NVIDIA Quadro 6000 vs NVIDIA Tesla C2075 Comparison

The NVIDIA Tesla C2075 and NVIDIA Quadro 6000 are both professional-grade Fermi architecture cards from NVIDIA, but they are engineered for distinctly different roles. The data shows the Tesla C2075 is designed for compute acceleration, while the Quadro 6000 is built for professional visualization and content creation. Despite sharing the same fundamental silicon heritage, their benchmark scores, feature sets, and physical specifications reveal a clear separation of purpose. The Tesla C2075 posts a Geekbench OpenCL score of 10,400, significantly ahead of the Quadro 6000’s 9,846, but the Quadro counters with a broader display output configuration and a lower thermal envelope.

FAQ

Q: Which card has a higher OpenCL benchmark score?

A: The NVIDIA Tesla C2075 leads with a Geekbench OpenCL score of 10,400, while the NVIDIA Quadro 6000 trails at 9,846. This gives the Tesla a 5.6% performance advantage in this compute-oriented workload.

Q: Do both cards have the same memory capacity and type?

A: Yes, both cards feature 6 GB of GDDR5 memory on a 384-bit bus. However, the Tesla C2075 has a higher memory clock at 783 MHz (3.1 Gbps effective) and greater bandwidth at 150.3 GB/s, compared to the Quadro 6000’s 747 MHz (3 Gbps effective) and 143.4 GB/s.

Q: What are the key architectural differences between the two chips?

A: The Tesla C2075 uses the GF110 chip based on the newer "Fermi 2.0" architecture, while the Quadro 6000 uses the GF100 chip based on the original "Fermi" architecture. Both have 448 shading units, 56 TMUs, and 48 ROPs, but they differ in transistor count and die size.

Q: Which card offers more display outputs?

A: The NVIDIA Quadro 6000 offers significantly more display outputs: 1x DVI, 2x DisplayPort, and 1x S-Video. The Tesla C2075 is limited to a single DVI output, reflecting its compute-first design.

Q: What is the thermal design power (TDP) difference between the two cards?

A: The Tesla C2075 has a higher TDP of 247 W, while the Quadro 6000 consumes less at 204 W. Both require the same suggested power supply of 550 W and use identical power connectors (1x 6-pin + 1x 8-pin).

Q: How do the cards compare in terms of physical size?

A: Both cards are dual-slot designs with a length of 248 mm (9.8 inches). The Quadro 6000 has a specified height of 111 mm (4.4 inches), while the Tesla C2075 does not list a height specification.

Architecture Differences

The fundamental architectural split between these two cards is defined by their chips. The Tesla C2075 is built on the GF110 chip, which NVIDIA designates as "Fermi 2.0," while the Quadro 6000 uses the GF100 chip, part of the original "Fermi" architecture. This is not a trivial naming difference; it represents a revision of the underlying design. Both are manufactured on the same 40 nm process at TSMC, but the GF110 packs 3,000 million transistors on a 520 mm² die, while the GF100 contains 3,100 million transistors on a slightly larger 529 mm² die. This results in a marginally higher transistor density of 5.9M / mm² for the Quadro versus 5.8M / mm² for the Tesla.

In terms of compute resources, the two cards are surprisingly similar. Both feature 448 shading units, 56 texture mapping units (TMUs), and 48 render output units (ROPs). The pixel rate and texture rate are identical at 16.07 GPixel/s and 32.14 GTexel/s, respectively. The FP32 performance is also exactly the same at 1,027.7 GFLOPS. Neither card supports FP16 arithmetic, and neither has dedicated ray tracing or tensor cores. The API support is also identical, with both offering DirectX 12 (11_0) and OpenGL 4.6, but no Vulkan support.

The memory subsystems differ subtly. The Tesla C2075 runs its GDDR5 memory at 783 MHz (3.1 Gbps effective) and achieves 150.3 GB/s bandwidth, while the Quadro 6000 runs at 747 MHz (3 Gbps effective) with 143.4 GB/s bandwidth. Both use a 384-bit bus interface. The memory clock difference is modest but contributes to the Tesla’s benchmark advantage. The interface is PCIe 2.0 x16 for both cards. The Tesla is classified as part of the Tesla Fermi (x20xx) generation, while the Quadro belongs to the Quadro Fermi (x000) generation.

Head-to-Head Benchmarks

The only direct benchmark comparison available is the Geekbench OpenCL test, where the Tesla C2075 decisively wins. The Tesla scores 10,400 points, while the Quadro 6000 scores 9,846 points, resulting in a 5.6% delta in favor of the Tesla. This score is a strong indicator of raw compute throughput, which aligns with the Tesla’s intended role as a general-purpose GPU for scientific and data-parallel workloads. The 5.6% advantage is not overwhelming, but it is consistent across the memory and clock improvements found in the GF110 chip.

Contextualizing the scores against their nearest rivals provides additional insight. The Tesla C2075’s score of 10,400 places it in the 48th percentile of all GPUs. Its closest competitor is the AMD Radeon RX 550X, which scores 10,481 (a -0.8% delta), while the AMD Radeon RX 6500M is nearly tied at 10,362 (a 0.4% delta). The Tesla also edges out the NVIDIA GeForce GTX 950A (10,273) by 1.2%. This means the Tesla is competitive with mid-range mobile and entry-level desktop GPUs from the same era, despite its professional positioning.

The Quadro 6000, with its 9,846 score, sits at the 47th percentile of all GPUs. Its nearest rival is the NVIDIA Quadro M2000M, which scores 9,832 (a 0.1% delta), followed by the AMD FirePro W5000 at 9,803 (a 0.4% delta). The Quadro 6000 edges out the NVIDIA GeForce GTX 1070 (9,780) by 0.7% but trails the NVIDIA GeForce GTX 870M (9,959) by -1.1%. This shows the Quadro 6000 is competitive with a broad range of professional and consumer cards, but it is clearly behind the Tesla in raw compute performance.

Specification Differences

When comparing the two cards side-by-side, the specification deltas are concentrated in a few key areas. The chip and architecture are the most significant difference: GF110 (Fermi 2.0) for the Tesla versus GF100 (Fermi) for the Quadro. This is accompanied by a small reduction in transistor count for the Tesla (3,000 million vs. 3,100 million) and a correspondingly smaller die size (520 mm² vs. 529 mm²).

The memory clocks differ, with the Tesla running at 783 MHz (3.1 Gbps effective) versus the Quadro’s 747 MHz (3 Gbps effective). This produces a bandwidth advantage for the Tesla: 150.3 GB/s versus 143.4 GB/s. The TDP also varies, with the Tesla drawing 247 W and the Quadro drawing 204 W. This is a substantial 43 W difference, which is noteworthy for system integration and cooling requirements.

The display outputs are a major point of divergence. The Tesla C2075 offers only a single DVI port, while the Quadro 6000 provides 1x DVI, 2x DisplayPort, and 1x S-Video. This makes the Quadro the clear choice for multi-monitor professional workstations. The Quadro also has a specified height of 111 mm (4.4 inches), whereas the Tesla does not list a height. Both cards are dual-slot, measure 248 mm in length, and require a 550 W power supply with 1x 6-pin + 1x 8-pin connectors. The release dates are also different: the Quadro 6000 launched on December 9, 2010, while the Tesla C2075 followed on July 24, 2011.

Where Each One Wins

The data paints a clear picture of distinct use cases. The NVIDIA Tesla C2075 wins in pure compute performance, as evidenced by its 5.6% higher Geekbench OpenCL score. This makes it the superior choice for GPU-accelerated compute tasks such as scientific simulation, machine learning inference, and other data-parallel workloads where raw FP32 throughput (1,027.7 GFLOPS) and memory bandwidth (150.3 GB/s) are paramount. Its higher TDP of 247 W is a trade-off for that performance, but in a server or dedicated compute node, that thermal headroom is often acceptable. The Tesla’s single DVI output reinforces its role as a headless compute accelerator rather than a display adapter.

The NVIDIA Quadro 6000, while slightly slower in compute, wins decisively in workstation flexibility. Its 204 W TDP makes it easier to cool and integrate into a professional workstation chassis. More importantly, its display output configuration — 1x DVI, 2x DisplayPort, and 1x S-Video — supports multi-monitor setups that are essential for CAD, 3D modeling, and video editing workflows. While its Geekbench score of 9,846 is lower, it still competes well against its nearest rivals, sitting just 0.1% behind the Quadro M2000M and 0.4% behind the FirePro W5000. For a professional who needs both OpenGL 4.6 acceleration and multiple display outputs, the Quadro 6000 is the more practical choice.

The benchmark data indicates the Tesla C2075 is the compute specialist, while the Quadro 6000 is the visualization generalist. In a head-to-head compute benchmark, the Tesla wins outright. In a real-world workstation environment requiring visual output, the Quadro’s feature set gives it an advantage that no benchmark score can capture. The choice between them should be driven by the primary workload: raw number-crunching favors the Tesla, while interactive graphics and multi-monitor productivity favor the Quadro.