NVIDIA GeForce RTX 3090 Ti vs NVIDIA Tesla T4 Comparison

Head-to-Head Benchmarks

The database records two direct benchmark comparisons between the NVIDIA GeForce RTX 3090 Ti and the NVIDIA Tesla T4, and the results are decisively one-sided. In Geekbench OpenCL, the RTX 3090 Ti scores 174,441 points against the Tesla T4's 61,276 points. That is a delta of 184.7%, meaning the RTX 3090 Ti delivers nearly triple the raw compute throughput in this workload. The margin is even steeper in Geekbench Vulkan: the RTX 3090 Ti posts 215,633 points versus 72,190 points for the Tesla T4, a 198.7% advantage. In short, the RTX 3090 Ti is not just faster, it is in a different performance class entirely.

Looking at the average benchmark scores across the full database, the RTX 3090 Ti sits at 131,938, while the Tesla T4 sits at 66,733. That is a 97.7% gap in the aggregate, which aligns with the head-to-head results. The RTX 3090 Ti's percentile ranking among all GPUs is 95, placing it in the top 5% of every card the database has measured. The Tesla T4, by contrast, ranks at the 90th percentile, which is still strong but reflects a fundamentally lower performance tier. When placed against its nearest rivals, the RTX 3090 Ti's average score is within 0.7% of the NVIDIA L4 (131,072), 2.4% below the RTX 4000 Ada Generation (135,218), and 2.4% below the A10M (135,230). The Tesla T4's closest competitors include the AMD Radeon VII at 66,004 (1.1% behind), the Tesla P40 at 65,095 (2.5% behind), and the AMD Radeon Instinct MI25 at 68,562 (2.7% ahead).

The data shows a clear pattern: the RTX 3090 Ti wins every recorded benchmark against the Tesla T4. There are no tests where the Tesla T4 takes the lead. The wins tally is 2 for the RTX 3090 Ti and 0 for the Tesla T4. This is not a close contest; it is a generational and architectural gap that shows up in every metric measured.

FAQ

Q: Which GPU has the higher average benchmark score?

A: The NVIDIA GeForce RTX 3090 Ti has a significantly higher average benchmark score of 131,938, compared to the NVIDIA Tesla T4's 66,733. The RTX 3090 Ti also ranks in the 95th percentile of all GPUs, while the Tesla T4 ranks in the 90th percentile.

Q: How much faster is the RTX 3090 Ti in Geekbench Vulkan?

A: The RTX 3090 Ti scores 215,633 points in Geekbench Vulkan, while the Tesla T4 scores 72,190 points. That is a 198.7% delta, meaning the RTX 3090 Ti is nearly three times faster in this specific test.

Q: Does the Tesla T4 win any benchmark against the RTX 3090 Ti?

A: No. The database records two head-to-head benchmarks (Geekbench OpenCL and Geekbench Vulkan), and the RTX 3090 Ti wins both. The wins tally is 2 for the RTX 3090 Ti and 0 for the Tesla T4.

Q: What is the memory configuration difference between the two cards?

A: The RTX 3090 Ti has 24 GB of GDDR6X memory on a 384-bit bus, delivering 1.01 TB/s of bandwidth. The Tesla T4 has 16 GB of GDDR6 memory on a 256-bit bus, delivering 320.0 GB/s of bandwidth.

Q: How do their closest rivals compare?

A: The RTX 3090 Ti's average score is 0.7% above the NVIDIA L4 (131,072) and 2.4% below the RTX 4000 Ada Generation (135,218) and the A10M (135,230). The Tesla T4's average score is 1.1% above the AMD Radeon VII (66,004) and 3% below the Intel Arc A770 (68,809).

Q: What is the TDP difference?

A: The RTX 3090 Ti has a TDP of 450 W, while the Tesla T4 has a TDP of 70 W. The suggested power supply is 850 W for the RTX 3090 Ti and 250 W for the Tesla T4.

The Verdict

The data is unambiguous. The RTX 3090 Ti is the far more powerful GPU in every recorded benchmark, with a 184.7% lead in OpenCL and a 198.7% lead in Vulkan. Its average score of 131,938 places it in the 95th percentile of all GPUs, whereas the Tesla T4's 66,733 places it in the 90th percentile. If the goal is maximum compute throughput, the RTX 3090 Ti is the clear choice.

However, the Tesla T4 is not without its own rationale. Its TDP is 70 W versus 450 W for the RTX 3090 Ti, and it requires no auxiliary power connectors while the RTX 3090 Ti needs a 16-pin connector and an 850 W power supply. The Tesla T4 is a single-slot card, while the RTX 3090 Ti is triple-slot. For deployments where power and space are constrained, the Tesla T4's 70 W envelope and compact footprint make it a practical option. Its 16 GB of GDDR6 memory is also substantial, though its 320.0 GB/s bandwidth is far below the RTX 3090 Ti's 1.01 TB/s.

The verdict hinges on the use case. For raw performance in applications that can leverage massive FP32 throughput (40.00 TFLOPS versus 8.141 TFLOPS), the RTX 3090 Ti wins outright. For low-power inference or edge deployments where the 70 W TDP and single-slot form factor matter more than raw speed, the Tesla T4 is the sensible pick. The data does not support choosing the Tesla T4 for performance reasons; it supports choosing it for efficiency and physical constraints.

Specification Differences

The two cards differ across nearly every specification. The RTX 3090 Ti uses the GA102 chip on an 8 nm Samsung process, while the Tesla T4 uses the TU104 chip on a 12 nm TSMC process. The RTX 3090 Ti has 28,300 million transistors on a 628 mm² die, whereas the Tesla T4 has 13,600 million transistors on a 545 mm² die. Transistor density is 45.1M per mm² for the RTX 3090 Ti and 25.0M per mm² for the Tesla T4.

Clock speeds are also notably different. The RTX 3090 Ti has a base clock of 1560 MHz and a boost clock of 1860 MHz. The Tesla T4 has a base clock of 585 MHz and a boost clock of 1590 MHz. Memory clocks differ as well: the RTX 3090 Ti runs at 1313 MHz with 21 Gbps effective, while the Tesla T4 runs at 1250 MHz with 10 Gbps effective.

The memory subsystems are dissimilar. The RTX 3090 Ti has 24 GB of GDDR6X on a 384-bit bus with 1.01 TB/s bandwidth. The Tesla T4 has 16 GB of GDDR6 on a 256-bit bus with 320.0 GB/s bandwidth. The RTX 3090 Ti also has far more compute units: 10,752 shading units versus 2,560, 336 TMUs versus 160, 112 ROPs versus 64, 84 RT cores versus 40, and 336 tensor cores versus 320.

Pixel rate is 208.3 GPixel/s for the RTX 3090 Ti versus 101.8 GPixel/s for the Tesla T4. Texture rate is 625.0 GTexel/s versus 254.4 GTexel/s. FP32 performance is 40.00 TFLOPS versus 8.141 TFLOPS, and FP16 is 40.00 TFLOPS (1:1) for the RTX 3090 Ti versus 16.28 TFLOPS (2:1) for the Tesla T4.

Physical dimensions differ substantially. The RTX 3090 Ti is 336 mm long, 140 mm tall, and 61 mm wide, occupying a triple-slot profile. The Tesla T4 is 168 mm long and single-slot. The RTX 3090 Ti uses a 16-pin power connector, while the Tesla T4 uses none. The suggested PSU is 850 W for the RTX 3090 Ti and 250 W for the Tesla T4. The RTX 3090 Ti has display outputs (1x HDMI 2.1, 3x DisplayPort 1.4a), while the Tesla T4 has none. The bus interface is PCIe 4.0 x16 for the RTX 3090 Ti and PCIe 3.0 x16 for the Tesla T4.

Architecture Differences

The architectural gap is fundamental. The RTX 3090 Ti is built on the Ampere architecture, while the Tesla T4 is built on the older Turing architecture. Ampere uses an 8 nm Samsung process, while Turing uses a 12 nm TSMC process. This process difference partially explains the transistor count: 28,300 million for Ampere versus 13,600 million for Turing, despite the RTX 3090 Ti's larger die (628 mm² versus 545 mm²).

The RTX 3090 Ti has 84 RT cores and 336 tensor cores, versus 40 RT cores and 320 tensor cores for the Tesla T4. The RT core count is more than double, which is relevant for ray-traced workloads. The tensor core counts are closer, but the RTX 3090 Ti's tensor cores operate at far higher clocks and within a larger memory bandwidth envelope.

FP16 performance reveals a key architectural difference. The RTX 3090 Ti delivers 40.00 TFLOPS FP16 at a 1:1 ratio with FP32, meaning it does not sacrifice FP32 throughput for half-precision work. The Tesla T4 delivers 16.28 TFLOPS FP16 at a 2:1 ratio, meaning it doubles FP16 throughput relative to its 8.141 TFLOPS FP32. This makes the Tesla T4 relatively stronger in FP16 workloads when normalized to its FP32 baseline, though the absolute FP16 number is still lower than the RTX 3090 Ti's.

The generation names reflect the timeline: the RTX 3090 Ti is from the GeForce 30-series with a release date of 2022-01-26, while the Tesla T4 is from the Tesla Turing (Txx) generation with a release date of 2018-09-12. The RTX 3090 Ti's predecessor is GeForce 20 and its successor is GeForce 40. The Tesla T4's predecessor is Tesla Volta and its successor is Server Ampere. Both are end-of-life in production status.

Where Each One Wins

The RTX 3090 Ti wins in every performance metric recorded in the database. It takes the Geekbench OpenCL test by 184.7% and the Geekbench Vulkan test by 198.7%. Its FP32 throughput of 40.00 TFLOPS is nearly five times the Tesla T4's 8.141 TFLOPS. Its memory bandwidth of 1.01 TB/s is more than three times the Tesla T4's 320.0 GB/s. Its pixel rate (208.3 GPixel/s versus 101.8 GPixel/s) and texture rate (625.0 GTexel/s versus 254.4 GTexel/s) are both roughly double. For any workload that stresses raw compute, rasterization, or memory throughput, the RTX 3090 Ti is the clear winner.

The Tesla T4 wins in efficiency and physical integration. Its 70 W TDP is a fraction of the RTX 3090 Ti's 450 W, and it requires no power connectors and only a 250 W suggested PSU. It is a single-slot card at 168 mm length, versus the RTX 3090 Ti's triple-slot, 336 mm length. In a dense server environment, the Tesla T4 can fit into far more chassis and power budgets. Its 16 GB of GDDR6 memory is also adequate for many inference workloads, and its FP16 performance of 16.28 TFLOPS (2:1) is respectable relative to its FP32 baseline.

The use-case split is clean. For desktop workstations, content creation, gaming, or any compute task where performance is the priority, the RTX 3090 Ti is the only rational choice based on the data. For low-power inference, edge servers, or multi-card deployments where the 70 W envelope and single-slot form factor are decisive, the Tesla T4 has a clear role. The benchmark data does not show a single test where the Tesla T4 outperforms the RTX 3090 Ti, but it shows a very different set of tradeoffs around power, size, and deployment flexibility.