NVIDIA T400 vs NVIDIA Tesla K20m Comparison

Where Each One Wins

The two benchmarks recorded in the database split cleanly between these NVIDIA cards, with each taking one victory. The NVIDIA Tesla K20m wins the Geekbench Vulkan test decisively, posting a score of 21936 against the NVIDIA T400's 15976. That is a 37.3% advantage, a substantial gap that suggests the older Kepler architecture retains significant strength in compute-oriented Vulkan workloads. The Tesla K20m's victory here is not marginal; it is a dominant margin that places it well ahead in this specific API scenario.

The NVIDIA T400, by contrast, takes the Geekbench OpenCL test. Its score of 17039 edges out the Tesla K20m's 16241, a 4.7% difference. This is a narrower win, indicating that while the T400 is superior in OpenCL, the gap is nowhere near as dramatic as the Tesla K20m's Vulkan lead. The two cards therefore appeal to different workloads: the T400 is the better choice for OpenCL-centric tasks, while the Tesla K20m dominates in Vulkan environments. The database's win count reflects this balance, with each card claiming one benchmark. Users should weigh which API matters more for their specific applications, as the data shows no overall winner across both tests. The Tesla K20m's Vulkan blowout is the largest single-score difference in the head-to-head, while the T400's OpenCL win is comparatively modest. This split suggests that the choice between these two depends heavily on the software stack in use, not on general-purpose performance.

FAQ

Q: Which card has the higher average benchmark score?

A: The NVIDIA Tesla K20m records an average benchmark score of 19089, compared to the NVIDIA T400's 16508. The Tesla K20m also holds a higher percentile ranking at 64 versus the T400's 60.

Q: How does the Tesla K20m perform relative to its nearest rivals?

A: The Tesla K20m's nearest rivals include the NVIDIA GeForce RTX 4050 Mobile at 19049 (0.2% higher), the AMD Radeon RX 6600 at 19036 (0.3% higher), and the NVIDIA Quadro K6000 at 19030 (0.3% higher). It also sits just above the NVIDIA GeForce GTX 780, which scores 19164, putting the Tesla K20m 0.4% behind that card.

Q: What about the T400's competitive position?

A: The T400's nearest rivals are the NVIDIA GeForce RTX 5090 D V2 at 16504 (a 0% delta), the AMD Radeon PRO W7500 at 16415 (0.6% lower), the NVIDIA RTX PRO 6000 Blackwell at 16408 (0.6% lower), and the AMD Radeon RX 5700 XT at 16361 (0.9% lower). The T400 sits slightly above all of these except the RTX 5090 D V2, which is essentially tied.

Q: What are the memory specifications of each card?

A: The Tesla K20m has 5 GB of GDDR5 memory on a 320-bit bus, with 208.0 GB/s bandwidth. The T400 has 2 GB of GDDR6 memory on a 64-bit bus, with 80.00 GB/s bandwidth.

Q: Which card is more power-efficient according to the data?

A: The T400 has a TDP of 30 W, while the Tesla K20m is rated at 225 W. The T400 also requires no power connectors and suggests a 200 W PSU, whereas the Tesla K20m needs a 1x 6-pin plus 1x 8-pin connector and suggests a 550 W PSU.

Q: Do both cards support the same DirectX version?

A: No. The Tesla K20m supports DirectX 12 (11_0), while the T400 supports DirectX 12 (12_1). Both support OpenGL 4.6, but their Vulkan versions differ: the Tesla K20m has 1.2.175, and the T400 has 1.4.

Head-to-Head Benchmarks

The two recorded benchmarks provide a clear picture of how these cards diverge. In Geekbench Vulkan, the Tesla K20m achieves a score of 21936, while the T400 manages only 15976. The delta is 37.3% in favor of the Tesla K20m, making this the largest performance gap in either direction. This is not a close contest; the Tesla K20m outperforms the T400 by a wide margin in Vulkan, suggesting its GK110 chip with 2496 shading units and 208 texture mapping units delivers far more compute throughput in this API. The T400's 384 shading units and 24 TMUs are simply outmatched here, despite the newer architecture.

In Geekbench OpenCL, the situation reverses, though less dramatically. The T400 scores 17039, and the Tesla K20m scores 16241, a 4.7% difference. The T400's win is real but narrow, indicating that its Turing architecture handles OpenCL workloads more efficiently on a per-unit basis. The T400's higher boost clock of 1425 MHz (versus no recorded boost for the Tesla K20m) likely contributes to this efficiency, as does its 2:1 FP16 capability at 2.189 TFLOPS, which the Tesla K20m lacks entirely. Still, the Tesla K20m's raw FP32 throughput of 3.524 TFLOPS dwarfs the T400's 1,094.4 GFLOPS, so the OpenCL result is somewhat surprising. The data implies that the T400's architecture extracts more usable performance from its smaller shader count, at least in this specific test. Across both benchmarks, the average scores tell a similar story: the Tesla K20m averages 19089, while the T400 averages 16508, a difference of roughly 15.6% in favor of the older card, driven almost entirely by the Vulkan result.

Specification Differences

The two cards diverge sharply on nearly every hardware specification. The Tesla K20m uses 28 nm process technology with 7,080 million transistors on a 561 mm² die, yielding a transistor density of 12.6M per mm². The T400 uses 12 nm with 4,700 million transistors on a 200 mm² die, giving a higher density of 23.5M per mm². Memory differs fundamentally: the Tesla K20m has 5 GB of GDDR5 on a 320-bit bus with 208.0 GB/s bandwidth and a memory clock of 1300 MHz (5.2 Gbps effective). The T400 has 2 GB of GDDR6 on a 64-bit bus with 80.00 GB/s bandwidth and a memory clock of 1250 MHz (10 Gbps effective). The T400's GDDR6 is faster per pin, but its narrow bus severely limits total bandwidth.

Compute resources also diverge. The Tesla K20m has 2496 shading units, 208 TMUs, and 40 ROPs, while the T400 has 384 shading units, 24 TMUs, and 16 ROPs. Pixel and texture rates follow: the Tesla K20m reaches 36.71 GPixel/s and 146.8 GTexel/s, whereas the T400 achieves 22.80 GPixel/s and 34.20 GTexel/s. FP32 performance is 3.524 TFLOPS for the Tesla K20m versus 1,094.4 GFLOPS for the T400. The T400 adds FP16 at 2.189 TFLOPS (2:1), which the Tesla K20m does not support. Power draw is dramatically different: 225 W for the Tesla K20m versus 30 W for the T400. The Tesla K20m is dual-slot with a 1x 6-pin and 1x 8-pin connector and a 550 W suggested PSU, while the T400 is single-slot with no power connectors and a 200 W suggested PSU. The T400 also supports PCIe 3.0 x16, whereas the Tesla K20m uses PCIe 2.0 x16.

Architecture Differences

Both cards come from NVIDIA but represent different architectural eras. The Tesla K20m is built on Kepler, with the GK110 chip, and belongs to the Tesla Kepler generation. The T400 is built on Turing, with the TU117 chip, and belongs to the Quadro Turing generation. The process node moved from 28 nm on the Tesla K20m to 12 nm on the T400, both fabricated by TSMC. The transistor density more than doubled from 12.6M per mm² to 23.5M per mm², reflecting the newer process. The T400's TU117 is a smaller chip at 200 mm² versus the GK110's 561 mm², though the GK110 packs far more transistors overall.

Architectural features differ in meaningful ways. The T400 supports DirectX 12 (12_1) and Vulkan 1.4, while the Tesla K20m supports DirectX 12 (11_0) and Vulkan 1.2.175. Both have OpenGL 4.6. The T400 has FP16 support at 2.189 TFLOPS with a 2:1 ratio, a feature absent from the Tesla K20m, which only lists FP32. Neither card has dedicated ray tracing or tensor cores. Memory type also reflects the architectural gap: GDDR5 for Kepler versus GDDR6 for Turing, with the T400's 12 nm process enabling higher effective data rates. The T400's base clock is 420 MHz with a boost up to 1425 MHz, while the Tesla K20m has no recorded base or boost clocks. Display outputs differ completely: the T400 has 3x mini-DisplayPort 1.4a, while the Tesla K20m has no outputs, as it is a compute-focused accelerator. The T400 is also a single-slot card versus the Tesla K20m's dual-slot design.

The Verdict

The data points to two distinct usage scenarios. The NVIDIA Tesla K20m is the clear choice for Vulkan-heavy workloads, where its 37.3% lead over the T400 is decisive. Its 5 GB memory and 208.0 GB/s bandwidth also make it better suited for large datasets, and its average benchmark score of 19089 places it in the 64th percentile, above the T400's 60th percentile. The Tesla K20m's FP32 throughput of 3.524 TFLOPS is more than triple the T400's, so any task that relies on raw single-precision compute will favor it. However, this comes at a cost in power: 225 W versus 30 W, and the Tesla K20m's lack of display outputs means it is strictly for server or compute environments.

The NVIDIA T400 is the more balanced card for workstation use, given its display outputs and modern feature set. Its OpenCL win, though narrow at 4.7%, shows it can outperform the Tesla K20m in that API. The T400's Vulkan 1.4 support and DirectX 12 (12_1) are ahead of the Tesla K20m's older standards. Its lower power draw and single-slot form factor are practical advantages. For users running OpenCL applications or needing a card with display connectivity, the T400 is the logical pick. The Tesla K20m, despite its age, remains competitive in average score due to the Vulkan result, but its higher power requirements and missing outputs limit its appeal. The database suggests neither card is universally superior; the choice depends on whether the workload favors Vulkan (Tesla K20m) or OpenCL and newer API features (T400).