#GQA MoE LLM
11 related articles
·7 min
DeepSeek's Mysteriously Retracted Paper: Breaking AI's Multimodal Reasoning Bottleneck with Visual Primitives
DeepSeek's paper 'Thinking with Visual Primitives' was online for just 4 hours before being pulled. It uses bounding boxes and points as reasoning primitives, letting models 'point at' images to outperform GPT, Gemini, and Claude on maze navigation and counting.
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·4 min
Understanding Transformer From the Ground Up: How Language Models Predict the Next Word
From Tokenization and Embedding to the Attention mechanism, this article systematically breaks down how Transformer works — and how ChatGPT turns input text into next-token probabilities.
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Hardware-Software Co-Design: A Guide t…
·2 min
Hardware-Software Co-Design: A Guide to Building Hardware-Friendly LLM Architectures
Explore AI Model Co-Design principles and how hardware-friendly LLM architecture design — covering MoE, GQA, and FP8 quantization — optimizes the accuracy, throughput, and latency trade-off.
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·2 min
15-Year-Old Trains 200M MoE Language Model from Scratch: Full Architecture & Hands-On Breakdown
A 15-year-old trained Tiny-MoE, a 200M-parameter MoE language model from scratch using free Kaggle GPUs, featuring MLA attention, RoPE+YaRN, and native PyTorch.
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·7 min
A Java Developer's Guide to AI: Framework Selection and Practical Tutorial for LangChain4J
As LLM costs keep falling, how can Java developers seize the AI opportunity? This article explores LangChain4J's core capabilities, supported models and vector databases, and compares LangChain4J vs. Spring AI to help you build local knowledge bases and intelligent customer service systems.
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·7 min
Ollama + Hermes Local AI Deployment: Building a 100% Private Personal AI Operating System
Build a fully private local AI system with Ollama + Hermes: zero cost, no rate limits, data stays local. Learn deployment steps, model selection tips, and private/cloud hybrid workflows.
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·4 min
Kimi K2.7 Code Deep Dive: The Cost-Performance Battle of a Trillion-Parameter Coding Model
Deep dive into Moonshot AI's Kimi K2.7 Code: MoE architecture details, benchmark analysis, API pricing vs Claude/GPT, 6x speed version, and practical guidance for developers evaluating adoption.
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·3 min
LFM2.5 Local Deployment Hands-On: An 8B Parameter Model That Outperforms GPT-o3s in Tool Calling
Hands-on test of Liquid AI's LFM2.5 local deployment: architecture breakdown, 16GB VRAM troubleshooting, and GraphRAG tool-calling benchmarks vs GPT-o3s.
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·4 min
Google Hybrid Inference Comes to iOS: A Complete Guide to On-Device AI Cross-Platform Deployment
Google Hybrid Inference officially supports iOS, adds Gemma 4 on Android, and Chrome local Web inference nears GA. A deep dive into hybrid inference technology, cross-platform advantages, and developer opportunities.
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·4 min
Google Hybrid Inference Comes to iOS: A Complete Guide to On-Device AI Cross-Platform Deployment
Google Hybrid Inference now supports iOS, adds Gemma 4 on Android, and Chrome local Web inference nears GA. A deep dive into hybrid inference technology, cross-platform advantages, and developer opportunities.
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Tutorials·3 min
OpenAI Open-Sources GPT-OSS: Run O4-Level Models on 16GB VRAM — Complete Deployment Guide
OpenAI open-sources GPT-OSS (20B/120B) with MOE architecture and native FP4 precision. Run O3-level reasoning on a single RTX 4090. Full deployment guide for Ollama, vLLM, and more.
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