Blog Gemma 4 AI
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Gemma 4 26B vs 31B: MoE vs Dense — Mana yang Lebih Baik?
Perbandingan mendalam model 26B MoE dan 31B Dense Gemma 4. Penjelasan arsitektur MoE, hasil benchmark, kebutuhan VRAM, perbedaan kecepatan, dan rekomendasi use case.
How to Run Gemma 4 on AMD GPU (ROCm Setup Guide)
Step-by-step guide to running Gemma 4 on AMD GPUs with ROCm. Covers supported architectures, installation, Lemonade tool, vLLM/SGLang setup, and common troubleshooting tips.
How to Use the Gemma 4 API (Python, cURL & JavaScript)
Complete tutorial for calling the Gemma 4 API three ways: Ollama local API, Google AI Studio, and OpenRouter. Full code examples in Python, cURL, and JavaScript with streaming support.
Gemma 4 Architecture Explained: MoE, Dense, and Why It Matters
Understand how Gemma 4 works under the hood — Mixture of Experts, Dense models, attention mechanisms, and that massive 256K context window.
Gemma 4 Chinese Language Performance: Honest Review
A practical, honest review of Gemma 4's Chinese language abilities — comprehension, generation, code comments, translation, and how it compares to Qwen 3.
How to Run Gemma 4 in Docker (Complete Container Guide)
Run Gemma 4 in Docker containers — Dockerfile, docker-compose, GPU passthrough, persistent storage, and multi-model setups.
Cara Download & Instal Gemma 4 (Semua Metode)
Panduan lengkap download Gemma 4 — via Ollama, LM Studio, Hugging Face, Google AI Studio, dan Kaggle. Temukan metode terbaik untuk setup kamu.
How to Fine-Tune Gemma 4 with LoRA (Step-by-Step)
Learn how to fine-tune Gemma 4 using LoRA and QLoRA with Unsloth. From data prep to GGUF export and Ollama deployment — everything you need.
How to Build AI Agents with Gemma 4 Function Calling
Build AI agents with Gemma 4's native function calling. Covers tool definition in JSON schema, weather API and calculator examples, multi-step agent loops, Python code with Ollama API, and structured output patterns.
Gemma 4 GGUF: Which Quantization Should I Pick?
Complete guide to Gemma 4 GGUF quantization formats. Compares Q4_K_M, Q5_K_M, Q8_0, and IQ4_XS with file sizes, quality benchmarks, speed measurements, and setup instructions for llama.cpp, Ollama, and LM Studio.
Bisakah Laptop Saya Menjalankan Gemma 4? (Kebutuhan RAM & GPU)
Kebutuhan hardware lengkap untuk setiap model Gemma 4. RAM, VRAM, dan spek GPU untuk laptop, desktop, dan cloud. Ketahui persis apa yang kamu butuhkan sebelum download.
How to Download Gemma 4 from Hugging Face (Weights & GGUF)
Download Gemma 4 from Hugging Face — official weights and GGUF quantized versions. Covers git lfs, huggingface-cli, transformers library usage, text-generation-inference, and HF mirror for Chinese users.
How to Run Gemma 4 on iPhone (Yes, It Actually Works)
A practical guide to running Gemma 4 AI on your iPhone. Which models work, how to set it up with Google AI Edge Gallery, and honest performance expectations.
Gemma 4 Structured Output: How to Get Reliable JSON Every Time
Get consistent, parseable JSON from Gemma 4 — system prompt techniques, Ollama format parameter, Pydantic validation, and retry patterns.
Gemma 4 on Mac: M1, M2, M3, M4 Performance Tested
Real performance benchmarks for Gemma 4 on every Apple Silicon Mac — M1 through M4, with tokens per second, model recommendations, and optimization tips.
Cara Deploy Gemma 4 di Android & iOS (Panduan AI Mobile)
Panduan lengkap menjalankan Gemma 4 di perangkat mobile. Mencakup deployment Android dengan AI Edge SDK, AICore, dan MediaPipe, iOS dengan AI Edge Gallery dan LiteRT, pemilihan model, ekspektasi performa, dan kemampuan AI offline.
How to Analyze Images with Gemma 4 (Multimodal Guide)
Learn how to use Gemma 4's multimodal capabilities to analyze images, extract text, read charts, and more. Includes Ollama CLI commands, Python API examples, and practical use cases.
How to Run Gemma 4 on NVIDIA RTX (CUDA Setup & Optimization)
Complete guide to running Gemma 4 on NVIDIA GPUs. Covers CUDA requirements, Ollama setup, GPU offloading, RTX performance comparison, Jetson support, and TensorRT-LLM optimization.
How to Run Gemma 4 on Raspberry Pi (Yes, Really)
Run Gemma 4 E2B on a Raspberry Pi 5 with Ollama — setup guide, realistic performance expectations, use cases, and optimization tips.
Kenapa Gemma 4 Lambat? Panduan Mempercepat untuk Mac, Windows & Linux
Diagnosa dan perbaiki performa Gemma 4 yang lambat. Mencakup deteksi CPU fallback, perbandingan kecepatan kuantisasi, tuning panjang konteks, manajemen KV cache, dan optimasi spesifik platform.
Gemma 4 Thinking Mode: What It Does & When to Use It
Understand Gemma 4's thinking/reasoning mode — how to enable it, when it helps, when to skip it, and real performance comparisons with and without thinking.
Gemma 4 Bermasalah? Solusi untuk OOM, Lambat & Masalah GPU
Perbaiki masalah Gemma 4 yang paling umum — error out of memory, inferensi lambat, GPU tidak terdeteksi, masalah download, dan lainnya. Solusi nyata dari komunitas.
How to Deploy Gemma 4 in Production (vLLM + Docker)
Deploy Gemma 4 for production use with vLLM, Docker, and an OpenAI-compatible API. Covers GPU planning, batch inference, monitoring, and Vertex AI.
Gemma 4 vs ChatGPT: Bisakah AI Lokal Gratis Menggantikannya?
Perbandingan jujur Gemma 4 dan ChatGPT — biaya, privasi, kecepatan, kualitas per tugas, dan kapan menggunakan masing-masing. Plus pendekatan hybrid yang memberi yang terbaik dari keduanya.
Gemma 4 vs Gemini: Apa Bedanya?
Gemma 4 dan Gemini berasal dari tim yang sama di Google, tapi mereka produk yang sangat berbeda. Ini yang membedakan mereka dan kapan menggunakan masing-masing.
Gemma 4 vs Gemma 3: What's New and Should You Upgrade?
Detailed comparison of Gemma 4 and Gemma 3. Covers architecture changes, Apache 2.0 licensing, MoE models, audio support, 256K context, benchmark improvements, and migration guide.
Model Gemma 4 Mana yang Harus Dipakai? (E2B vs E4B vs 26B vs 31B)
Perbandingan praktis keempat model Gemma 4 — E2B, E4B, 26B MoE, dan 31B Dense. Temukan mana yang cocok untuk hardware dan kebutuhanmu.
50 Best Gemma 4 Prompts: Coding, Writing, Analysis & Multimodal (2026)
Curated collection of the most effective prompts for Gemma 4. Copy-paste ready prompts for coding, writing, data analysis, image understanding, and more.
Best Local AI Models You Can Run in 2026: Complete Ranking & Comparison
A comprehensive ranking of the best open-source AI models you can run locally in 2026. Compare Gemma 4, Llama 4, Qwen 3, Phi-4, and Mistral — with hardware requirements, installation guides, and real-world use cases.
Gemma 4 vs Llama 4: Which Open AI Model Should You Use in 2026?
Detailed comparison of Google Gemma 4 and Meta Llama 4 Maverick. Benchmarks, features, licensing, and real-world performance. Find the best open model for your project.
Gemma 4 vs Qwen 3: Detailed Comparison (2026)
In-depth comparison of Google Gemma 4 and Alibaba Qwen 3. Side-by-side analysis of parameters, benchmarks, licensing, Chinese language support, and local deployment.
10 Practical Use Cases for Gemma 4: What You Can Actually Do With It
Discover 10 real-world use cases for Gemma 4, from coding assistance to document analysis to privacy-sensitive applications. Each use case includes the recommended model size and example prompts you can try today.
How to Use Gemma 4 for Free on Google AI Studio (2026)
Try Gemma 4 online for free — no installation, no GPU required. Complete guide to using Gemma 4 on Google AI Studio with chat, API access, and free tier details.
Cara Menjalankan Gemma 4 Secara Lokal dengan Ollama: Panduan Lengkap (2026)
Panduan langkah demi langkah untuk menginstal dan menjalankan Google Gemma 4 di komputer menggunakan Ollama. Setup satu perintah, tanpa cloud. Bisa di Mac, Windows, dan Linux.
How to Run Gemma 4 with LM Studio: Beginner-Friendly Guide (2026)
Learn how to run Google Gemma 4 locally using LM Studio — a beautiful GUI app for AI models. No command line needed. Download, click, and chat.
How to Run Gemma 4 in Your Browser with WebGPU (No Server Required)
A complete guide to running Gemma 4 directly in your browser using WebGPU. No backend, no API keys, no setup — just open a tab and start chatting with a powerful AI model on your own device.