GPU Comparison

The NVIDIA Tesla T4 and Intel Arc A570M represent two very different philosophies in GPU design, yet their benchmark scores place them in a similar performance tier. The Tesla T4 is a mature, end-of-life data center accelerator built on a 12nm process with a massive 545 mm² die, while the Arc A570M is an active, mobile-first part using a denser 6nm process. The data shows a single head-to-head benchmark result, with the Tesla T4 emerging victorious, but the broader context from their respective rival pools reveals a more nuanced picture.

The Tesla T4 achieves an average benchmark score of 66,733, placing it in the 90th percentile of all GPUs. This score is 1.1% higher than the AMD Radeon VII (66,004) and 2.5% higher than the NVIDIA Tesla P40 (65,095). It also leads the AMD Radeon Instinct MI25 (68,562) by 2.7% and the Intel Arc A770 (68,809) by 3.0%, meaning the T4 actually trails those two specific rivals, but its overall standing remains strong. In contrast, the Arc A570M’s average score of 58,239 sits in the 88th percentile. It is nearly identical to the AMD Radeon RX 6950 XT (58,392), which beats it by just 0.3%, and it edges out the AMD Radeon RX 5600 OEM (58,085) by 0.3%. The NVIDIA P102-100 (58,528) and AMD Radeon PRO V710 (58,657) both outpace the Arc part by 0.5% and 0.7%, respectively.

Head-to-Head Benchmarks

The only direct comparison available is the Geekbench OpenCL test, where the NVIDIA Tesla T4 scores 61,276 against the Intel Arc A570M’s 58,239. This gives the Tesla T4 a 5.2% win, a clear margin that underscores its computational edge in this workload. The T4’s advantage is not marginal; it is a decisive lead that reflects its higher raw compute throughput.

Delving into the specs, the Tesla T4’s FP32 performance of 8.141 TFLOPS is substantially higher than the Arc A570M’s 5.325 TFLOPS, a 52.9% advantage in theoretical peak compute. The T4 also doubles the FP16 throughput at 16.28 TFLOPS versus 10.65 TFLOPS, again a 52.9% lead. This suggests the T4 is better suited for compute-heavy tasks that leverage FP32 or FP16 arithmetic.

However, the Arc A570M is not without its own strengths. It has a higher base clock of 900 MHz versus 585 MHz, and although its boost clock of 1300 MHz is lower than the T4’s 1590 MHz, the Arc part’s architecture is tuned for efficiency. The Arc A570M’s pixel rate of 83.20 GPixel/s is lower than the T4’s 101.8 GPixel/s, and its texture rate of 166.4 GTexel/s trails the T4’s 254.4 GTexel/s. These figures align with the T4’s superior rasterization capabilities.

The memory subsystem also favors the Tesla T4. It offers 16 GB of GDDR6 on a 256-bit bus, delivering 320.0 GB/s of bandwidth. The Arc A570M has 8 GB of GDDR6 on a 128-bit bus, yielding 224.0 GB/s. For workloads that are memory-bandwidth bound, the T4’s 42.9% higher bandwidth is a significant advantage. The T4 also has more shading units (2560 vs 2048), more TMUs (160 vs 128), and more RT cores (40 vs 16). The T4 even includes 320 Tensor Cores, which the Arc A570M lacks entirely.

The Verdict

The benchmark results indicate that the NVIDIA Tesla T4 is the stronger performer in a direct comparison. Its 5.2% lead in Geekbench OpenCL, combined with higher FP32 and FP16 throughput, higher memory bandwidth, and more RT cores, makes it the clear choice for compute-intensive applications. The T4’s 90th percentile ranking versus the A570M’s 88th percentile further reinforces this hierarchy.

The Tesla T4’s nearest rivals, such as the AMD Radeon VII and NVIDIA Tesla P40, are all within a 2.5% delta, suggesting that it occupies a competitive spot in the high-performance tier. Its 16 GB memory capacity is double that of the A570M, making it more suitable for large datasets or models that exceed 8 GB. The T4 also has a lower TDP of 70 W compared to the A570M’s 75 W, which is counterintuitive given its larger die and higher performance, evidence of the efficiency of the Turing architecture.

The Arc A570M, while trailing in raw performance, holds its own against a different set of rivals. Its scores are within 0.7% of the AMD Radeon RX 6950 XT, RX 5600 OEM, NVIDIA P102-100, and Radeon PRO V710. This places it in a solid mid-range bracket. It is an active product, meaning it is still in production, while the T4 is end-of-life. For users looking for a current-generation part, the A570M is the only viable option, despite its lower performance.

Where Each One Wins

The NVIDIA Tesla T4 wins in every measurable benchmark category available. It has a higher average benchmark score (66,733 vs 58,239), a higher OpenCL score (61,276 vs 58,239), and a higher percentile ranking (90th vs 88th). Its architectural advantages, more shading units, TMUs, ROPs, RT cores, and Tensor Cores, translate into superior FP32, FP16, pixel, and texture rates. The T4’s 16 GB memory and 320.0 GB/s bandwidth are ideal for AI inference, scientific computing, or rendering tasks that demand large memory pools and high data throughput.

The Intel Arc A570M wins in specific use cases related to its form factor and production status. As an IGP (integrated graphics processor) with no dedicated power connectors, it is designed for portable devices. Its 6nm process node offers a higher transistor density of 42.8M / mm² versus the T4’s 25.0M / mm², indicating a more modern, space-efficient design. The A570M also supports PCIe 4.0 x8, a faster bus interface than the T4’s PCIe 3.0 x16, which could benefit data transfer rates in systems that support it. For mobile workloads where power draw and physical size are constrained, the A570M is the appropriate choice, even if it sacrifices performance.

FAQ

Q: Which GPU has a higher Geekbench OpenCL score?

A: The NVIDIA Tesla T4 scores 61,276, which is 5.2% higher than the Intel Arc A570M’s 58,239.

Q: How does the Tesla T4 compare to its nearest rival, the AMD Radeon VII?

A: The Tesla T4 has an average benchmark score of 66,733, which is 1.1% higher than the AMD Radeon VII’s 66,004.

Q: What is the memory capacity difference between the two GPUs?

A: The NVIDIA Tesla T4 has 16 GB of GDDR6 memory, while the Intel Arc A570M has 8 GB of GDDR6 memory.

Q: Is the Intel Arc A570M still in production?

A: Yes, the Intel Arc A570M has a production status of "Active," while the NVIDIA Tesla T4 is marked as "End-of-life."

Q: Which GPU has more RT cores?

A: The NVIDIA Tesla T4 has 40 RT cores, whereas the Intel Arc A570M has 16 RT cores.

Q: How does the Tesla T4’s FP32 performance compare to the Arc A570M?

A: The Tesla T4 delivers 8.141 TFLOPS of FP32 performance, which is 52.9% higher than the Arc A570M’s 5.325 TFLOPS.

Architecture Differences

The NVIDIA Tesla T4 is built on the Turing architecture, fabricated on a 12nm process at TSMC. It uses a large TU104 chip with 13,600 million transistors spread across a 545 mm² die, resulting in a transistor density of 25.0M / mm². The T4 features 2560 shading units, 160 TMUs, 64 ROPs, 40 RT cores, and 320 Tensor Cores. It operates at a base clock of 585 MHz and a boost clock of 1590 MHz, with memory running at 1250 MHz (10 Gbps effective). The T4 has no display outputs, making it a pure compute accelerator.

The Intel Arc A570M uses the Xe-HPG architecture (Alchemist generation) on a 6nm process at TSMC. Its DG2-256 chip contains 11,500 million transistors on a 269 mm² die, achieving a much higher transistor density of 42.8M / mm². The A570M has 2048 shading units, 128 TMUs, 64 ROPs, and 16 RT cores, but no Tensor Cores. Its base clock is 900 MHz with a boost clock of 1300 MHz, and memory runs at 1750 MHz (14 Gbps effective). The A570M is an IGP with portable-device-dependent display outputs.

Key differences include the T4’s larger memory bus (256-bit vs 128-bit), higher bandwidth (320.0 GB/s vs 224.0 GB/s), and support for PCIe 3.0 x16 versus the A570M’s PCIe 4.0 x8. The T4 also has a lower TDP of 70 W despite its larger die, while the A570M is rated at 75 W. The T4 is a single-slot card with no power connectors, whereas the A570M is an integrated part with no specified power connectors or dimensions. Both support DirectX 12 Ultimate, OpenGL 4.6, and Vulkan 1.4, but the T4’s Tensor Cores give it a distinct advantage in AI workloads that the A570M cannot match.