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Lao Guo's Learning Space
Lao Guo's Learning Space
May 7, 2026 · Artificial Intelligence

Gemma 4 MTP Deep Dive: Speculative Decoding & KV‑Cache Sharing for 3× Faster Inference

The article explains why large‑language‑model inference is bottlenecked by memory‑bandwidth, then details Google’s Gemma 4 MTP technique—using a small draft model with speculative decoding and shared KV‑Cache—to parallelize token prediction, achieving up to three‑fold speed gains without any loss in output quality, and provides step‑by‑step local deployment instructions.

Gemma 4Inference OptimizationKV Cache
0 likes · 11 min read
Gemma 4 MTP Deep Dive: Speculative Decoding & KV‑Cache Sharing for 3× Faster Inference
Old Zhang's AI Learning
Old Zhang's AI Learning
May 6, 2026 · Artificial Intelligence

Google Boosts Gemma 4 Inference Speed Up to 3× with MTP Drafter and Day‑0 vLLM Support

Google’s new Multi‑Token Prediction (MTP) drafter for Gemma 4 delivers up to three‑fold inference speedups across hardware and frameworks—validated by official benchmarks and independent DGX Spark tests—while preserving identical output quality, and is immediately usable via Hugging Face, vLLM, MLX, Ollama and edge‑device runtimes.

Apple SiliconGemma 4LLM inference
0 likes · 9 min read
Google Boosts Gemma 4 Inference Speed Up to 3× with MTP Drafter and Day‑0 vLLM Support
DevOps Coach
DevOps Coach
Apr 23, 2026 · Artificial Intelligence

Can Gemma 4 on a MacBook Pro or NVIDIA Blackwell Replace Cloud LLMs? A Hands‑On Performance Study

The author benchmarks Gemma 4 locally on a 24 GB M4 Pro MacBook Pro (llama.cpp) and on a Dell GB10 with an NVIDIA Blackwell GPU (Ollama), comparing token speed, tool‑call reliability, and task completion against cloud GPT‑5.4, showing the Mac runs faster per token but the Blackwell system achieves higher first‑pass success with fewer retries, and that the jump from Gemma 3 to Gemma 4 dramatically improves agentic coding viability.

Agentic CodingGemma 4MacBook Pro
0 likes · 15 min read
Can Gemma 4 on a MacBook Pro or NVIDIA Blackwell Replace Cloud LLMs? A Hands‑On Performance Study
HyperAI Super Neural
HyperAI Super Neural
Apr 16, 2026 · Artificial Intelligence

Open-Source Small LLMs Reach GPT‑5‑Level Intelligence: One‑Stop Evaluation of Qwen 3.5, Gemma 4 and Other Top Models

A recent Artificial Analysis report finds that the 27‑billion‑parameter Qwen 3.5 and 31‑billion‑parameter Gemma 4 models achieve Intelligence Index scores comparable to GPT‑5, and the article details their benchmark results, multimodal capabilities, deployment on a single NVIDIA H100, and provides one‑click notebook tutorials for several open‑source LLMs.

DeploymentGemma 4Intelligence Index
0 likes · 8 min read
Open-Source Small LLMs Reach GPT‑5‑Level Intelligence: One‑Stop Evaluation of Qwen 3.5, Gemma 4 and Other Top Models
Lao Guo's Learning Space
Lao Guo's Learning Space
Apr 12, 2026 · Industry Insights

How 1/10 Pricing Drives Chinese LLMs to 10× Market Share

The article analyzes how Chinese large language models like GLM‑5.1, Qianwen 3.6‑Plus and Gemma 4 achieve roughly one‑tenth the cost of GPT‑5.4, leading to dramatically higher profit margins, silent migration in Silicon Valley, and a rapid rise in market share backed by a maturing ecosystem.

AI model ecosystemChinese LLMGLM-5.1
0 likes · 10 min read
How 1/10 Pricing Drives Chinese LLMs to 10× Market Share
AI Explorer
AI Explorer
Apr 10, 2026 · Artificial Intelligence

Google AI Edge Gallery: Offline Mobile AI Model Playground

Google’s open‑source AI Edge Gallery lets Android and iOS devices run large language models such as Gemma 4 entirely offline, eliminating network latency and privacy concerns; the app showcases six modular AI features, offers a simple install path, and signals Google’s push toward a standardized edge‑AI ecosystem.

Edge AIGemma 4Google AI Edge Gallery
0 likes · 8 min read
Google AI Edge Gallery: Offline Mobile AI Model Playground
Machine Heart
Machine Heart
Apr 10, 2026 · Artificial Intelligence

Run Gemma 4 with OpenClaw in Three Simple Steps – Official Google Guide

This article walks through Google’s official three‑step tutorial for connecting the Gemma 4 language model to OpenClaw using Ollama, details hardware requirements, discusses performance and security considerations, and evaluates the model’s capabilities compared to larger LLMs.

Gemma 4Mac StudioOllama
0 likes · 5 min read
Run Gemma 4 with OpenClaw in Three Simple Steps – Official Google Guide
Machine Learning Algorithms & Natural Language Processing
Machine Learning Algorithms & Natural Language Processing
Apr 8, 2026 · Artificial Intelligence

Dissecting Gemma‑4’s Architecture and Training Choices: A Technical Comparison with Qwen‑3 and GLM‑5

This article breaks down every architectural and training decision behind Gemma‑4—KV sharing, p‑RoPE, per‑layer embeddings, and a dual‑path MoE + dense MLP—while contrasting its efficiency and performance with Qwen‑3 and GLM‑5 across benchmarks, quantization strategies, and RL pipelines.

GLM-5Gemma 4LLM architecture
0 likes · 23 min read
Dissecting Gemma‑4’s Architecture and Training Choices: A Technical Comparison with Qwen‑3 and GLM‑5
Old Zhang's AI Learning
Old Zhang's AI Learning
Apr 7, 2026 · Artificial Intelligence

vLLM 0.19.0: HuggingFace v5 Support, Multimodal Boosts, and CPU KV Cache Offload

The vLLM 0.19.0 release adds first‑day Gemma 4 support, merges zero‑bubble asynchronous scheduling with speculative decoding, matures Model Runner V2, introduces full‑CUDA‑graph acceleration for ViT, generalizes DBO, brings CPU KV cache offload, and expands hardware and Transformers compatibility, offering substantial performance and flexibility gains for production LLM inference.

CPU KV offloadGPUGemma 4
0 likes · 18 min read
vLLM 0.19.0: HuggingFace v5 Support, Multimodal Boosts, and CPU KV Cache Offload
Coder Circle
Coder Circle
Apr 7, 2026 · Industry Insights

AI Industry Highlights: OpenAI Shake‑up, China’s Model Surge, Gemma 4 Open‑Source, and Cursor 3

The April 7 AI briefing covers OpenAI’s leadership turnover and bold economic reform proposals, China’s AI model usage overtaking the United States, Google’s Gemma 4 achieving 85% of larger models’ scores with a 256K context, Cursor 3 ushering in an agent‑based coding era, and a joint effort by OpenAI, Anthropic and Google to combat model distillation.

AI policyChina AI modelsCursor 3
0 likes · 9 min read
AI Industry Highlights: OpenAI Shake‑up, China’s Model Surge, Gemma 4 Open‑Source, and Cursor 3
SuanNi
SuanNi
Apr 3, 2026 · Artificial Intelligence

How Gemma 4 Packs Cloud‑Grade AI Into Your Pocket Devices

Google’s newly released Gemma 4 series delivers a range of open‑source LLMs—from 2.3 B to 31 B parameters—optimized for edge devices through per‑layer embeddings, mixed‑expert MoE, hybrid attention, and extensive hardware support, achieving top‑tier benchmark scores while running efficiently on phones and IoT.

Edge AIGemma 4Hybrid Attention
0 likes · 10 min read
How Gemma 4 Packs Cloud‑Grade AI Into Your Pocket Devices
Machine Heart
Machine Heart
Apr 3, 2026 · Artificial Intelligence

Google Open‑Sources Gemma 4, Outperforming a 13×‑Larger Qwen 3.5

Google DeepMind released the open‑source Gemma 4 family—four model sizes ranging from 2 B to 31 B parameters, supporting text, images, video and audio, with up to 256 k token context, Apache 2.0 licensing, and benchmark results that place it on par with the 397 B Qwen 3.5 despite being far smaller.

Apache-2.0Gemma 4Google DeepMind
0 likes · 11 min read
Google Open‑Sources Gemma 4, Outperforming a 13×‑Larger Qwen 3.5