AMD Radeon PRO W6800 vs NVIDIA Tesla T4 Comparison

The Verdict

The data presents a clear performance hierarchy between these two end-of-life workstation and server GPUs. The AMD Radeon PRO W6800 holds a decisive advantage in every recorded benchmark, with its average benchmark score of 135396 placing it in the 96th percentile of all GPUs, while the NVIDIA Tesla T4 achieves an average of 66733, landing in the 90th percentile. The W6800 leads by a substantial 98.8% in Geekbench OpenCL (121808 versus 61276) and by 52.3% in Geekbench Vulkan (109961 versus 72190). For users prioritizing raw compute throughput, the W6800 is the obvious selection.

However, the Tesla T4 is not without purpose. Its 70 W TDP and single-slot design, with no power connectors, make it suitable for dense server deployments where thermal and space constraints dominate. The T4 also brings 320 tensor cores, a feature absent from the AMD part, which matters for workloads that rely on tensor operations. The verdict from the database: choose the W6800 for maximum compute performance and display output capability, choose the T4 for low-power, accelerator-centric server roles where its smaller footprint and tensor core support are the deciding factors.

FAQ

Q: Which GPU has the higher average benchmark score?

A: The AMD Radeon PRO W6800 records an average benchmark score of 135396, while the NVIDIA Tesla T4 averages 66733. This places the W6800 in the 96th percentile of all GPUs, versus the T4's 90th percentile.

Q: How large is the performance gap in the head-to-head tests?

A: In Geekbench OpenCL, the W6800 scores 121808 against the T4's 61276, a delta of 98.8%. In Geekbench Vulkan, the W6800 scores 109961 against 72190, a delta of 52.3%. The W6800 wins both recorded head-to-head benchmarks.

Q: Does the NVIDIA Tesla T4 have any unique hardware features?

A: Yes, the T4 includes 320 tensor cores, which are not present on the AMD Radeon PRO W6800. This is a notable architectural distinction for AI-related workloads.

Q: What are the power requirements for each card?

A: The AMD Radeon PRO W6800 has a TDP of 250 W and requires a 600 W suggested PSU, with 1x 6-pin and 1x 8-pin power connectors. The NVIDIA Tesla T4 has a TDP of 70 W, requires a 250 W suggested PSU, and has no power connectors.

Q: Which card supports display outputs?

A: The AMD Radeon PRO W6800 has 6x mini-DisplayPort 1.4a outputs. The NVIDIA Tesla T4 has no display outputs, indicating it is designed as a compute-only accelerator.

Q: What is the release timeline for these products?

A: The AMD Radeon PRO W6800 was released on 2021-06-07, while the NVIDIA Tesla T4 was released earlier on 2018-09-12. Both are marked as end-of-life in the database.

Architecture Differences

The two GPUs come from different architectural lineages and manufacturing nodes. The AMD Radeon PRO W6800 is built on RDNA 2.0 architecture, fabricated on a 7 nm process at TSMC. Its chip, Navi 21, contains 26,800 million transistors on a 520 mm² die, yielding a transistor density of 51.5 million per mm². The NVIDIA Tesla T4 uses the Turing architecture, manufactured on a 12 nm process at TSMC. Its TU104 chip houses 13,600 million transistors on a 545 mm² die, resulting in a lower density of 25.0 million per mm². The node advantage is clear: the W6800 packs nearly twice the transistors in a slightly smaller die.

Compute resource allocation also differs significantly. The W6800 has 3840 shading units, 240 texture mapping units, and 96 ROPs, plus 60 ray tracing cores. The T4 has 2560 shading units, 160 TMUs, and 64 ROPs, with 40 ray tracing cores but adds 320 tensor cores. The presence of tensor cores on the T4 is the most striking architectural divergence, as the W6800 has no equivalent hardware. This suggests the T4 was designed with inference or tensor-based workloads in mind, while the W6800 focuses on traditional rasterization and compute.

Both cards support the same API set: DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4. However, the underlying implementations differ due to the respective architectures. The W6800's RDNA 2.0 design emphasizes higher clock speeds and efficiency per watt, while the T4's Turing architecture prioritizes versatility with tensor cores and lower power draw. The manufacturing process gap (7 nm versus 12 nm) likely contributes to the W6800's higher density and performance potential.

Specification Differences

The specification sheets reveal distinct design philosophies. Memory capacity is a major split: the W6800 offers 32 GB of GDDR6 on a 256-bit bus, delivering 512.0 GB/s bandwidth, while the T4 provides 16 GB of GDDR6 on the same 256-bit bus but with 320.0 GB/s bandwidth. The W6800's memory clock is 2000 MHz (16 Gbps effective), versus the T4's 1250 MHz (10 Gbps effective). This doubling of capacity and 60% higher bandwidth gives the W6800 a clear advantage in memory-bound workloads.

Clock speeds also diverge sharply. The W6800 runs at a base of 1575 MHz and boosts to 2322 MHz, while the T4 operates at a base of 585 MHz and boosts to 1590 MHz. The result is a large gap in compute throughput: the W6800 delivers 17.83 TFLOPS FP32 and 35.67 TFLOPS FP16 (2:1), while the T4 manages 8.141 TFLOPS FP32 and 16.28 TFLOPS FP16 (2:1). Pixel and texture rates follow the same pattern: 222.9 GPixel/s and 557.3 GTexel/s for the W6800, versus 101.8 GPixel/s and 254.4 GTexel/s for the T4.

Physical and power specifications further separate the two. The W6800 is a dual-slot card measuring 267 mm in length, 120 mm in height, and 50 mm in width, with a TDP of 250 W and a suggested PSU of 600 W. The T4 is a single-slot card at 168 mm in length, with no listed height or width, a TDP of 70 W, and a suggested PSU of 250 W. The T4 has no power connectors, while the W6800 needs 1x 6-pin and 1x 8-pin. Bus interfaces also differ: the W6800 uses PCIe 4.0 x16, the T4 uses PCIe 3.0 x16. Display outputs are exclusive to the W6800 (6x mini-DisplayPort 1.4a), as the T4 has none.

Head-to-Head Benchmarks

The database records two head-to-head comparisons, and the AMD Radeon PRO W6800 wins both. In Geekbench OpenCL, the W6800 scores 121808 against the T4's 61276, a delta of 98.8%. This near-doubling of performance is consistent with the FP32 throughput gap: 17.83 TFLOPS versus 8.141 TFLOPS. The W6800 effectively delivers nearly twice the raw compute in this API, which aligns with its higher shading unit count and clock speeds.

In Geekbench Vulkan, the W6800 scores 109961 versus 72190, a delta of 52.3%. The margin narrows compared to OpenCL, but the W6800 still maintains a commanding lead. The T4's Vulkan score of 72190 is actually higher than its OpenCL score of 61276, suggesting the Turing architecture handles Vulkan more efficiently relative to its own baseline. Yet the W6800's Vulkan performance remains far ahead in absolute terms.

The overall benchmark averages reinforce this pattern. The W6800's average of 135396 sits within 0.1% of the NVIDIA A10M (135230) and the NVIDIA RTX 4000 Ada Generation (135218), and it is 0.3% behind the AMD Radeon Pro W6800X Duo (135774) and 0.8% behind the AMD Radeon PRO V620 (136472). The T4's average of 66733 is 1.1% ahead of the AMD Radeon VII (66004) and 2.5% ahead of the NVIDIA Tesla P40 (65095), but 2.7% behind the AMD Radeon Instinct MI25 (68562) and 3% behind the Intel Arc A770 (68809). These rival positions show that the W6800 competes in the upper tier of workstation GPUs, while the T4 sits in a lower performance bracket despite its tensor core advantage.

Where Each One Wins

The AMD Radeon PRO W6800 wins on every measurable compute benchmark in this comparison. Its 98.8% lead in OpenCL and 52.3% lead in Vulkan, combined with double the memory capacity (32 GB versus 16 GB) and 60% higher bandwidth (512.0 GB/s versus 320.0 GB/s), make it the clear choice for compute-heavy tasks such as rendering, simulation, or large dataset processing. The presence of six display outputs also means it can drive multi-monitor workstation setups directly, something the T4 cannot do at all.

The NVIDIA Tesla T4 wins on power efficiency and form factor. At 70 W TDP with no power connectors, it draws less than a third of the W6800's 250 W and fits in a single slot at 168 mm length, versus the W6800's dual-slot, 267 mm footprint. For server environments where power density and physical space are premium, the T4 is the more practical accelerator. Its 320 tensor cores provide a hardware capability absent from the W6800, which could be decisive for workloads that specifically leverage tensor operations. The T4's suggested PSU of 250 W also means it can slot into systems with modest power delivery, while the W6800 demands a 600 W PSU.

The performance data, however, is unambiguous: in the recorded benchmarks, the W6800 outperforms the T4 by a wide margin. Users who need maximum compute throughput and can accommodate the larger card should select the W6800. Users who prioritize low power, compact size, and tensor core support in a server context should consider the T4, accepting a significant compute penalty in exchange for those operational advantages.