Apple M4 GPU (8-core) vs GPU (10-Core)

We compared two integrated laptop professional GPUs: the Apple M4 GPU (8-core) with 128 pipelines and 1024 shaders against the 6 months older GPU (10-Core) that utilizes 160 pipelines and 1280 shaders. Here you will find complete details about specs, efficiency, performance tests, and more.

Review

General comparison of performance in games, applications, power efficiency, and other metrics
Gaming
Performance in DirectX, OpenCL, and Vulkan games
Workstation
Perf. in 3D modeling, video editing and rendering apps
Energy Efficiency
Power consumption efficiency in different scenarios
NanoReview Final Score
Overall video card score

Key differences

Key distinctions and advantages of M4 GPU (10-Core) over M4 GPU (8-core)
Reasons to consider the Apple M4 GPU (10-Core)
  • Performs better (up to 19%) in 3DMark Steel Nomad Lite
  • 27% higher maximum theoretical performance (3.8 vs 3 TFLOPS)
  • Achieves 22% more points in the GeekBench 6 Compute test (37K vs 30K)
  • Has 25% more shading units (1280 vs 1024)

Benchmarks

Graphics cards’ performance in recent benchmarking apps

3D Mark

Multiplatform graphics benchmark suite that directly correlates with performance in modern games
Steel Nomad Lite Score
Solar Bay 13969 16554
Wild Life Extreme 7931 9610
Sources: 3DMark [1], [2]

GeekBench 6 OpenCL

GPU test for computational tasks (image processing, photography, computer vision, and ML)
GB6 Compute Score
Background Blur 57.4 img/sec 72.2 img/sec
Face Detection 41.3 img/sec 48.3 img/sec
Horizon Detection 1.21 Gpixels/sec 1.4 Gpixels/sec
Edge Detection 1.74 Gpixels/sec 1.94 Gpixels/sec
Gaussian Blur 1.12 Gpixels/sec 1.5 Gpixels/sec
Feature Matching 0.43 Gpixels/sec 0.53 Gpixels/sec
Stereo Matching 94.9 Gpixels/sec 123.3 Gpixels/sec
Particle Physics 3902.5 FPS 4938.4 FPS
API OpenCL OpenCL
Sources: Geekbench [3], [4]

Cinebench 2024 GPU

Hardware benchmark using Maxon's Cinema 4D rendering engine
Cinebench 2024 GPU

Blender

Rendering performance test for 3D modeling
Blender GPU
Sources: Blender [9], [10]100 & 529 samples

Artificial Intelligence Tests

Performance in machine learning and artificial intelligence tasks

GeekBench 6 ML

Tests throughput of AI operations in single, half, and quantized precision
GB6 ML Single Precision
GB6 ML Half Precision
GB6 ML Quantized
Image Classification (SP) - 4874
Image Segmentation (HP) - 8168
Image Super Resolution (Q) - 11983
Face Detection (HP) - 17036
Pose Estimation (Q) - 31171
Text Classification (SP) - 2964
Machine Translation (HP) - 3410
Object Detection (SP) - 5112
Depth Estimation (Q) - 22700
Style Transfer (SP) - 60872
Framework - Core ML
Backend - GPU
Sources: Geekbench [9]

Specifications

Technical specifications of Apple M4 GPU (8-core) and GPU (10-Core)

General

Vendor Apple Apple
Build Integrated Integrated
Released October 29, 2024 May 7, 2024
Case Laptop Laptop
Purpose Professional Professional
Segment Mid-range Mid-range
Architecture Apple M GPU Apple M GPU
GPU Codename Custom Custom
Rival Equivalent - - Adreno X1-85
Successor - Apple M5 GPU (8-Core) - Apple M5 GPU (10-Core)
Recommended CPU - Apple M4 (8-Core) or above - Apple M4 (10-Core) or above
Used in CPUs - Apple M4 (8-Core) - Apple M4 (10-Core)
Laptop GPU ranking (66th and 71st place)

Graphics Processing Unit

Base Clock 500 MHz 500 MHz
Boost Clock 1470 MHz 1470 MHz
Shading Units 1024 1280
Texture Mapping Units (TMUs) 64 80
Render Output Units (ROPs) 32 40
Compute Units (Pipelines) 128 160
Instructions Per Cycle 2 IPC 2 IPC

Raw Performance

Pixel Fill Rate 47 GPixel/s 59 GPixel/s
Texture Fill Rate 94 GTexel/s 118 GTexel/s
FLOPS (FP32)
3 TFLOPS
3.8 TFLOPS

Physical

Interface Custom Custom
TGP 15 W 18 W
Manufacturing TSMC TSMC
Fabrication Process 3 nm 3 nm
Transistor Count - 28 billion
Max. Temperature 100°C 100°C

Memory

Memory Type System Shared System Shared
Memory Clock 7500 MHz 7500 MHz
Effective Memory Speed 15000 Mbps 15000 Mbps
Bus 128-bit 128-bit
ECC No No
Memory Bandwidth
120 GB/s
120 GB/s

API

Ray Tracing Yes Yes
DLSS No No

Cast your vote

Choose between two graphics cards
67 (41.9%)
93 (58.1%)
Total votes: 160

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