Gemma 4
Gemma 4 is an open-source large language model series released by Google, with a parameter scale of 31 billion (31B). Built on the Transformer architecture, it supports tasks including text understanding, generation, and multi-step reasoning. Model weights are made available to researchers and developers for local deployment and fine-tuning on downstream tasks. As an iteration of the Gemma series, it is designed to deliver strong general-purpose language processing capabilities while maintaining relatively low resource requirements.
Core Facts
Gemma 4's 26B MoE model uses a Mixture of Experts architecture, with 26 billion total parameters but only approximately 4 billion parameters active at any given moment.
Gemma 4 adopts the Apache 2.0 license, allowing completely unrestricted commercial use
Gemma 4的1B/2B模型量化后仅需4GB显存即可运行
Timeline (last 90 days)
With the new kernel on NVIDIA Ampere and newer GPUs, Gemma 4's global attention layers achieve 1.4 to 2.1 times faster attention and up to 4.9 times lower attention memory.
Invoice AI integrates a conversational assistant based on Gemma 4 and runs it via Ollama Cloud.
The author explicitly states they have not yet rerun all 24 test cases on the local 8B version, and therefore does not claim the local 8B performs the same as the hosted 26B.
Because it uses open-weight models, when the author's local GPU driver failed, they pointed the calls to the hosted version of the same Gemma 4 family (26B) by changing environment variables, continuing without rewriting any code.
The author tested with 12 real listings run twice each for 24 generations in total, of which 17 were ready on the first pass, 7 entered confirm, 0 failed, with an average time of 5.5 seconds and a total cost of $0.0035.
listwright by default calls the local gemma4 model via Ollama, through an abstraction layer compatible with the OpenAI chat API, and switching to a remote hosted endpoint only requires changing environment variables.
listwright is an open-source command-line tool that uses the Gemma 4 model to generate Etsy product titles, 13 tags, and three-paragraph descriptions from product photos and factual inputs.
Gemma 4 is Google's open-source model that can run locally directly in the browser.
Gemma 4 uses the Apache 2.0 license, which permits building paid products legally.
RepoBuddy's workflow has three steps: shallow-clone the repository, build a knowledge graph with Graphify, and after graph retrieval hand the question to Gemma 4 to answer.
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All Facts (20)
Gemma 4's 26B MoE model uses a Mixture of Experts architecture, with 26 billion total parameters but only approximately 4 billion parameters active at any given moment.
80%VerifiedGemma 4 adopts the Apache 2.0 license, allowing completely unrestricted commercial use
75%VerifiedGemma 4的1B/2B模型量化后仅需4GB显存即可运行
65%Unverified全部四种Gemma 4模型都支持文本和图片输入，Edge模型（E2B和E4B）还额外支持音频输入
90%UnverifiedGemma 4支持完全离线状态下的图像文字提取（OCR），采用视觉-语言多模态架构
90%UnverifiedGemma 4大模型上下文窗口可达256,000 Token
90%Unverified所有Gemma 4模型原生支持多模态（文本、图像、最多30秒音频输入），上下文窗口为128K Token，支持超过40种语言
85%UnverifiedGemma 4引入了多模态能力，Qwen3支持超长上下文，DeepSeek采用MoE（混合专家）架构
85%Unverified使用Gemma 4系列模型验证了模型权重与Harness状态的联合学习效果，发现单独的监督微调和离线强化学习预热都不能让模型取得里程碑进展，只有联合学习循环才能产生持续提升
85%UnverifiedGemma 4的1B/2B模型自带语音识别功能
80%UnverifiedGoogle在Gemma 4中实际应用了MTP技术
80%UnverifiedGemma 4使用滑动窗口注意力（SWA）架构，该架构在处理数千行混淆JavaScript时导致模型遗忘早先读入的关键上下文
80%Partially VerifiedEmbeddingGemma 2 is a multimodal embedding model built by Google on the Gemma 4 architecture, capable of encoding text, images, audio, and video into a shared 768-dimensional vector space.
75%Unverified使用Gemma 4 2B版本本地运行Codex时，处理速度大约每秒30到40个Token
75%Partially VerifiedGoogle says Gemini 4 Argon helped refactor Chrome's massive codebase, completing months of engineering in just a few weeks, and increased internal agent code submissions by more than 35%.
65%UnverifiedWith the new kernel on NVIDIA Ampere and newer GPUs, Gemma 4's global attention layers achieve 1.4 to 2.1 times faster attention and up to 4.9 times lower attention memory.
50%UnverifiedInvoice AI integrates a conversational assistant based on Gemma 4 and runs it via Ollama Cloud.
50%UnverifiedThe author tested with 12 real listings run twice each for 24 generations in total, of which 17 were ready on the first pass, 7 entered confirm, 0 failed, with an average time of 5.5 seconds and a total cost of $0.0035.
50%UnverifiedBecause it uses open-weight models, when the author's local GPU driver failed, they pointed the calls to the hosted version of the same Gemma 4 family (26B) by changing environment variables, continuing without rewriting any code.
50%Unverifiedlistwright is an open-source command-line tool that uses the Gemma 4 model to generate Etsy product titles, 13 tags, and three-paragraph descriptions from product photos and factual inputs.
50%