AMD Radeon R9 M375X vs NVIDIA Tesla C2070 Comparison

Head-to-Head Benchmarks

The only direct comparison available in the database is the Geekbench OpenCL test, and it is a decisive victory for the NVIDIA Tesla C2070. The Tesla C2070 scores 9,716 points, while the AMD Radeon R9 M375X scores 8,273 points. That is a 17.4% advantage for the NVIDIA part, a substantial margin in compute workloads that rely on OpenCL acceleration.

Context matters here. The Tesla C2070 sits at the 47th percentile among all GPUs in the database, while the Radeon R9 M375X sits at the 43rd percentile. That four-percentile gap reflects the raw performance delta, but it also masks how close these parts are to their respective peer groups. The Tesla C2070's nearest rivals include the NVIDIA Tesla M10 at 9,724 points (a 0.1% difference), the NVIDIA Quadro P4000 at 9,665 points (0.5% behind), and the AMD Radeon Pro WX 2100 at 9,653 points (0.7% behind). The Tesla C2070 is effectively trading blows with these cards, within a single percentage point in either direction. The GeForce GTX 1070, a much newer gaming part, sits just 0.7% ahead at 9,780 points, which shows the Tesla C2070 remains competitive in raw OpenCL throughput despite its age.

The Radeon R9 M375X, by contrast, is clustered with a different tier of hardware. Its nearest rivals are the NVIDIA Quadro K1200 at 8,265 points (0.7% behind), the GeForce GTX 675MX at 8,427 points (1.2% ahead), the AMD Radeon 880M at 8,436 points (1.3% ahead), and the GeForce MX330 at 8,458 points (1.6% ahead). All of these are within a narrow band, meaning the R9 M375X is not an outlier in its class; it is simply a mid-pack performer among entry-level and older mobile-oriented GPUs.

The head-to-head result is unambiguous: the Tesla C2070 wins the only shared benchmark, and it wins by a healthy margin. The Radeon R9 M375X has no benchmark win in the database to counter that, as the wins tally shows one win for the NVIDIA card and zero for the AMD card. The Vulkan score for the R9 M375X, 8,377 points, is not directly comparable to the Tesla C2070 because the latter has no recorded Vulkan result, so it cannot be used to claim parity or superiority in that API.

The Verdict

The data points to a clear ranking: the NVIDIA Tesla C2070 is the faster GPU in compute workloads as measured by Geekbench OpenCL. Its 17.4% lead over the Radeon R9 M375X is not a marginal difference; it is a meaningful gap that would show up in any OpenCL-heavy application. For users whose primary metric is raw compute throughput, the Tesla C2070 is the better choice.

However, the verdict is not solely about speed. The Radeon R9 M375X is a much younger product, released in 2015 compared to the Tesla C2070's 2011 launch. It uses a smaller die, draws less power by implication (though the database does not list a TDP for the AMD part, the NVIDIA card is rated at 238 W), and supports modern APIs that the Tesla C2070 cannot match. The R9 M375X lists Vulkan 1.2.170 support, while the Tesla C2070 has no Vulkan support at all. It also supports DirectX 12 (11_1) versus the Tesla C2070's DirectX 12 (11_0), a small but real API feature gap.

So the verdict splits along use cases. If the workload is pure OpenCL compute and power consumption is not a constraint, the Tesla C2070 wins outright. If the workload involves Vulkan, requires a smaller physical footprint, or runs in a system with limited power delivery, the Radeon R9 M375X is the more sensible pick despite its lower compute score.

Where Each One Wins

The NVIDIA Tesla C2070 wins in raw OpenCL compute performance. Its 9,716 score versus 8,273 for the AMD part is the single largest measurable advantage in this comparison. It also offers significantly more memory, 6 GB versus 2 GB, and a wider memory bus at 384-bit versus 128-bit, which translates to 143.4 GB/s of bandwidth against 72.00 GB/s for the Radeon. For dataset-heavy workloads that exceed 2 GB or that are bandwidth-sensitive, the Tesla C2070 is the obvious winner. Its pixel rate is nearly identical to the AMD card, 16.07 GPixel/s versus 16.24 GPixel/s, but its texture rate is lower at 32.14 GTexel/s versus 40.60 GTexel/s, so the AMD part actually wins in texture throughput.

The Radeon R9 M375X wins in several non-benchmark categories. It has a higher transistor density, 12.2M per mm² versus 5.9M per mm² for the Tesla, which reflects its much smaller 123 mm² die against the Tesla's 529 mm² die. It also has a higher base clock at 925 MHz and a boost clock at 1015 MHz, whereas the Tesla C2070 has no recorded base or boost clock in the database. The AMD card supports PCIe 3.0 x16, while the Tesla C2070 is limited to PCIe 2.0 x16. For users building a modern system, that bus interface difference matters for data transfer efficiency.

The R9 M375X also wins on shading unit count, with 640 shading units versus 448 for the Tesla C2070, and it posts a higher FP32 throughput at 1,299.2 GFLOPS versus 1,027.7 GFLOPS. That is curious given the OpenCL result favors NVIDIA, but it suggests the Tesla C2070's advantage comes from other architectural factors rather than raw shader math. The AMD card also has a lower transistor count at 1,500 million versus 3,100 million, which, combined with the smaller die, points to a more power-efficient design, though the database does not list a TDP for the R9 M375X to confirm the actual power draw.

FAQ

Q: Which GPU has the higher OpenCL score?

A: The NVIDIA Tesla C2070 scores 9,716 points in Geekbench OpenCL, which is 17.4% higher than the AMD Radeon R9 M375X's score of 8,273 points.

Q: Does the AMD Radeon R9 M375X support Vulkan?

A: Yes, the R9 M375X supports Vulkan 1.2.170. The NVIDIA Tesla C2070 has no recorded Vulkan support in the database.

Q: How much memory does each card have?

A: The NVIDIA Tesla C2070 has 6 GB of GDDR5 memory on a 384-bit bus, providing 143.4 GB/s of bandwidth. The AMD Radeon R9 M375X has 2 GB of GDDR5 memory on a 128-bit bus, providing 72.00 GB/s of bandwidth.

Q: Which GPU has a higher FP32 compute throughput?

A: The AMD Radeon R9 M375X reaches 1,299.2 GFLOPS, while the NVIDIA Tesla C2070 reaches 1,027.7 GFLOPS. Despite this, the Tesla C2070 wins the OpenCL benchmark.

Q: What are the process nodes for these two GPUs?

A: The NVIDIA Tesla C2070 uses a 40 nm process, while the AMD Radeon R9 M375X uses a 28 nm process. The AMD part also has a smaller die at 123 mm² versus 529 mm² for the NVIDIA card.

Q: What is the bus interface of each card?

A: The NVIDIA Tesla C2070 uses PCIe 2.0 x16, while the AMD Radeon R9 M375X uses PCIe 3.0 x16.

Architecture Differences

The two GPUs come from different architectural generations and design philosophies. The NVIDIA Tesla C2070 is built on the Fermi architecture with the GF100 chip, a 40 nm design manufactured by TSMC. It packs 3,100 million transistors onto a 529 mm² die, yielding a transistor density of 5.9M per mm². This is a large, power-hungry compute-oriented chip, reflected in its 238 W TDP and dual-slot cooling requirement, along with its 1x 6-pin plus 1x 8-pin power connectors and a suggested power supply of 550 W. It was released in 2011 as part of the Tesla Fermi generation, with a predecessor named Tesla and a successor named Tesla Kepler.

The AMD Radeon R9 M375X is a much smaller and newer part. It uses the Tropo chip with the GCN 1.0 architecture, built on a 28 nm process at TSMC. The die measures just 123 mm² and contains 1,500 million transistors, giving it a transistor density of 12.2M per mm², more than double that of the Tesla C2070. It was released in 2015 as part of the Gem System (R9 M300) generation, with a predecessor named Solar System and a successor named Polaris Mobile. The database does not list a TDP, slot width, power connectors, or suggested PSU for this card, which is typical for a mobile-class GPU.

The memory subsystems differ dramatically. The Tesla C2070 uses 6 GB of GDDR5 on a 384-bit bus with a memory clock of 747 MHz (3 Gbps effective), achieving 143.4 GB/s of bandwidth. The R9 M375X uses 2 GB of GDDR5 on a 128-bit bus with a memory clock of 1125 MHz (4.5 Gbps effective), achieving 72.00 GB/s. The Tesla C2070's wider bus gives it exactly double the bandwidth of the AMD part, a major factor in compute workloads.

The compute units are organized differently as well. The Tesla C2070 has 448 shading units, 56 texture mapping units, and 48 ROPs. The R9 M375X has 640 shading units, 40 TMUs, and 16 ROPs. The AMD card has more shading units and a higher texture rate at 40.60 GTexel/s versus 32.14 GTexel/s for the NVIDIA card. The pixel rates are nearly identical, with the R9 M375X at 16.24 GPixel/s and the Tesla C2070 at 16.07 GPixel/s. The R9 M375X also has a higher FP32 throughput at 1,299.2 GFLOPS versus 1,027.7 GFLOPS for the Tesla C2070.

API support is another major differentiator. The Tesla C2070 supports DirectX 12 (11_0) and OpenGL 4.6, but has no Vulkan support listed. The R9 M375X supports DirectX 12 (11_1), OpenGL 4.6, and Vulkan 1.2.170. The R9 M375X also uses PCIe 3.0 x16, whereas the Tesla C2070 is limited to PCIe 2.0 x16. The Tesla C2070 has a single DVI display output, while the R9 M375X has no display outputs listed, suggesting it is intended for laptop or embedded use rather than standalone workstation duty. The Tesla C2070 measures 248 mm in length (9.8 inches) and is a dual-slot card, while the R9 M375X has no dimensions listed.

Both parts are end-of-life products, so neither is a forward-looking investment. The architectural differences explain the benchmark result: the Tesla C2070's massive memory bandwidth and compute-focused Fermi design prevail in OpenCL, while the R9 M375X's newer GCN architecture, higher clocks, and modern API support make it a more flexible part for current software environments.