound by regulatory restrictions.Four Models Optimized for Different Deployment Scenarios
Gemma 4 comprises four distinct variants designed to address use cases ranging from edge devices to high-performance servers. The 31B Dense model focuses on maximizing output quality and currently ranks third on the Arena AI open-model leaderboard, behind only GLM-5 and Kimi 2.5
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. Despite its capabilities, the 31B model is a fraction of the size of competing models, making local AI deployment significantly more cost-effective. This model can run unquantized in bfloat16 format on a single 80GB Nvidia H100 GPU, and when quantized to 4-bit precision, it fits on consumer graphics cards like the Nvidia RTX 40903
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Source: Wccftech
The 26B Mixture-of-Experts model prioritizes low latency over raw quality, activating only 3.8 billion of its 26 billion model parameters during inference to deliver higher tokens-per-second performance
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. This architecture proves particularly valuable for applications requiring faster responses, such as coding assistants and agentic workflows, though the reduced active parameters do impact output quality compared to dense models3
. Both larger models feature a 256,000-token context window, making them appropriate for complex code generation tasks3
.AI on Smartphones Without Internet Connectivity
The Effective 2B and Effective 4B models target mobile devices and edge devices like Raspberry Pi and Jetson Nano, developed through collaboration with the Pixel team, Qualcomm, and MediaTek
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. These models use per-layer embeddings to reduce their effective size to 2.3 billion and 4.5 billion parameters respectively, despite having actual parameter counts of 5.1 billion and 8 billion3
. This innovation enables on-device AI that runs entirely offline, using minimal memory during inference and consuming up to 60% less battery than previous versions5
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Source: Mashable
Google touts near-zero latency for these edge models, with the E2B running three times faster than the E4B
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. Both support multi-modality, natively processing video, images, and audio inputs for speech recognition, with a 128,000-token context window3
. These models will also serve as the foundation for Gemini Nano 4, Google's next-generation on-device model for Android devices launching later this year5
.Related Stories
Improved Reasoning and Enterprise-Ready Features
All Gemma 4 variants incorporate improved reasoning capabilities for mathematics and instruction-following, support for more than 140 languages, and native function calling for structured JSON output
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. These enhancements position the models for agentic AI workflows where autonomous decision-making is required. Google claims significant performance improvements across AI benchmarks compared to Gemma 3, though the company advises taking vendor-supplied benchmarks with appropriate skepticism3
.Since the first Gemma release in February 2024, developers have downloaded the models over 400 million times, creating a vibrant ecosystem of more than 100,000 community variants
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. The shift to a permissive license is expected to accelerate adoption rates further, particularly among enterprises that can now legitimately bundle the AI with products, services, and devices2
.Availability and Deployment Options
Gemma 4 is immediately available through Hugging Face, Kaggle, and Ollama, with the larger models accessible via Google AI Studio and edge models through AI Edge Gallery
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. Google claims day-one support for more than a dozen inference frameworks including vLLM, SGLang, Llama.cpp, and MLX3
. Hugging Face co-founder Clément Delangue described the Apache 2.0 licensing decision as "a huge milestone," while Google DeepMind CEO Demis Hassabis called the new models "the best open models in the world for their respective sizes"5
.While Gemma 4 carries the Apache 2.0 license, it remains "open-weight" rather than fully open-source, as Google has not released the complete training dataset, scripts, infrastructure code, or detailed methodologies required for full reproducibility
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. For most developers, this distinction matters little, as the license still permits all forms of commercial use, modification, redistribution, and deployment with only attribution required4
.References
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