#model inference

3511 related articles

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 30, 2026·2 min

Behind the Open-Source Model Frenzy: Who Will Provide Cheap Inference Services?

Open-source LLM weights don't equal low-cost access for developers. This article analyzes the inference service gap in open-source AI and how providers like Together AI and Groq are addressing it.

Jul 30, 2026·2 min

Behind the Open-Source Model Frenzy: Who Will Provide Cheap Inference Services?

Open-source LLM weights don't mean developers can use them cheaply. This article examines the inference service gap in open-source AI and how providers like Together AI and Groq are addressing it.

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 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 24, 2026·6 min

AI Application Engineer Interview Guide: Core Topics in Model Quantization and Inference Deployment

A systematic review of must-know topics for AI Application Engineer interviews: PTQ/QAT quantization, operator fusion, inference pipelines, latency/throughput analysis, and edge deployment of detection/segmentation/BEV models.

Jul 24, 2026·6 min

AI Application Engineer Interview Guide: Core Topics on Model Quantization and Inference Deployment

A systematic guide to must-know AI application engineer interview topics: PTQ/QAT quantization, operator fusion, inference pipelines, latency/throughput analysis, and edge deployment of detection/segmentation/BEV models.

Jul 24, 2026·5 min

China Weighs Restricting Top AI Model Exports as DeepSeek Develops Its Own Inference Chip

China's Commerce Ministry weighs restricting overseas access to top open-weight AI models from Alibaba, ByteDance, and DeepSeek, while DeepSeek develops its own inference chip amid a US-China AI export standoff.

Jul 24, 2026·5 min

China Weighs Restricting Top AI Model Exports, While DeepSeek Quietly Builds Its Own Inference Chip

China's Ministry of Commerce is weighing restrictions on overseas access to top open-weight AI models from Alibaba, ByteDance, and DeepSeek. Meanwhile, DeepSeek is quietly building its own inference chip and raising ~$7B in first external funding.

Goku: A Browser-Based LLM Inference En…

Jul 20, 2026·2 min

Goku: A Browser-Based LLM Inference Engine and Model Manager Built on WebAssembly

Goku is a browser-based LLM inference engine built on WebAssembly and wllama, enabling local AI inference, model management, and offline use — no cloud API needed.

Block Low-Rank Compression: A Guide to…

Jul 19, 2026·2 min

Block Low-Rank Compression: A Guide to Accelerating Large Model Inference on Memory-Constrained GPUs

Learn how Block Low-Rank (BLR) decomposition compresses large model memory usage and accelerates GPU inference, including CUDA kernel optimization and combination with quantization and pruning.

Jul 14, 2026·2 min

Production LLM Deployment Guide: Model Selection, GPU Configuration, and Inference Engine Breakdown

A comprehensive decision framework for production LLM deployment: model selection (open-source vs. API), GPU VRAM configuration, and inference engine comparison including vLLM and TensorRT-LLM.

Jul 12, 2026·3 min

CPU-Native Language Models: Breaking Through Inference Bottlenecks with Memory Bandwidth Co-Design

SiliconLLM builds a CPU-native LLM architecture from scratch, combining selective SSM, ternary (1.58-bit) LUT MLP, and granular MoE, co-designed around the L3 cache bandwidth cliff. Ternary kernels show 4-5x speedup over fp32.

Jul 11, 2026·2 min

Lingbot World: A 14B Open-Weight World Model with Causal Architecture and Inference Acceleration

Lingbot World is an open-weight world model on Hugging Face with 14B parameters, causal autoregressive architecture, and inference speed optimizations. Explore its architecture and use cases.

Jul 8, 2026·3 min

GPT Flagship Model Integrates with Codex: A Deep Dive into 750 Tokens/sec Inference Speed

OpenAI's top flagship model integrates with Codex, hitting 750 tokens/sec on Cerebras wafer chips. We break down MoE architecture, subscription changes, and open-source advances from Hunyuan and Longcat 2.0.

Jul 6, 2026·6 min

A 284B Model Running on a MacBook: The Real Breakthrough and Barriers of Local DeepSeek Inference

Redis creator runs 284B-parameter DeepSeek model on a MacBook Pro at 26 tokens/sec using a pure C engine, asymmetric quantization, and MoE architecture.

Jun 24, 2026·2 min

DiffusionGemma: Google's Text Diffusion Model Achieves 4x Inference Speedup

Google launches DiffusionGemma, a text diffusion language model achieving 4x faster inference than Gemma 4 series. Learn how text diffusion works and its impact on AI.

Jun 17, 2026·1 min

DiffusionGemma: Google's Open-Source Diffusion Language Model with 4x Faster Inference

Google releases DiffusionGemma, an open-source diffusion language model achieving up to 4x faster inference and real-time self-correction by generating text in parallel rather than token by token.

Jun 14, 2026·2 min

Perplexity Partners with Intel: Local AI Models and Hybrid Inference Come to Laptops

Perplexity partners with Intel to bring local AI models and hybrid inference to Core Ultra Series 3 laptops. We break down the architecture, NPU capabilities, and the cloud-to-edge AI trend.

Jun 4, 2026·1 min

Chrome Hybrid Inference Officially Released: A Deep Dive into the New initializeDeviceModel Method

Google Chrome Hybrid Inference reaches GA with the new initializeDeviceModel() explicit initialization method. Learn about the architecture, API changes, and developer impact.