#GPU HBM

137 related articles

Aug 1, 2026·3 min

The Return of Private Cloud: A Rational Choice in the Era of Data Sovereignty and Compute Autonomy

After a decade of public cloud dominance, private cloud is making a comeback. From cost recalculation and data sovereignty compliance to AI compute autonomy, we analyze why enterprises are reconsidering private and hybrid cloud strategies.

Aug 1, 2026·3 min

How Cheap Can It Be to Serve a 2.8 Trillion Parameter Model? A Deep Dive into Inference Economics

Deep analysis of the real cost of serving a 2.8 trillion parameter model. From MoE sparse activation to batching scale effects and inference optimization, revealing why model size and serving cost are less correlated than assumed.

Jul 31, 2026·3 min

Practical Guide to Setting Up a Local AI Coding Environment on MacBook Pro M4

Complete guide to setting up a local AI coding environment on MacBook Pro M4, covering Ollama, MLX, Continue, Qwen3-Coder 30B configuration, and performance optimization strategies for 32GB RAM.

Jul 31, 2026·2 min

Running Kimi K3 with 29GB of RAM: The Trade-offs and Costs of Extreme Quantization

Running Kimi K3 with 29GB RAM at just 0.5 tok/s. An in-depth analysis of extreme quantization techniques, performance trade-offs, and the impossible triangle of local LLM deployment.

Jul 31, 2026·2 min

Running Kimi K3 in 29GB of RAM: The Trade-offs and Costs of Extreme Quantization

Running Kimi K3 with 29GB RAM at just 0.5 tok/s. A deep analysis of extreme quantization techniques, performance trade-offs, and the impossible triangle of local LLM deployment.

Jul 30, 2026·3 min

Is LLM Inference Really That Expensive? Breaking Down the Cost Reduction Logic of GPU Compute and Inference Frameworks

Analyzing real LLM inference costs: from B200 GPU compute gains, vLLM framework optimization to MTP multi-token prediction, explaining why serving costs are widely overestimated.

Jul 29, 2026·3 min

Is LLM Inference Actually Profitable? Breaking Down the Cost Structure and Business Logic of Large Model Inference

A deep dive into LLM inference cost structure and profitability models—from GPU throughput, MoE architecture, and KV Cache to scale effects—revealing the business logic behind API price wars.

Jul 29, 2026·3 min

Moonshot AI Open-Sources FlashKDA: A Deep Dive into High-Performance CUDA Kernels for KDA Attention

Moonshot AI open-sources FlashKDA, providing high-performance CUDA kernels for Kimi Delta Attention. Learn about its technical principles, performance gains, and value for long-context training and inference acceleration.

Jul 29, 2026·3 min

Moonshot AI Open-Sources FlashKDA: A Deep Dive into High-Performance CUDA Kernels for KDA Attention

Moonshot AI open-sources FlashKDA, providing high-performance CUDA kernels for Kimi Delta Attention. Explore its technical principles, performance gains, and value for long-context training and inference.

Jul 29, 2026·2 min

AI Bubble Fears Intensify: The Logic Behind Chip Stocks Selling Off Across U.S. and Asian Markets

Chip stocks fall simultaneously across U.S. and Asian markets as AI bubble fears intensify. Analysis of the drivers, sustainability of AI capex, and the balance between short-term volatility and long-term trends.

Jul 29, 2026·2 min

AI Bubble Fears Intensify: The Logic Behind Chip Stocks Selling Off Across US and Asian Markets

Chip stocks decline simultaneously across US and Asian markets as AI bubble fears intensify. Analysis of the logic behind the selloff, sustainability questions around AI capex, and the relationship between short-term volatility and long-term trends.

Jul 28, 2026·3 min

Kimi Delta Attention Explained: The Evolution from Standard Attention to Linear Attention

A deep dive into Kimi Delta Attention (KDA): tracing the evolution from quadratic Softmax attention through linear attention, Delta rules, and gated decay mechanisms, with insights on associative memory and hardware optimization.

Jul 28, 2026·3 min

Kimi Delta Attention Explained: The Evolution from Standard Attention to Linear Attention

Deep dive into Kimi Delta Attention (KDA): from standard Softmax attention's quadratic bottleneck through linear attention, Delta Rule, and gated decay mechanisms — the complete evolution explained.

Jul 28, 2026·3 min

Kimi K3 Launch: A 2.8 Trillion Parameter Flagship Model Makes Its Grand Entrance

Moonshot AI launches Kimi K3 with 2.8 trillion parameters and 1M token context. Google delays Gemini 3.5 Pro, AI coding tools upgrade collectively as competition shifts to coding and Agent capabilities.

Jul 28, 2026·4 min

Colibri: Running a 744-Billion-Parameter LLM on an Ordinary Laptop

Colibri uses MoE hot-cold separation and 4-bit quantization to run 744B-parameter models like GLM 5.2 on consumer hardware. Learn about its three-tier memory architecture and speculative decoding.

Jul 28, 2026·4 min

Laguna S 2.1 Deep Dive: Hands-On Local Deployment of a 118B Parameter Coding Model

In-depth review of Poolside's Laguna S 2.1 open-source coding model: MoE architecture, RL training, DGX Spark local deployment, and real-world agentic coding tests with 8B active parameters.

Jul 28, 2026·3 min

Samsung Z Fold 8 Hands-On: The Compact Foldable Is the Biggest Surprise

Samsung unveils the Z Fold 8, Z Fold 8 Ultra, and Z Flip 8. The Z Fold 8's passport-style design weighs just 201g with a dramatically improved crease, preemptively countering Apple's rumored foldable iPhone.

Jul 28, 2026·3 min

Samsung Z Fold 8 Hands-On: The Compact Foldable Is the Biggest Surprise

Samsung launches Z Fold 8, Z Fold 8 Ultra, and Z Flip 8. The Z Fold 8's passport-style design weighs just 201g with dramatically reduced crease, preemptively countering Apple's rumored foldable iPhone.

Jul 28, 2026·3 min

Apple Silicon LLM Inference Speed Benchmarks: A Complete Guide to Local Large Model Performance on Mac

In-depth analysis of Apple Silicon local LLM inference speed benchmarks covering M-series memory bandwidth, model quantization, MLX framework optimization, and Mac configuration guidance.

Jul 28, 2026·3 min

AMD CDNA5 Architecture Deep Dive: Technical Evolution and the AI Computing Competition Landscape

Deep analysis of AMD's CDNA5 architecture covering Chiplet packaging upgrades, HBM memory evolution, and low-precision compute optimization, examining how AMD challenges NVIDIA's AI chip dominance.