NVIDIA RTX A4500 vs NVIDIA Tesla T4 Comparison

Where Each One Wins

The NVIDIA RTX A4500 and NVIDIA Tesla T4 serve fundamentally different segments of the workstation market, and the recorded benchmark data reflects that split clearly. The RTX A4500 wins both head-to-head tests, and the margin of those wins is decisive. The data shows a clean sweep: 2 wins for the RTX A4500, 0 for the Tesla T4. However, the context matters more than the scoreboard.

The RTX A4500 dominates in raw compute throughput. In Geekbench OpenCL, the RTX A4500 scores 141837 against the Tesla T4's 61276, a 131.5% advantage. That is not a marginal edge; it is more than double the output. For workloads that rely on general compute acceleration, such as simulation, rendering, or data processing on the workstation, the RTX A4500 is the clear choice. The same pattern holds in Geekbench Vulkan, where the RTX A4500 scores 129980 versus 72190, an 80.1% lead. Vulkan workloads, which often stress graphics and compute pipelines together, also favor the Ampere card heavily.

The Tesla T4 wins in a different arena: deployment efficiency, not performance. The T4 is a single-slot, 70 W card with no power connectors and no display outputs. It draws its power entirely from the PCIe slot, and its suggested power supply is 250 W. The RTX A4500, by contrast, is a dual-slot card with a 200 W TDP, requires a single 8-pin power connector, and needs a 550 W power supply. The T4 also runs on PCIe 3.0 x16 while the RTX A4500 uses PCIe 4.0 x16. For dense server deployments where thermal envelope and physical space are the constraints, the T4 is the only sensible option between the two. The RTX A4500 may be faster, but the T4 fits where the RTX A4500 cannot.

The compute feature sets also differ. The RTX A4500 has 56 RT cores and 224 tensor cores. The Tesla T4 has 40 RT cores and 320 tensor cores. The T4's tensor core count is higher, and its FP16 throughput is rated at 16.28 TFLOPS (2:1), which is higher than its FP32 rate of 8.141 TFLOPS. The RTX A4500 runs FP16 at 23.65 TFLOPS (1:1), identical to its FP32 rate. For inference tasks that use FP16 tensor operations, the T4 is proportionally more capable relative to its overall compute rating, though the RTX A4500's absolute FP16 number is still higher. The data does not include a head-to-head tensor benchmark, so direct claims are not possible, but the specification list indicates the T4 was designed with an emphasis on accelerated inference efficiency.

In short, the RTX A4500 wins on performance across the board in the recorded tests. The Tesla T4 wins on physical and power constraints. The right pick depends entirely on whether the workload demands maximum throughput or maximum deployment density with minimal power draw.

The Verdict

From the benchmark results alone, the verdict is unambiguous for compute-heavy workstation use: choose the NVIDIA RTX Pick the RTX A4500 for any scenario where performance is the limiting factor. Its Geekbench OpenCL score of 141837 places it 131.5% ahead of the Tesla T4, and its Geekbench Vulkan score of 129980 places it 80.1% ahead. The RTX A4500 sits at the 93rd percentile among all GPUs in the database, which is above the Tesla T4's 90th percentile. The average benchmark score of 91671 for the RTX A4500 is 37.4% higher than the Tesla T4's 66733 average.

Choose the Tesla T4 for server or edge deployment where power and space are the hard constraints. The T4 is a single-slot card at 70 W with no external power connectors, no display outputs, and a 250 W suggested PSU. The RTX A4500 is dual-slot, uses 200 W, requires an 8-pin connector, and asks for a 550 W PSU. The T4's 16 GB memory capacity is lower than the RTX A4500's 20 GB, but for inference-heavy workloads that fit within 16 GB, the T4's higher tensor core count (320 versus 224) and its FP16 throughput advantage relative to its FP32 rate (16.28 TFLOPS versus 8.141 TFLOPS) indicate a design tuned for AI inference efficiency.

The RTX A4500 is end-of-life production status, as is the Tesla T4. Neither card is a future-proof acquisition. But for anyone choosing between the two today, the performance gap is too large to ignore unless the deployment physically requires the T4's form factor. The data says: performance goes to the RTX A4500, density goes to the Tesla T4.

Head-to-Head Benchmarks

The head-to-head records contain two tests, and the RTX A4500 wins both. The first, Geekbench OpenCL, shows the RTX A4500 at 141837 against the Tesla T4 at 61276. That is a 131.5% delta in favor of the RTX A4500. OpenCL is a broad compute workload that approximates general-purpose GPU tasks, including rendering, physics simulation, and data-parallel processing. A 131.5% advantage means the RTX A4500 completes roughly the same OpenCL work in less than half the time, assuming linear scaling. For any OpenCL-based application, the RTX A4500 is the faster card by a wide margin.

The second test, Geekbench Vulkan, shows the RTX A4500 at 129980 and the Tesla T4 at 72190, a delta of 80.1%. Vulkan is a graphics and compute API, and the RTX A4500's lead here is narrower than in OpenCL but still substantial. The RTX A4500's advantage in Vulkan is driven by its larger shading unit count (7168 versus 2560), higher texture rate (369.6 GTexel/s versus 254.4 GTexel/s), and higher pixel rate (158.4 GPixel/s versus 101.8 GPixel/s). The Tesla T4's higher tensor core count does not directly accelerate Vulkan graphics workloads; those tensor cores are for inference operations. As such, graphics API tests naturally favor the RTX A4500.

The RTX A4500's wins are not the only relevant numbers. The RTX A4500's nearest rivals in the database are the NVIDIA RTX A4500 Mobile (average score 91134, 0.6% lower), the AMD Radeon Instinct MI60 (92466, 0.9% higher), the NVIDIA Quadro GP100 (87445, 4.8% lower), and the AMD Radeon PRO W7600 (87108, 5.2% lower). The Tesla T4's nearest rivals include the AMD Radeon VII (66004, 1.1% lower), the NVIDIA Tesla P40 (65095, 2.5% lower), the AMD Radeon Instinct MI25 (68562, 2.7% higher), and the Intel Arc A770 (68809, 3% higher). These figures place both cards in the upper tier of the database, but the RTX A4500 sits clearly above the T4 in absolute terms.

FAQ

Q: Which GPU is faster in Geekbench OpenCL?

A: The NVIDIA RTX A4500 scores 141837, which is 131.5% higher than the Tesla T4's 61276.

Q: Which GPU is faster in Geekbench Vulkan?

A: The NVIDIA RTX A4500 scores 129980, which is 80.1% higher than the Tesla T4's 72190.

Q: Which card has a higher average benchmark score?

A: The NVIDIA RTX A4500 has an average benchmark score of 91671, while the NVIDIA Tesla T4 has 66733. The RTX A4500 also ranks at the 93rd percentile among all GPUs, compared to the Tesla T4's 90th percentile.

Q: What are the power requirements of each card?

A: The NVIDIA RTX A4500 has a 200 W TDP, requires a single 8-pin power connector, and suggests a 550 W power supply. The NVIDIA Tesla T4 has a 70 W TDP, requires no power connectors, and suggests a 250 W power supply.

Q: How much memory does each card have?

A: The NVIDIA RTX A4500 has 20 GB of GDDR6 memory on a 320-bit bus with 640.0 GB/s bandwidth. The NVIDIA Tesla T4 has 16 GB of GDDR6 memory on a 256-bit bus with 320.0 GB/s bandwidth.

Q: Do both cards support the same graphics APIs?

A: Yes, both support DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4 according to the recorded specifications.

Architecture Differences

The two cards come from different NVIDIA architectures. The RTX A4500 is built on Ampere, using the GA102 chip, fabricated on Samsung's 8 nm process. The Tesla T4 is built on Turing, using the TU104 chip, fabricated on TSMC's 12 nm process. The process difference is significant: the RTX A4500 packs 28,300 million transistors into a 628 mm² die, giving a transistor density of 45.1 million per square millimeter. The Tesla T4 contains 13,600 million transistors on a 545 mm² die, with a density of 25.0 million per square millimeter. The RTX A4500's higher density reflects the newer process node.

The memory architectures differ as well. The RTX A4500 uses a 320-bit bus with 20 GB of GDDR6 and 640.0 GB/s bandwidth. The Tesla T4 uses a 256-bit bus with 16 GB of GDDR6 and 320.0 GB/s bandwidth. The RTX A4500 doubles the bandwidth, which helps its compute and graphics throughput. The effective memory clock is listed as 16 Gbps for the RTX A4500 and 10 Gbps for the Tesla T4.

Compute resources also diverge. The RTX A4500 has 7168 shading units, 224 TMUs, 96 ROPs, 56 RT cores, and 224 tensor cores. The Tesla T4 has 2560 shading units, 160 TMUs, 64 ROPs, 40 RT cores, and 320 tensor cores. The RTX A4500 has more shading units, TMUs, ROPs, and RT cores. The Tesla T4 has more tensor cores. The FP32 and FP16 relationship differs: the RTX A4500 runs FP16 at 23.65 TFLOPS (1:1 with FP32), while the Tesla T4 runs FP16 at 16.28 TFLOPS (2:1, twice its FP32 rate of 8.141 TFLOPS). The RTX A4500's FP32 rate is 23.65 TFLOPS, nearly three times the Tesla T4's 8.141 TFLOPS.

Specification Differences

The NVIDIA RTX A4500 and NVIDIA Tesla T4 differ across several specification fields. The process node is 8 nm for the RTX A4500 and 12 nm for the Tesla T4. The transistor count is 28,300 million versus 13,600 million. Die size is 628 mm² versus 545 mm². Base clock is 1050 MHz for the RTX A4500 and 585 MHz for the Tesla T4. Boost clock is 1650 MHz versus 1590 MHz. Memory clock is 2000 MHz (16 Gbps effective) versus 1250 MHz (10 Gbps effective).

Memory size: 20 GB versus 16 GB. Bus width: 320-bit versus 256-bit. Bandwidth: 640.0 GB/s versus 320.0 GB/s. Shading units: 7168 versus 2560. TMUs: 224 versus 160. ROPs: 96 versus 64. RT cores: 56 versus 40. Tensor cores: 224 versus 320. Pixel rate: 158.4 GPixel/s versus 101.8 GPixel/s. Texture rate: 369.6 GTexel/s versus 254.4 GTexel/s. FP32: 23.65 TFLOPS versus 8.141 TFLOPS. FP16: 23.65 TFLOPS (1:1) versus 16.28 TFLOPS (2:1). TDP: 200 W versus 70 W. Slot width: dual-slot versus single-slot. Power connectors: 1x 8-pin versus none. Suggested PSU: 550 W versus 250 W. Bus interface: PCIe 4.0 x16 versus PCIe 3.0 x16. Display outputs: 4x DisplayPort 1.4a versus no outputs. Dimensions: 267 mm length versus 168 mm length. Release date: 2021-11-22 versus 2018-09-12.