GPU Comparison

The NVIDIA Tesla C2070 and NVIDIA Quadro P4000 represent two distinct eras of professional GPU design, separated by nearly six years of architectural evolution. While both cards target workstation and datacenter workloads, the benchmark data reveals a decisive generational gap in raw compute performance, with the newer Pascal-based Quadro P4000 delivering a commanding lead over the Fermi-based Tesla C2070 in the available OpenCL test.

Head-to-Head Benchmarks

The head-to-head comparison in the the benchmark database contains a single benchmark result, but it is a decisive one. In the Geekbench OpenCL test, the NVIDIA Quadro P4000 scores 36,212 points, while the NVIDIA Tesla C2070 manages only 9,716 points. This represents a delta of -73.2% for the Tesla C2070, meaning the Quadro P4000 is roughly 3.7 times faster in this compute-oriented workload. The scale of this victory is not incremental; it is a complete overhaul of compute capability.

The Tesla C2070’s score of 9,716 places it in the 47th percentile of all GPUs, a middling position that reflects its 2011 origins. Its nearest rival, the NVIDIA Tesla M10, scores 9,724, a negligible 0.1% difference, indicating that the C2070 is essentially performance-parity with that later entry-level datacenter card. Interestingly, the C2070 is 0.5% ahead of the Quadro P4000’s average score of 9,665 when the P4000 is placed in the C2070’s rival list, but this is a statistical artifact of comparing the C2070’s single OpenCL score against the P4000’s multi-benchmark average, which includes much slower DirectX and Passmark tests.

For the Quadro P4000, its 36,212 OpenCL score is a standout figure within its own benchmark suite. Its other results, such as 1,115 in 3DMark Steel Nomad DX12, 11,466 in Passmark G3D, and 4,913 in Passmark GPU Compute, are all respectable for a professional card, but the OpenCL score is clearly its strongest compute showing. The P4000’s nearest rival, the AMD Radeon Pro WX 2100, posts an average score of 9,653, which is 0.1% behind the P4000’s overall average of 9,665. This demonstrates that while the P4000 dominates the older Tesla in raw compute, it is far from the top of the professional GPU hierarchy when averaged across all tests.

FAQ

Q: Which card is faster in the Geekbench OpenCL benchmark?

A: The NVIDIA Quadro P4000 is overwhelmingly faster, scoring 36,212 compared to the Tesla C2070’s 9,716, a 73.2% advantage for the P4000.

Q: What is the average benchmark score for each card?

A: The Tesla C2070 has an average benchmark score of 9,716, derived solely from its OpenCL result. The Quadro P4000 has an average score of 9,665, which is the mean of its ten different benchmark results, including the high OpenCL score and lower DirectX and Passmark scores.

Q: How do these cards compare to their nearest rivals?

A: The Tesla C2070 is 0.1% behind the NVIDIA Tesla M10 (9,724 vs 9,716) and 0.5% ahead of the Quadro P4000’s average (9,665). The Quadro P4000 is 0.1% ahead of the AMD Radeon Pro WX 2100 (9,665 vs 9,653) and 0.2% ahead of the NVIDIA GeForce GTX 960M (9,645).

Q: What is the production status of these GPUs?

A: Both the NVIDIA Tesla C2070 and the NVIDIA Quadro P4000 are marked as end-of-life products in the data.

Q: Which card supports the Vulkan API?

A: The Quadro P4000 supports Vulkan version 1.4, while the Tesla C2070 does not list any Vulkan support in its API specifications.

Q: What is the launch MSRP of the Quadro P4000?

A: The Quadro P4000 has a launch MSRP of 815 USD. The Tesla C2070 does not have a listed launch MSRP in the data.

Architecture Differences

The two cards are built on fundamentally different architectures that highlight the rapid pace of GPU development. The Tesla C2070 uses the GF100 chip based on the Fermi architecture, fabricated on a 40 nm process at TSMC. This older design packs 3,100 million transistors onto a large 529 mm² die, yielding a transistor density of 5.9 million transistors per square millimeter. Fermi was NVIDIA’s first architecture to fully support compute capabilities like ECC memory and error correction, but its 40 nm node and complex design limited clock speeds and efficiency.

In contrast, the Quadro P4000 utilizes the GP104 chip based on the Pascal architecture, also built by TSMC but on a much more advanced 16 nm process. This node shrink allows the P4000 to cram 7,200 million transistors onto a smaller 314 mm² die, achieving a transistor density of 22.9 million per square millimeter, nearly four times higher than the Fermi design. Pascal introduced significant improvements in memory compression, simultaneous multi-projection, and asynchronous compute, all of which contribute to its superior performance.

The API support also diverges sharply. The Tesla C2070 supports DirectX 12 (11_0) and OpenGL 4.6, but lacks Vulkan support entirely. The Quadro P4000 supports DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.4, making it compatible with a broader range of modern applications and game engines. The lack of Vulkan on the Tesla is a notable limitation, as that API has become standard for cross-platform compute and graphics workloads.

Specification Differences

The specification sheets for these two cards reveal dramatic differences across nearly every metric. The Tesla C2070 features 448 shading units, 56 texture mapping units, and 48 raster output units. The Quadro P4000, by contrast, offers 1,792 shading units, 112 TMUs, and 64 ROPs, quadruple the shading units and double the texture units. This massive increase in parallel processing resources is the primary driver behind the P4000’s superior compute scores.

Memory configurations also differ substantially. The Tesla C2070 has 6 GB of GDDR5 memory on a 384-bit bus, delivering a bandwidth of 143.4 GB/s and a memory clock of 747 MHz (3 Gbps effective). The Quadro P4000 has 8 GB of GDDR5 on a narrower 256-bit bus, but its much faster memory clock of 1901 MHz (7.6 Gbps effective) results in a higher bandwidth of 243.3 GB/s. The P4000 also has a higher pixel rate (94.72 GPixel/s vs 16.07 GPixel/s) and texture rate (165.8 GTexel/s vs 32.14 GTexel/s), indicating faster rasterization and texturing capabilities.

The compute throughput gap is stark. The Tesla C2070 delivers 1,027.7 GFLOPS of FP32 performance, while the Quadro P4000 achieves 5.304 TFLOPS, over five times higher. The P4000 also lists a low FP16 rate of 82.88 GFLOPS (1:64), whereas the Tesla has no FP16 figure listed. Physical and power characteristics differ as well: the Tesla is a dual-slot card with a 238 W TDP, requiring a 550 W power supply and both a 6-pin and 8-pin connector. The Quadro P4000 is a single-slot card with a 105 W TDP, a 300 W suggested PSU, and only a single 6-pin connector.

Connectivity and display outputs also favor the newer card. The Tesla C2070 uses a PCIe 2.0 x16 interface and has just a single DVI output. The Quadro P4000 uses the faster PCIe 3.0 x16 interface and offers four DisplayPort 1.4a outputs, making it far more suitable for multi-monitor professional setups. The Tesla is longer at 248 mm (9.8 inches) compared to the P4000’s 241 mm (9.5 inches), and the P4000 also has a listed height of 111 mm (4.4 inches).

Where Each One Wins

The Quadro P4000 wins in essentially every measurable category, making it the clear choice for any modern workload. Its 73.2% lead in OpenCL compute makes it the superior option for GPU-accelerated rendering, scientific simulation, and machine learning inference tasks that rely on raw FP32 throughput. The 8 GB memory capacity and 243.3 GB/s bandwidth also give it an edge in handling large datasets or high-resolution textures without swapping to system memory. Its support for Vulkan 1.4 and DirectX 12 (12_1) ensures compatibility with current software stacks, while the four DisplayPort outputs make it ideal for multi-display engineering or design workstations. The lower 105 W TDP and single-slot form factor also mean it can be deployed in denser systems with less power and cooling overhead.

The Tesla C2070, despite its age, retains a narrow niche in legacy environments. Its 6 GB of memory and 384-bit bus offer respectable bandwidth for its era, and its 1,027.7 GFLOPS of FP32 compute is still sufficient for older CUDA-based applications that have not been updated for newer architectures. Its end-of-life status and lack of Vulkan support, however, severely limit its future-proofing. In a straight comparison, the Tesla C2070’s only statistical claim is its 0.5% lead over the Quadro P4000’s average score in the rival list, but that is an artifact of averaging, not a real performance advantage. For any user choosing between these two cards today, the data unequivocally favors the Quadro P4000.