Apple M5 Pro GPU (16-core) vs Max GPU (32-core)
VS
Apple M5 Pro GPU (16-core)
Custom
Apple M5 Max GPU (32-core)
Custom
We compared two integrated laptop professional GPUs: the Apple M5 Pro GPU (16-core) with 256 pipelines and 2048 shaders against the Max GPU (32-core) that utilizes 512 pipelines and 4096 shaders. Here you will find complete details about specs, efficiency, performance tests, and more.
Review
Gaming
Performance in DirectX, OpenCL, and Vulkan games
Workstation
Perf. in 3D modeling, video editing and rendering apps
AI/ML
Capabilities for machine learning and AI-related tasks
Energy Efficiency
Power consumption efficiency in different scenarios
NanoReview Final Score
Overall video card score
Key differences
Reasons to consider the Apple M5 Max GPU (32-core)
- Performs significantly better (up to 78%) in 3DMark Steel Nomad Lite
- 2x higher maximum theoretical performance (13.3 vs 6.6 TFLOPS)
- Achieves 65% more points in the GeekBench 6 Compute test (124K vs 75K)
- Has 50% higher memory bandwidth: 460.8 vs 307 GB/s
- Has 2x more shading units (4096 vs 2048)
Benchmarks
Graphics cards’ performance in recent benchmarking apps3D Mark
Steel Nomad Lite Score
| Solar Bay | 39369 | 69788 |
| Wild Life Extreme | 19874 | 35786 |
GeekBench 6 OpenCL
GB6 Compute Score
| Background Blur | 153.3 img/sec | 234.8 img/sec |
| Face Detection | 101 img/sec | 158.1 img/sec |
| Horizon Detection | 2.82 Gpixels/sec | 4.48 Gpixels/sec |
| Edge Detection | 4.09 Gpixels/sec | 6.62 Gpixels/sec |
| Gaussian Blur | 3.69 Gpixels/sec | 7.19 Gpixels/sec |
| Feature Matching | 0.84 Gpixels/sec | 1.17 Gpixels/sec |
| Stereo Matching | 212.6 Gpixels/sec | 384.9 Gpixels/sec |
| Particle Physics | 9757.6 FPS | 17866.8 FPS |
| API | OpenCL | OpenCL |
Blender
Blender GPU
Recent User Tests
Apple M5 Pro GPU (16-core)
| Date | Benchmark | Result |
|---|---|---|
| 📘 2026-07-18 (JSK) | Steel Nomad Light | 8894 |
| 📘 2026-03-30 (JSK) | Geekbench 6 OpenCL | 76085 |
Apple M5 Max GPU (32-core)
No benchmark results yet
Artificial Intelligence Tests
Performance in machine learning and artificial intelligence tasksGeekBench 6 ML
GB6 ML Single Precision
GB6 ML Half Precision
GB6 ML Quantized
| Image Classification (SP) | 8260 | 10338 |
| Image Segmentation (HP) | 25244 | 42053 |
| Image Super Resolution (Q) | 33177 | 41729 |
| Face Detection (HP) | 51773 | 71929 |
| Pose Estimation (Q) | 190718 | 287035 |
| Text Classification (SP) | 2913 | 2958 |
| Machine Translation (HP) | 8985 | 9156 |
| Object Detection (SP) | 7777 | 9951 |
| Depth Estimation (Q) | 63837 | 82338 |
| Style Transfer (SP) | 128419 | 264780 |
| Framework | Core ML | Core ML |
| Backend | GPU | GPU |
Specifications
Technical specifications of Apple M5 Pro GPU (16-core) and Max GPU (32-core)General
| Vendor | Apple | Apple |
| Build | Integrated | Integrated |
| Released | March 3, 2026 | March 3, 2026 |
| Case | Laptop | Laptop |
| Purpose | Professional | Professional |
| Segment | Mid-range | Mid-range |
| Architecture | Apple M GPU | Apple M GPU |
| GPU Codename | Custom | Custom |
| Recommended CPU | - Apple M5 Pro (15-Core) or above | - Apple M5 Max (32-сore GPU) or above |
| Used in CPUs | - Apple M5 Pro (15-Core) | - Apple M5 Max (32-сore GPU) |
Laptop GPU ranking (24th and 9th place)
Graphics Processing Unit
| Boost Clock | 1620 MHz | 1620 MHz |
| Shading Units | 2048 | 4096 |
| Texture Mapping Units (TMUs) | 128 | 256 |
| Render Output Units (ROPs) | 64 | 128 |
| Compute Units (Pipelines) | 256 | 512 |
| Instructions Per Cycle | 2 IPC | 2 IPC |
Raw Performance
| Pixel Fill Rate | 104 GPixel/s | 207 GPixel/s |
| Texture Fill Rate | 207 GTexel/s | 415 GTexel/s |
FLOPS (FP32)
Physical
| Interface | Custom | Custom |
| Manufacturing | TSMC | TSMC |
| Fabrication Process | 3 nm | 3 nm |
| Transistor Count | 28 billion | 28 billion |
| Max. Temperature | 100°C | 100°C |
Memory
| Memory Type | System Shared | System Shared |
| Memory Clock | 9600 MHz | 9600 MHz |
| Bus | 256-bit | 384-bit |
| ECC | No | No |
Memory Bandwidth
API
| Ray Tracing | Yes | Yes |
| DLSS | No | No |
Cast your vote
Total votes: 1