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Gemma 4 imbibes Google’s sharpest AI instincts, and is more welcoming

Posted By: Hemant Kumar Posted On: Apr 03, 2026Share Article
Gemma 4 imbibes Google’s sharpest AI instincts
The convenience and flexibility extend across personal, commercial, and enterprise usage (Official image)

Gemma 4 imbibes Google’s sharpest AI instincts, and is more welcoming

Gemma 4 imbibes Google’s sharpest AI instincts, and is more welcoming

Google’s Gemma 4 open models make a strong case for an open AI that can run locally, with an eye on competition from China

Published on: Apr 03, 2026 9:13 AM IST By Vishal Mathur Share via Copy link Even as Google releases the Gemma 4, its open large language models, there is a short historical significance to it. These models find the same technological and research foundations as the Gemini 3 Pro models, released late last year, and marked a big step forward for proprietary large language models. Gemma 4 brings those improvements for open models, with a focus on advanced reasoning and agentic workflows. It is natively trained on over 140 languages. The convenience and flexibility extend across personal, commercial, and enterprise usage (Official image) Gemma 4, with four being the generation reference in the name, is available in four model sizes as well. There’s the Effective 2B (E2B), Effective 4B (E4B), 26B Mixture of Experts (MoE), and 31B Dense. The 26B and 31B models are geared for frontier intelligence, with offline compute on personal systems. The smaller parameter size E2B and E4B models are more geared for smartphones, mobile devices, and internet of things (IoT) ecosystems, as well as edge devices, including the Raspberry Pi, and Nvidia’s Jetson. In case you are wondering how Gemma is different from Gemini, the key difference is that Gemma is an AI processing engine, and not a chatbot-esque implementation. While the underlying technology is largely similar, Gemma is an open model that can be downloaded and run locally for free. It also brings much more flexibility to modify, fine-tune, and customise, depending on specific workflows and computing needs. The fact that these models can be run locally and not on the cloud also has the benefits of data privacy and cost, for many applications. The convenience and flexibility extend across personal, commercial, and enterprise usage. Google has worked closely with partners, including Qualcomm, MediaTek, and Nvidia, for these models. The new models are released under the Apache 2.0 licence, which means offering significant freedom for developers, researchers, and commercial entities to use, modify, fine-tune, and redistribute the models with minimal restrictions. Previously, that flexibility was comparatively limited. “Purpose-built for advanced reasoning and agentic workflows, Gemma 4 delivers an unprecedented level of intelligence-per-parameter. This breakthrough builds on incredible community momentum: since the launch of our first generation, developers have downloaded Gemma over 400 million times, building a vibrant Gemmaverse of more than 100,000 variants,” says Clement Farabet, Vice President of Research at Google DeepMind. Arena AI, a public, web-based platform that evaluates large language models (LLMs), ranks Gemma 4’s 31 billion parameter model at number three (score of 1452), behind GLM-5 (1456 score) and Kimi K2.5 Thinking 1453 score), while the 26 billion parameter model ranks sixth (1441 score). GLM-5 is made by the Chinese AI company Z.ai, while the Kimi models are developed by the Chinese company Moonshot AI. OpenAI’s gpt-oss-20b open-weight language model, released in August, scores 1318. Farabet notes that Gemma 4 outcompetes models 20x its size. Gemma 4 is expected to solve a wide variety of generative AI tasks with text, audio, and image input, support for over 140 languages, and a long 128K and up to 256K context window. The 31B and 26B parameter models are designed for higher-end servers with powerful GPUs, including Nvidia’s H100. “The 26B and 31B models are designed for high-performance reasoning and developer-centric workflows, making them well-suited for agentic AI. Optimized to deliver state-of-the-art, accessible reasoning, these models run efficiently on NVIDIA RTX GPUs and DGX Spark — powering development environments, coding assistants, and agent-driven workflows,” notes Michael Fukuyama, Product Manager at Nvidia. The 2 billion and 4 billion parameter footprint of the E2B and E4B models will be crucial for Gemma 4’s utility on mobile devices, with optimisations to preserve RAM and battery life. Nvidia confirms that the Jetson Orin Nano supports the Gemma 4 e2b and e4b variants, enabling multimodal inference on small, embedded, and power-constrained systems, with the same model family scaling across the Jetson platform up to Jetson Thor. ABOUT THE AUTHOR Vishal Mathur Vishal Mathur is Technology Editor for Hindustan Times. When not making sense of technology, he often searches for an elusive analog space in a digital world. Stay updated with the latest Business News on Petrol Price, Gold Rate, Silver Rates, Diesel Prices along with Income Tax Calculator Home / Business / Gemma 4 Imbibes Google’s Sharpest AI Instincts, And Is More Welcoming See Less

Even as Google releases the Gemma 4, its open large language models, there is a short historical significance to it. These models find the same technological and research foundations as the Gemini 3 Pro models, released late last year, and marked a big step forward for proprietary large language models. Gemma 4 brings those improvements for open models, with a focus on advanced reasoning and agentic workflows. It is natively trained on over 140 languages.

Gemma 4, with four being the generation reference in the name, is available in four model sizes as well. There’s the Effective 2B (E2B), Effective 4B (E4B), 26B Mixture of Experts (MoE), and 31B Dense. The 26B and 31B models are geared for frontier intelligence, with offline compute on personal systems. The smaller parameter size E2B and E4B models are more geared for smartphones, mobile devices, and internet of things (IoT) ecosystems, as well as edge devices, including the Raspberry Pi, and Nvidia’s Jetson.

In case you are wondering how Gemma is different from Gemini, the key difference is that Gemma is an AI processing engine, and not a chatbot-esque implementation. While the underlying technology is largely similar, Gemma is an open model that can be downloaded and run locally for free. It also brings much more flexibility to modify, fine-tune, and customise, depending on specific workflows and computing needs. The fact that these models can be run locally and not on the cloud also has the benefits of data privacy and cost, for many applications.

The convenience and flexibility extend across personal, commercial, and enterprise usage.

Google has worked closely with partners, including Qualcomm, MediaTek, and Nvidia, for these models. The new models are released under the Apache 2.0 licence, which means offering significant freedom for developers, researchers, and commercial entities to use, modify, fine-tune, and redistribute the models with minimal restrictions. Previously, that flexibility was comparatively limited.

“Purpose-built for advanced reasoning and agentic workflows, Gemma 4 delivers an unprecedented level of intelligence-per-parameter. This breakthrough builds on incredible community momentum: since the launch of our first generation, developers have downloaded Gemma over 400 million times, building a vibrant Gemmaverse of more than 100,000 variants,” says Clement Farabet, Vice President of Research at Google DeepMind.

Arena AI, a public, web-based platform that evaluates large language models (LLMs), ranks Gemma 4’s 31 billion parameter model at number three (score of 1452), behind GLM-5 (1456 score) and Kimi K2.5 Thinking 1453 score), while the 26 billion parameter model ranks sixth (1441 score). GLM-5 is made by the Chinese AI company Z.ai, while the Kimi models are developed by the Chinese company Moonshot AI. OpenAI’s gpt-oss-20b open-weight language model, released in August, scores 1318.

Farabet notes that Gemma 4 outcompetes models 20x its size. Gemma 4 is expected to solve a wide variety of generative AI tasks with text, audio, and image input, support for over 140 languages, and a long 128K and up to 256K context window. The 31B and 26B parameter models are designed for higher-end servers with powerful GPUs, including Nvidia’s H100.

“The 26B and 31B models are designed for high-performance reasoning and developer-centric workflows, making them well-suited for agentic AI. Optimized to deliver state-of-the-art, accessible reasoning, these models run efficiently on NVIDIA RTX GPUs and DGX Spark — powering development environments, coding assistants, and agent-driven workflows,” notes Michael Fukuyama, Product Manager at Nvidia.

The 2 billion and 4 billion parameter footprint of the E2B and E4B models will be crucial for Gemma 4’s utility on mobile devices, with optimisations to preserve RAM and battery life. Nvidia confirms that the Jetson Orin Nano supports the Gemma 4 e2b and e4b variants, enabling multimodal inference on small, embedded, and power-constrained systems, with the same model family scaling across the Jetson platform up to Jetson Thor.

Source: HindustanTimes
Related Posts: Gemma 4,Google,AI,large language models,AI processing engine,advanced reasoning

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<strong>Kriti Sanon Rakshabandhan ad</strong>: Kriti Sanon is facing massive backlash online after appearing in a Raksha Bandhan jewellery
Entertainment

Kriti Sanon Rakshabandhan ad : Kriti Sanon is facing massive backlash online after appearing in a Raksha Bandhan jewellery advertisement wearing a fusion outfit featuring a bralette-style blouse, a cape and a draped skirt. While some users called the look inappropriate for a festive campaign

Drone deliveries are getting a full lift off and for Amazon Prime members the option to get their orders shipped faster is coming to more cities in the US
Technology

Drone deliveries are getting a full lift off and for Amazon Prime members the option to get their orders shipped faster is coming to more cities in the US. The company has confirmed that Prime Air deliveries will reach around 500 cities by the end of 2026

For Delhi-NCR residents, Guleria struck a reassuring note while explaining why this year’s wave has felt worse, but citizens need not panic The H1N1 virus
Latest News

For Delhi-NCR residents, Guleria struck a reassuring note while explaining why this year’s wave has felt worse, but citizens need not panic The H1N1 virus driving Delhi-NCR’s current flu surge appears to be changing its structure — a process that is making it spread faster and slip past the

Onam gifting is often about more than simply handing over a box of sweets. The festival brings families and friends together, and a well-chosen hamper can
Life Style

Onam gifting is often about more than simply handing over a box of sweets. The festival brings families and friends together, and a well-chosen hamper can combine traditional flavours with attractive packaging to make the occasion more special

A job applicant’s unusual rejection from a software engineering internship has left the internet divided after the candidate was reportedly turned down over
Latest News

A job applicant’s unusual rejection from a software engineering internship has left the internet divided after the candidate was reportedly turned down over the name of their resume file. The incident was highlighted in a now-viral post on X by user @adnaannasir_

I have passed Class 12 (PCMB) with a state rank of 10 and have taken NEET 2026 and KCET. I want to pursue B.Sc. Chemistry but people say I should not do so
Education

I have passed Class 12 (PCMB) with a state rank of 10 and have taken NEET 2026 and KCET. I want to pursue B.Sc. Chemistry but people say I should not do so because I have such good marks. I am also considering BDS or a B.Sc. Paramedical course