NVIDIA GeForce GTX 870M vs NVIDIA Tesla C2070 Comparison

The NVIDIA GeForce GTX 870M and NVIDIA Tesla C2070 represent two distinct eras of GPU design, pitting a mobile Kepler part against a workstation-focused Fermi behemoth. The data reveals a decisive performance gap in favor of the newer chip, but the comparison is far more nuanced than a simple scoreboard, as architectural philosophies and physical specifications diverge sharply. The benchmark results, while limited to a single shared test, offer a clear starting point for understanding where each card excels and, more importantly, why.

Head-to-Head Benchmarks

The only common benchmark between the two GPUs is Geekbench OpenCL, and the results are unequivocal. The GeForce GTX 870M scores 12,630, while the Tesla C2070 manages 9,716. This translates to a 30% advantage for the GTX 870M in this compute workload. This is not a marginal victory; it is a substantial lead that places the mobile chip in a different performance tier for this specific test. To put the GTX 870M’s score in perspective, its average benchmark score of 9,959 places it at the 48th percentile of all GPUs, just 0.5% behind the AMD Radeon Pro 5300M and 0.8% behind the NVIDIA Quadro K5100M. Meanwhile, the Tesla C2070’s score of 9,716 sits at the 47th percentile, making it nearly identical in average performance to the NVIDIA Tesla M10 (0.1% behind) and only 0.5% ahead of the NVIDIA Quadro P4000. The head-to-head delta of 30% is the single most important data point here, showing that in raw OpenCL compute, the GTX 870M is not just faster, but significantly so. The data implies that the architectural advancements in Kepler, specifically its higher shading unit count and clock speeds, provide a massive advantage over the older Fermi design in this particular workload, despite the Tesla’s larger memory bus and frame buffer.

The Verdict

From the data, the choice is clear for compute-oriented tasks: the GeForce GTX 870M is the superior performer. It wins the only head-to-head benchmark by a 30% margin. The data shows the GTX 870M offers a 30% performance increase in OpenCL, which is a strong indicator of general compute capability. Furthermore, the GTX 870M achieves this with a significantly lower thermal design power (TDP) of 100 W compared to the Tesla C2070’s 238 W, suggesting far better efficiency. The Tesla C2070, while having more memory (6 GB vs 3 GB) and a wider memory bus (384 bit vs 192 bit), does not translate that into compute performance in this test. The Verdict for a user prioritizing compute benchmarks is straightforward: the GTX 870M is the better choice. The Tesla C2070’s only potential advantage lies in its larger memory capacity, which could be relevant for specific workloads that require more than 3 GB of data to be resident on the GPU. However, based strictly on the benchmark data, the GTX 870M is the definitive winner.

FAQ

Q: Which GPU has the higher benchmark score in the Geekbench OpenCL test?

A: The NVIDIA GeForce GTX 870M scores 12,630, which is 30% higher than the NVIDIA Tesla C2070’s score of 9,716.

Q: How does the GTX 870M compare to its nearest rivals in average performance?

A: The GTX 870M has an average benchmark score of 9,959, which is 0.5% behind the AMD Radeon Pro 5300M (10,013) and 1.1% behind the AMD Radeon R9 M375 (10,070).

Q: What is the performance percentile of the Tesla C2070 compared to all other GPUs?

A: The Tesla C2070 is at the 47th percentile of all GPUs, with an average benchmark score of 9,716.

Q: Does the Tesla C2070 have a higher texture fill rate than the GTX 870M?

A: No. The GTX 870M has a texture rate of 108.3 GTexel/s, while the Tesla C2070 has a much lower texture rate of 32.14 GTexel/s.

Q: What is the difference in power consumption between the two cards?

A: The GeForce GTX 870M has a TDP of 100 W, while the Tesla C2070 has a TDP of 238 W, making the Tesla significantly more power-hungry.

Specification Differences

The specifications of these two GPUs differ in almost every key metric. The GeForce GTX 870M features 1,344 shading units, 112 texture mapping units (TMUs), and 24 ROPs. In contrast, the Tesla C2070 has 448 shading units, 56 TMUs, and 48 ROPs. This means the GTX 870M has three times the shading units and double the TMUs, while the Tesla has double the ROPs. Clock speeds also differ drastically. The GTX 870M has a base clock of 941 MHz and a boost clock of 967 MHz, while the Tesla C2070 has no listed base or boost clock. The memory configurations are also distinct: the GTX 870M has 3 GB of GDDR5 on a 192-bit bus with a bandwidth of 120.0 GB/s, while the Tesla C2070 has 6 GB of GDDR5 on a 384-bit bus with a bandwidth of 143.4 GB/s. The Tesla’s memory clock is 747 MHz (3 Gbps effective), whereas the GTX 870M’s is 1250 MHz (5 Gbps effective). The power requirements are polar opposites: the GTX 870M is a 100 W MXM module with no power connectors, while the Tesla C2070 is a 238 W dual-slot card requiring a 550 W PSU and 1x 6-pin + 1x 8-pin power connectors. Their bus interfaces also differ, with the GTX 870M using MXM-B (3.0) and the Tesla using PCIe 2.0 x16.

Architecture Differences

The architectural divide between these two is generational. The GeForce GTX 870M is built on the Kepler architecture, using the GK104 chip, manufactured on a 28 nm process at TSMC. This process node allows for a transistor density of 12.0M / mm², packing 3,540 million transistors into a 294 mm² die. The Tesla C2070 is from the older Fermi architecture, using the GF100 chip, on a 40 nm process at TSMC. This results in a transistor density of just 5.9M / mm², with 3,100 million transistors on a much larger 529 mm² die. The difference in process technology is a primary driver of the performance gap. The GTX 870M’s smaller, denser process allows for higher clock speeds and more compute units within a lower power envelope. The Tesla C2070’s larger, less dense process limits its capabilities in comparison. The GTX 870M supports DirectX 12 (11_0), OpenGL 4.6, and Vulkan 1.2.175. The Tesla C2070 also supports DirectX 12 (11_0) and OpenGL 4.6, but notably lacks Vulkan support. Both have no dedicated ray tracing or tensor cores. The Tesla’s compute capabilities are further defined by its FP32 performance of 1,027.7 GFLOPS, which is less than half of the GTX 870M’s 2.599 TFLOPS.

Where Each One Wins

The GeForce GTX 870M wins in the most critical metric: compute performance. The data shows a 30% lead in OpenCL benchmarks. This is complemented by its superior pixel rate (27.08 GPixel/s vs 16.07 GPixel/s) and texture rate (108.3 GTexel/s vs 32.14 GTexel/s). Its smaller process node and higher clock speeds give it a clear advantage in raw processing throughput. The GTX 870M also wins on efficiency, with a TDP of 100 W versus 238 W, making it the more practical choice for any system where power consumption and heat are a concern. The Tesla C2070, however, has its own domain of advantage. It offers double the memory (6 GB vs 3 GB) and a wider 384-bit memory bus, which gives it a higher memory bandwidth (143.4 GB/s vs 120.0 GB/s). This could make it a better candidate for workloads that are extremely memory-intensive and require large datasets to be loaded on the GPU, even if the compute throughput is lower. The Tesla C2070 also has double the ROPs (48 vs 24), which might offer an edge in specific rasterization tasks, though the GTX 870M’s higher pixel rate suggests otherwise. In summary, the GTX 870M is the winner for general compute and efficiency, while the Tesla C2070’s larger memory pool is its only clear advantage.