With the widespread adoption of AI in mobile devices, nearly all smartphones now come equipped with AI capabilities. However, evaluating AI performance remains a hotly debated topic in the industry. Different manufacturers pursue diverse AI development directions, making fair comparisons challenging—akin to comparing track athletes with gymnasts. Currently, several evaluation platforms assess smartphone and chipset AI capabilities, with the most prominent being:
- ETH AI-Benchmark (Zurich AI Score)
- China Telecom AI Evaluation
- Master Lu AI Mark
- AnTuTu AI Score
But which of these four major AI evaluation platforms is the most professional? Let’s dive into a detailed analysis.
What Do AI Benchmarks Actually Measure?
Before comparing platforms, it’s essential to understand the key dimensions of AI evaluation: performance and precision.
- Performance: Measures the speed of processing AI applications (similar to CPU/GPU benchmarks).
- Precision: Evaluates the accuracy of AI computations, particularly in handling data types like INT8 (8-bit) and FP16 (16-bit).
FP16 vs. INT8: Precision Trade-offs
- FP16: Higher precision (16-bit) but requires more computational power. Ideal for high-detail tasks like HDR image processing, slow-motion video (e.g., 7680fps), and advanced AI applications (e.g., background blur, real-time video editing).
- INT8: Lower precision (8-bit) but more efficient in memory usage and power consumption. Prone to artifacts in high-contrast or low-light scenarios.
👉 Discover how FP16 enhances AI imaging
Which AI Benchmark Platform Is the Most Reliable?
1. Academic Leader: ETH AI-Benchmark (Zurich)
Developed by ETH Zurich, this platform is widely cited by tech media and influencers. Its strengths include:
- Testing multiple precisions (INT8, FP16, FP32) across diverse AI tasks (e.g., image classification, face recognition, semantic segmentation).
- Real-world application scenarios (e.g., image super-resolution, memory stress tests).
- Huawei and Honor devices consistently rank high, reflecting their AI innovations (e.g., AI-assisted photography, gesture controls).
2. Operator-Driven: China Telecom AI Evaluation
China Telecom’s framework assesses:
- Performance, precision, and energy efficiency across networks (classification, detection, super-resolution).
- Detailed metrics like TOP1/TOP5 accuracy and platform-specific SDK comparisons.
3. Benchmark Tools: Master Lu AI Mark & AnTuTu
- Master Lu: Tests AI performance using networks like Inception V3 and ResNet34 but lacks comprehensive precision analysis.
- AnTuTu: Uses vendor-specific SDKs (e.g., Qualcomm SNPE, Huawei HiAI), limiting cross-platform comparability. Critics question its objectivity.
👉 Why ETH’s methodology stands out
FAQs
Q1: Why does FP16 outperform INT8 in imaging?
A: FP16’s wider bitwidth preserves finer details, reducing noise and artifacts in high-dynamic-range scenarios.
Q2: Which platform do manufacturers trust most?
A: ETH AI-Benchmark and China Telecom are preferred for their academic rigor and multi-dimensional testing.
Q3: Can INT8 still be useful?
A: Yes! INT8 excels in low-power applications where memory efficiency outweighs precision loss.
Q4: How long until AI benchmarks standardize?
A: Like CPU benchmarks in the 1990s, it may take years of industry collaboration to establish universal standards.
Conclusion
While no single AI evaluation platform is perfect, ETH AI-Benchmark and China Telecom lead in comprehensiveness and objectivity. As AI technology evolves, standardized testing will emerge—but for now, these two platforms offer the most reliable insights.
For deeper dives into AI performance, stay tuned to our tech analyses!