MaLd0n

Yes

AMD vc tem de patchear muitos apps e outros não funcionam.

Sequoia or Tahoe with 32gb ram

Essas placas são complicadas e precisam de patches extras. Vai no suporte de 200 R$ que a gente resolve isso.

https://olarila.com/topic/5676-hackintosh-efi-folder-with-clover-and-opencore/

Sem suporte de video

no IGPU support

U need create ur personal layout and edit IRQs

https://olarila.com/topic/40033-easy-hackintosh-audio-solution-with-applealc/

U need use alcid=xx for ur audio codec https://olarila.com/topic/40033-easy-hackintosh-audio-solution-with-applealc/

https://suitebench-browser.dnmtechlabs.workers.dev/result/SB-AI-5091AA696B9840C3

This laptop is perfect. All working. I create one asussmc with automatic fan speed, create one layout 171 for hda universal. Just work nice cam, etc.

We are pleased to announce the release of SuiteBench AI, a free AI benchmarking application for macOS. SuiteBench AI was created to provide a practical and consistent way to measure AI-related performance across both Apple Silicon and Intel-based Macs, including systems with discrete GPUs. Rather than generating a simple synthetic number, SuiteBench AI executes multiple computational workloads across the available CPU, GPU, Metal and Core ML paths and combines the measured performance into an easy-to-compare Global AI Score. Main Features Universal macOS application — Apple Silicon + Intel x86_64 CPU AI workloads Metal GPU compute workloads Core ML acceleration Apple Neural Engine support when available Automatic backend selection Quick AI benchmark Complete AI benchmark Extended AI benchmark AI Stress mode Global AI Score Detailed local benchmark results Hardware and system information Real-time benchmark visualization Light and Dark Mode support Integrated AI Assistant Optional downloadable local AI models Local AI engine management AI-assisted benchmark interpretation Online public result database Global hardware rankings Search by CPU, GPU, Mac model or public result ID Compact and lightweight online result publishing SHA-256 result integrity identification Privacy-focused publication Free to use Integrated AI Assistant SuiteBench AI includes an integrated AI Assistant designed to help users understand benchmark results instead of simply presenting raw scores. The assistant can analyze the current benchmark session and provide additional context about the measured performance. It can help interpret: Global AI performance CPU performance GPU performance AI acceleration behavior Benchmark categories Strong and weak areas of the tested system Performance differences between available backends Diagnostic benchmark conditions Overall hardware balance This makes SuiteBench AI not only a benchmarking application, but also an interactive performance analysis tool. The idea is simple: Benchmark the machine. Then use AI to understand the benchmark. Optional Downloadable Local AI Users who want a more advanced AI experience can optionally download and use additional local AI models directly from SuiteBench AI. These models are completely optional and are not required to run any benchmark. The application allows the user to manage the local AI environment, select supported models and use them with the SuiteBench AI Assistant for deeper analysis and conversation. Features include: Optional AI model downloads Model selection directly inside SuiteBench AI Local AI engine installation and management Starting and stopping the selected local AI Local benchmark analysis More advanced result interpretation No dependency on an external AI model for benchmarking The benchmark system remains completely independent from the downloadable AI models. Users who only want to benchmark their hardware can use SuiteBench AI normally without downloading any additional AI model. Users who want deeper analysis can enable a local AI model and turn SuiteBench AI into a more advanced hardware analysis assistant. Local-First AI Design When a downloaded local AI model is used, the model runs through the local AI engine on the Mac. The AI Assistant and the online benchmark database are separate systems. The optional local AI model is used to analyze benchmark information locally. It does not become part of the public benchmark upload. The SuiteBench Browser receives only the compact benchmark result that the user explicitly chooses to publish. SuiteBench Browser SuiteBench AI includes optional integration with SuiteBench Browser, the public benchmark database developed by DNMTechLabs. After completing a benchmark, users can manually publish their result and receive a unique public identifier such as: SB-AI-XXXXXXXXXXXXXXXX Published results can then be compared through the online Global AI ranking. The leaderboard is automatically ordered from the highest Global AI Score to the lowest, making it easy to compare different processors, GPUs and Mac configurations. The public result contains only information directly related to the benchmark, including: Global AI Score CPU GPU Mac model identifier Architecture macOS version Benchmark mode SuiteBench AI version and build Benchmark methodology version SHA-256 integrity hash The online result format is intentionally compact and lightweight. Privacy First Online result publication is completely optional and manual. SuiteBench AI does not include personal files or personal account information in the public benchmark result. The result publication system is designed specifically around benchmark-related technical information. Personal information such as the following is not part of the public result capsule: Username Computer name Serial number MAC address Apple ID Local file paths Personal files Raw benchmark latency samples Detailed raw workload evidence Before publication, SuiteBench AI shows the technical information associated with the result being submitted. Lightweight Online Publishing The online publication architecture was intentionally redesigned to remain extremely lightweight. Instead of uploading large benchmark datasets containing thousands of latency samples and individual workload records, SuiteBench AI creates a compact result capsule containing only the information required for the public result and ranking. A normal result payload is typically only a few hundred bytes. This approach reduces: Network traffic Server processing Database usage Upload failures Backend complexity while keeping the public benchmark database fast and easy to maintain. Benchmark Reliability SuiteBench AI includes multiple mechanisms designed to improve consistency and usability across different hardware. These include: Benchmark warm-up phases Repeated measurements Latency stability analysis Thermal-state monitoring Automatic backend calibration Native execution detection Diagnostic workload handling Resilient Global AI scoring An unavailable or problematic individual workload does not unnecessarily invalidate an otherwise usable completed benchmark. If a benchmark finishes successfully and produces meaningful performance measurements, SuiteBench AI preserves the usable data and calculates the best meaningful Global AI result available from that run. Supported Hardware SuiteBench AI is designed to support a wide range of macOS systems, including: Apple Silicon Macs Intel Macs Integrated GPUs Discrete AMD GPUs Metal-capable GPUs Apple Neural Engine capable systems Available acceleration paths and performance naturally depend on the hardware and macOS configuration. Free Software SuiteBench AI is free. Our goal is to provide the macOS community with a useful AI performance benchmark and gradually build a public database that makes it easier to compare CPUs, GPUs, Mac generations and AI acceleration technologies. No account is required to run the benchmark. Online result publication is optional. Download HERE SuiteBench AI 1.1 Developer: DNMTechLabs Platform: macOS Architecture: Universal — arm64 + x86_64 Price: Free Online Database: SuiteBench Browser Benchmark your Mac, compare your hardware, explore the public rankings and, if you want deeper analysis, use the integrated AI Assistant or an optional downloadable local AI model. DNMTechLabs — Building practical tools for the macOS community.

SystemPulse is a lightweight, native macOS system monitoring application designed to provide real-time hardware and system information without unnecessary background services, external dependencies, or cloud telemetry. Built specifically for macOS, SystemPulse combines native Apple frameworks and low-level system APIs to display essential system information in a clean, responsive dashboard. Main Features Real-time CPU monitoring Total CPU usage Per-core activity Load average CPU model and core information CPU temperature GPU monitoring GPU identification Utilization when exposed by the driver GPU temperature Metal and IORegistry-based information Apple Silicon temperature support M1 family M2 family M3 family M4 family M5 family Additional thermal fallback for newer or unsupported Apple Silicon platforms Intel Mac support Native AppleSMC temperature reading CPU and GPU telemetry where available Memory monitoring Used and available memory Memory pressure Swap information Storage monitoring Volume usage Available space Storage statistics Network monitoring Active interfaces Upload/download activity Native macOS network counters No public IP lookup Process Explorer CPU usage by process Memory usage by process Native libproc implementation Fast process filtering Power information Battery and power-source status where supported Live history graphs CPU GPU Memory Network Other monitored resources Native Temperature Monitoring SystemPulse does not rely on external command-line utilities such as powermetrics. Temperature monitoring is performed directly through native macOS interfaces, including: AppleSMC / IOKit IOAccelerator Apple Silicon thermal sensors HID thermal sensor fallback where required The application validates sensor values before displaying them. If macOS or the hardware does not publish a valid sensor, SystemPulse reports “Not published” instead of generating or estimating a temperature. Intel + Apple Silicon SystemPulse is designed as a Universal macOS application, supporting both: x86_64 arm64 Apple Silicon detection also accounts for execution through Rosetta, so the correct thermal monitoring path can still be selected when a universal build is launched under translation. Privacy SystemPulse is designed to work locally. No analytics No telemetry uploads No account required No cloud backend No public IP lookup No background helper required for normal monitoring No external monitoring service System information remains on your Mac unless you explicitly export a snapshot. Performance The monitoring engine was designed to minimize unnecessary CPU and memory usage. SystemPulse uses: Dedicated background queues for hardware providers Provider execution gates to prevent sampling backlog Bounded history buffers Cached hardware metadata Controlled UI update coalescing Native APIs instead of repeatedly launching shell commands Lazy thermal fallback queries Cached Apple Silicon HID sensor enumeration The objective is simple: monitor the system without becoming a system load itself. Light & Dark Mode The interface automatically follows the selected macOS appearance and includes proper adaptive text and contrast handling for: System Light Dark Release Information This release includes extensive release-oriented auditing and fixes covering: Swift 6 concurrency compatibility Apple Silicon thermal monitoring Intel SMC monitoring CPU/GPU temperature handling Rosetta detection startup window stabilization Light/Dark appearance consistency IOKit/CoreFoundation ownership background task lifecycle provider scheduling bounded caches and history stricter SMC response validation release build configuration The application is built with strict compiler warnings enabled and uses AD-HOC signing for distribution. Requirements macOS 13 or newer Intel or Apple Silicon Mac Sensor availability depends on the hardware, macOS version, firmware and what each device exposes through the operating system. Download HERE Download the latest SystemPulse release and run it directly on your Mac. Feedback, hardware reports and sensor compatibility reports are welcome, especially from different generations of Intel and Apple Silicon Macs.

https://github.com/averycblack/ECEnabler