NVIDIA T1000 vs NVIDIA Tesla P4 Comparison

The NVIDIA Tesla P4 and NVIDIA T1000 are two very different professional graphics cards, separated by a generation and aimed at different workloads. The Tesla P4 is a Pascal-era compute accelerator with a massive shader count, while the T1000 is a Turing-era workstation card with a focus on efficiency and modern display output. Benchmark data shows a clear split: the T1000 takes the lead in OpenCL compute, while the Tesla P4 dominates in Vulkan graphics performance.

Head-to-Head Benchmarks

The two cards split their benchmark wins evenly, with each taking a decisive victory in a different API. In the Geekbench OpenCL test, the NVIDIA T1000 scores 37,704 points, which is 7.3% higher than the Tesla P4’s 34,947 points. This is a significant margin in a compute-oriented workload, and it aligns with the T1000’s newer architecture and higher boost clock. The T1000’s average benchmark score of 36,289 places it in the 80th percentile of all GPUs, putting it in the same performance tier as the AMD Radeon RX 5300M, which scores 36,529 (a 0.7% difference), and the NVIDIA GeForce GTX TITAN X at 36,530 (also 0.7% off).

The tables turn completely in the Geekbench Vulkan test. Here, the Tesla P4 posts a commanding 40,309 points, beating the T1000’s 34,874 by a substantial 15.6%. This is the Tesla P4’s strongest showing, and it pushes the card’s average benchmark score to 37,628, putting it in the 81st percentile of all GPUs. That average score puts it in rarefied air, essentially tied with the NVIDIA GeForce RTX 4070, which scores 37,648 (a mere 0.1% difference), and slightly ahead of the AMD Radeon RX Vega 56 at 37,507 (0.3% higher for the P4).

The key takeaway from these head-to-head results is that the Tesla P4 is a graphics powerhouse in Vulkan-based applications, while the T1000 offers superior raw compute throughput in OpenCL. The 15.6% win for the Tesla P4 is the largest margin in either direction, making it the clear victor in that specific scenario. Conversely, the T1000’s 7.3% OpenCL advantage is more modest but still represents a definitive win for compute tasks. The data does not show a single overall winner; instead, it reveals a card that is better suited for different types of workloads.

The Verdict

The choice between these two cards hinges entirely on the application workload. For users running OpenCL-based compute tasks, the NVIDIA T1000 is the better option. Its 7.3% lead in the Geekbench OpenCL benchmark, coupled with its higher boost clock of 1395 MHz, indicates a more efficient compute pipeline. The T1000’s average score of 36,289 also puts it within striking distance of much more expensive hardware, like the NVIDIA Quadro GV100, which scores 35,520 (2.2% lower). This makes the T1000 a surprisingly capable compute card for its size.

However, for any workload that leverages Vulkan, the NVIDIA Tesla P4 is the definitive choice. The 15.6% lead in the Vulkan benchmark is not a marginal difference; it is a decisive generational gap in graphics throughput. The Tesla P4’s average score of 37,628 places it in the 81st percentile, matching the performance of the GeForce RTX 4070 in this aggregate metric. This suggests that for graphics-intensive rendering or compute tasks that use Vulkan, the older Pascal card is the superior performer.

The data does not support a single recommendation for all users. Instead, it points to a binary choice. Pick the T1000 for OpenCL-driven workloads like scientific computing, data analytics, or any CUDA-based task that relies on OpenCL. Pick the Tesla P4 for Vulkan-based rendering, game development, or any application that can take advantage of its superior graphics rasterization. The T1000 is the more modern card with a higher clock speed, but the Tesla P4’s sheer shader count (2560 vs 896) gives it an insurmountable lead in Vulkan.

Architecture Differences

The two cards are built on fundamentally different architectures, which explains their divergent benchmark results. The Tesla P4 is based on the Pascal architecture, manufactured on a 16 nm process at TSMC. Its chip, the GP104, contains 7,200 million transistors on a 314 mm² die, resulting in a transistor density of 22.9M per mm². The T1000, in contrast, is a Turing-generation part, built on TSMC’s 12 nm node. Its TU117 chip packs 4,700 million transistors into a smaller 200 mm² die, giving it a higher density of 23.5M per mm².

The Pascal card is a brute-force design. It features 2560 shading units, 160 texture mapping units, and 64 ROPs. This hardware configuration delivers a pixel rate of 71.30 GPixel/s and a texture rate of 178.2 GTexel/s. Its FP32 compute throughput is rated at 5.704 TFLOPS, but its FP16 performance is a paltry 89.12 GFLOPS, reflecting a 1:64 ratio that makes it practically useless for half-precision work. The T1000, by comparison, has a much leaner setup with 896 shading units, 56 TMUs, and 32 ROPs. Its pixel rate is 44.64 GPixel/s and its texture rate is 78.12 GTexel/s. Its FP32 performance is 2.500 TFLOPS, but it shines in FP16 with 5.000 TFLOPS, thanks to a 2:1 ratio that effectively doubles its throughput for supported workloads.

Memory configurations also differ significantly. The Tesla P4 uses 8 GB of GDDR5 on a 256-bit bus, yielding a bandwidth of 192.3 GB/s. The T1000 has 4 GB of GDDR6 on a narrower 128-bit bus, resulting in 160.0 GB/s of bandwidth. While the T1000’s memory is faster in terms of effective speed (10 Gbps vs 6 Gbps), the P4’s wider bus and larger capacity provide more total bandwidth and headroom for large datasets. The T1000 compensates with a higher boost clock of 1395 MHz compared to the P4’s 1114 MHz, but the P4’s raw hardware resources dominate in graphics-heavy tasks.

Both cards share the same API support, including DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.4. However, the display outputs tell a different story. The T1000 has 4x mini-DisplayPort 1.4a outputs, making it a functional workstation card for multi-monitor setups. The Tesla P4 has no display outputs whatsoever, confirming its role as a dedicated compute accelerator for servers or datacenter environments. The T1000 also draws less power with a 50 W TDP versus the P4’s 75 W, though both require a 250 W suggested PSU and use no external power connectors.

FAQ

Q: Which card is faster in OpenCL workloads?

A: The NVIDIA T1000 is faster, scoring 37,704 points in the Geekbench OpenCL benchmark compared to the Tesla P4’s 34,947 points, a 7.3% advantage.

Q: Which card has better Vulkan performance?

A: The NVIDIA Tesla P4 dominates in Vulkan, scoring 40,309 points versus the T1000’s 34,874 points, representing a 15.6% lead for the Pascal card.

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

A: The Tesla P4 has 8 GB of GDDR5 memory on a 256-bit bus, while the T1000 has 4 GB of GDDR6 on a 128-bit bus. The P4’s memory bandwidth is 192.3 GB/s, whereas the T1000 offers 160.0 GB/s.

Q: Can the Tesla P4 be used for display output?

A: No, the Tesla P4 has no display outputs. The T1000, however, includes 4x mini-DisplayPort 1.4a outputs for multi-monitor configurations.

Q: How do these cards compare to their nearest rivals in average benchmark score?

A: The Tesla P4’s average score of 37,628 is nearly identical to the NVIDIA GeForce RTX 4070 (37,648, a 0.1% difference) and slightly ahead of the AMD Radeon RX Vega 56 (37,507, a 0.3% difference). The T1000’s average of 36,289 is just behind the AMD Radeon RX 5300M (36,529, a 0.7% difference) and ahead of the NVIDIA Quadro GV100 (35,520, a 2.2% difference).

Q: What are the FP16 compute capabilities of each card?

A: The T1000 offers robust FP16 performance at 5.000 TFLOPS (2:1 ratio), while the Tesla P4’s FP16 throughput is severely limited at 89.12 GFLOPS (1:64 ratio). This makes the T1000 vastly superior for half-precision compute tasks.

Where Each One Wins

NVIDIA Tesla P4: This card wins decisively in Vulkan-based graphics applications. The 15.6% lead in the Geekbench Vulkan test over the T1000 is its strongest argument, and its overall average score of 37,628 places it in the 81st percentile of all GPUs, tying it with the GeForce RTX 4070. The P4’s massive 2560 shading units and 8 GB of VRAM make it the clear pick for rendering pipelines, game development, or any workload that is graphics-bound. It is also the better choice for scenarios requiring more than 4 GB of memory, as its larger frame buffer and wider 256-bit bus provide superior memory bandwidth (192.3 GB/s) for large textures and datasets.

NVIDIA T1000: The T1000 is the winner in OpenCL compute workloads, as evidenced by its 7.3% lead in that benchmark. Its higher boost clock of 1395 MHz and efficient Turing architecture deliver better raw compute throughput per watt. The T1000’s FP16 performance is a standout feature, delivering 5.000 TFLOPS versus the P4’s 89.12 GFLOPS, making it the only viable choice for half-precision machine learning or scientific applications. It is also the only card with display outputs, featuring 4x mini-DisplayPort 1.4a, making it suitable for workstation use with multiple monitors. Its lower 50 W TDP makes it easier to cool and integrate into compact systems. For users who need a functional desktop card with modern compute features, the T1000 is the superior option.