mac
30 articles about mac in AI news
M4 Max Mac Studio Tops GB10 in Local AI Decode Throughput
M4 Max Mac Studio beats GB10 and Strix Halo in local AI decode throughput but memory bandwidth caps large model performance. Tom's Hardware tested llama.cpp across three platforms.
Qwen 3.8 Max Generates macOS Clone in Single HTML Pass
Qwen 3.8 Max generated a full macOS clone in HTML/CSS/JS in a single pass, demonstrating unusually high UI fidelity for a code generation model.
Build a Claude Content Machine That Never Sounds Like Slop
Clone Morning Brew founder Alex Lieberman's Claude Content Machine: an Oracle, Interview Panel, and Writer's Council that produce original content using CLAUDE.md voice files.
Murati's Thinking Machines Ships 975B Inkling — Leads US Open Models
Murati's Thinking Machines releases Inkling, a 975B-parameter MoE model that leads US open models but trails Chinese rivals on benchmarks and cost.
Bluemercury Names Alex Choueiri CEO, Macy’s Continues Exec Shuffle
Alex Choueiri named CEO of Bluemercury, succeeding co-founder Marla Beck. The Macy’s-owned chain has ~160 stores.
How This Solo Builder Ships Features While Sleeping with a 5-Machine Local
Alex Finn's build-and-review loop with Claude Code and local models like OpenClaw automates feature shipping on 5 machines. Key takeaway: set up Tailscale and allocate tasks by model strength.
Mira Murati's Thinking Machines beats frontier models by 29.8% with Bridgewater's expert judgments
Thinking Machines beat frontier models by 29.8% fewer errors using Bridgewater's expert judgments, at 13.8x lower inference cost.
MACCHA: The File-Based Cross-Agent Brain That Makes Claude Code Remember
MACCHA solves Claude Code's cold-start problem with a file-based 7-tier memory system. Use it to persist preferences, project rules, and lessons across sessions without a daemon.
MacArena: 421-Task macOS Benchmark Reveals 26% CUA Ranking Inversion
MacArena benchmark of 421 macOS tasks reveals 26% performance gap for top models on native tasks, suggesting current CUAs overfit to Linux distributions.
SMAC-Talk: StarCraft Benchmark Tests LLM Agents Against Deceptive Allies
SMAC-Talk extends StarCraft Multi-Agent Challenge with natural language communication, testing LLM agents against deceptive allies. Qwen3.5 models benchmarked; no model exceeds 72% win rate.
Codex 'Locked Use' Feature Spotted on macOS
Codex may get locked-use mode on macOS, per screenshot. Enables background AI coding without screen.
Qwen 3.6 27B Hits 34 tok/s on M5 Max MacBook Pro
Qwen 3.6 27B hits 34 tok/s on M5 Max MacBook Pro with 90% acceptance rate, per @rohanpaul_ai. Shows viable local LLM inference on Apple Silicon.
Thinking Machines Unveils Native Multimodal Interaction Model
Thinking Machines unveiled a native interaction model that simultaneously listens, sees, speaks, interrupts, reacts, thinks in background, and uses tools. The approach targets the fundamental turn-based bottleneck of current AI assistants.
Cua Driver Open-Sourced: macOS Agent Control for Any App
Cua released Cua Driver as open-source, allowing agents like Claude Code and Codex to drive any macOS app through visual understanding and direct UI interaction.
Google Collaborates with Macy's to Develop 'Ask Macy's' AI Agent
According to Digital Commerce 360, Google is helping Macy's develop an AI agent called 'Ask Macy's'. This signals a deepening partnership between the retail giant and Google Cloud, aiming to deploy generative AI for customer service and product discovery. While full details are limited, the move represents a direct, large-scale application of conversational AI in luxury and general retail.
AutoZone, Home Depot, Macy’s, and Ulta Partner with Google for Agentic AI
AutoZone, Home Depot, Macy’s, and Ulta Beauty have entered into partnerships with Google Cloud to implement agentic AI solutions. These systems, built on Google's Gemini models, aim to handle complex, multi-step customer interactions. The move signals a shift from experimental chatbots to more autonomous, task-completing AI agents in retail.
Gur Singh Claims 7 M4 MacBooks Match A100, Calls Cloud GPU Training a 'Scam'
Developer Gur Singh posted that seven M4 MacBooks (2.9 TFLOPS each) match an NVIDIA A100's performance, calling cloud GPU training a 'scam' and advocating for distributed, consumer-hardware approaches.
AirTrain Enables Distributed ML Training on MacBooks Over Wi-Fi
Developer @AlexanderCodes_ open-sourced AirTrain, a tool that enables distributed ML training across Apple Silicon MacBooks using Wi-Fi by syncing gradients every 500 steps instead of every step. This makes personal device training feasible for models up to 70B parameters without cloud GPU costs.
Claude Code Runs 100% Locally on Mac via Native 200-Line API Server
A developer created a 200-line server that speaks Anthropic's API natively, allowing Claude Code to run entirely locally on M-series Macs at 65 tokens/second with no cloud dependency.
AI Developer Tools Shift to Mac-First, Excluding Windows/Linux Users
AI developers report a growing trend of cutting-edge AI tools being released exclusively or primarily for macOS, making it difficult for Windows and Linux users to access the latest innovations. This platform shift creates a hardware-based barrier to entry in the AI development ecosystem.
OpenAI Codex Update Adds macOS Agent, Browser, Memory; 3M Weekly Users
OpenAI released a major Codex update featuring background macOS automation, an in-app browser, persistent memory, and 90+ plugins. With 3M weekly users and nearly half of usage now non-coding, Codex is being repositioned as a general work agent.
Perplexity AI Launches 'Personal Computer' for Mac App Orchestration
Perplexity AI has released 'Personal Computer', a feature that integrates with its Mac app to securely orchestrate local files and applications. This move expands its AI assistant from web search to direct desktop interaction.
Mac Studio Runs 122B-Parameter AI Model Locally, Beats AWS on Cost
A developer demonstrated that a $3,999 Mac Studio can run a 122B-parameter AI model locally. Compared to a $5/hour AWS instance, the Mac pays for itself in roughly five weeks of continuous use.
Mac Studio AI Hardware Shortage Signals Shift to Cloud Rentals
Developers report a global shortage of high-memory Apple Silicon Macs, with 128GB Mac Studios unavailable worldwide. This pushes practitioners toward renting cloud H100 GPUs at ~$3/hr, marking a shift from the recent local AI trend.
OpenAI Rebrands Mac Codex App as Unified AI 'Superapp' Platform
OpenAI is transforming its Mac Codex app into a unified AI platform dubbed a 'Superapp,' integrating chat, agent workflows, and multimodal capabilities into a single interface. This move signals a shift from a specialized coding tool to a broader, user-facing desktop AI application.
Atomic Chat's TurboQuant Enables Gemma 4 Local Inference on 16GB MacBook Air
Atomic Chat's new TurboQuant algorithm aggressively compresses the KV cache, allowing models requiring 32GB+ RAM to run on 16GB MacBook Airs at 25 tokens/sec, advancing local AI deployment.
Hazmat Makes `--dangerously-skip-permissions` Actually Safe for Claude Code on macOS
A new tool, Hazmat, enables safe, fully autonomous Claude Code sessions on macOS by applying multiple OS-level security layers, making `--dangerously-skip-permissions` a viable productivity option.
Apple's AI Mac Mini Sells Out, Signaling Unprecedented Demand
Apple's latest Mac mini, featuring its new Apple Intelligence silicon, has sold out across retailers—a first for the typically high-availability product line. This signals overwhelming initial demand for Apple's push into on-device AI computing.
Open-Source AI Assistant Runs Locally on MacBook Air M4 with 16GB RAM, No API Keys Required
A developer showcased a complete AI assistant running entirely on a MacBook Air M4 with 16GB RAM, using open-source models with no cloud API calls. This demonstrates the feasibility of capable local AI on consumer-grade Apple Silicon hardware.
Gemma 4 26B A4B Hits 45.7 tokens/sec Decode Speed on MacBook Air via MLX Community
A community benchmark shows the Gemma 4 26B A4B model running at 45.7 tokens/sec decode speed on a MacBook Air using the MLX framework. This highlights rapid progress in efficient local deployment of mid-size language models on consumer Apple Silicon.