AMD Radeon R9 M360 vs NVIDIA Tesla C2070 Comparison

Head-to-Head Benchmarks

The only directly comparable benchmark in the database is Geekbench OpenCL, and the NVIDIA Tesla C2070 takes it decisively. The Tesla C2070 scores 9716, while the AMD Radeon R9 M360 scores 8211. That is an 18.3% advantage for the NVIDIA part, a substantial gap in compute workloads. The delta is large enough that it is unlikely to be noise; the C2070 simply has more raw OpenCL throughput available.

Looking at how each card sits among its nearest rivals reinforces that gap. The Tesla C2070's 9716 places it between the NVIDIA Tesla M10 (9724, only 0.1% higher) and the NVIDIA Quadro P4000 (9665, 0.5% lower). It also edges out the AMD Radeon Pro WX 2100 (9653, 0.7% lower) and trails the NVIDIA GeForce GTX 1070 (9780, 0.7% higher) by a slim margin. In other words, the C2070 is right in the middle of a tight cluster of much newer GPUs, which is remarkable for a product from 2011. Its 47th percentile ranking across all GPUs confirms it is not an outlier; it is a competent compute card even by modern standards.

The AMD Radeon R9 M360, by contrast, sits in a lower performance tier. Its 8211 OpenCL score puts it in a cluster with the NVIDIA GeForce GTX 950M (8135, 0.1% lower), the NVIDIA GeForce 945M (8099, 0.4% lower), and the NVIDIA GRID K2 (8080, 0.6% lower). It also trails the NVIDIA GeForce GTX 980 (8167, 0.5% higher) by a hair. The R9 M360's 42nd percentile ranking across all GPUs is five points lower than the C2070's, and its average benchmark score of 8129 is roughly 16% below the Tesla's 9716. The data does not show a single benchmark where the AMD card wins outright; the head-to-head table lists one win for the Tesla and zero for the Radeon.

What is striking is that the C2070 achieves this lead despite being older and built on a larger process node. The Tesla uses the GF100 chip on a 40 nm TSMC process, with 3,100 million transistors on a 529 mm² die. The R9 M360 uses the Tropo chip on a 28 nm TSMC process, with 1,500 million transistors on a 123 mm² die. The AMD part is smaller, denser, and more modern in design, yet it loses by a wide margin in OpenCL. The R9 M360's transistor density of 12.2M per mm² is more than double the Tesla's 5.9M per mm², but density does not translate into compute performance here. The Tesla's larger die and higher transistor count give it more shading units, TMUs, and ROPs, and that hardware scale shows up in the raw score.

There is also a Vulkan score for the R9 M360 (8047), but no comparable Vulkan result exists for the C2070, so it cannot be used for a head-to-head comparison. The only apples-to-apples metric is OpenCL, and the verdict is unambiguous.

The Verdict

The NVIDIA Tesla C2070 is the stronger compute card in every measurable way from this database. Its OpenCL score of 9716 beats the AMD Radeon R9 M360's 8211 by 18.3%, and its percentile ranking (47th) is higher than the AMD's (42nd). If the task is OpenCL compute, general GPU acceleration, or any workload that relies on shading and texture throughput, the C2070 is the pick. The data shows a clear winner with no countervailing benchmark win for the AMD side.

However, the R9 M360 is not without reasons for consideration. It supports Vulkan 1.2.170, while the C2070 has no Vulkan support listed at all. Its DirectX support is also newer: the AMD card lists DirectX 12 (11_1), while the Tesla lists DirectX 12 (11_0). For any application that requires Vulkan, the AMD card is the only choice between the two. The R9 M360 also has a higher base clock (900 MHz) and boost clock (925 MHz) compared to the Tesla's unspecified clocks, though clock speed alone does not make up for the compute deficit. The AMD part is also built on a smaller 28 nm process, which typically means lower power draw, though the database does not list a TDP for the R9 M360 to confirm that. The Tesla's TDP is listed at 238 W, and it requires a 550 W suggested PSU with a dual-slot cooler and both a 6-pin and 8-pin power connector. The AMD card's power requirements are not recorded, so no direct comparison is possible.

For pure compute, the Tesla wins. For API compatibility and modern feature support, the AMD wins. There is no scenario in this data where the R9 M360 beats the C2070 on raw performance, so the decision hinges on software requirements, not speed.

Where Each One Wins

The NVIDIA Tesla C2070 wins in every benchmark category where both cards have recorded results. That is a single OpenCL test, but it is the one that matters for compute. The Tesla's 448 shading units, 56 TMUs, and 48 ROPs give it substantially more parallel hardware than the R9 M360's 512 shading units, 32 TMUs, and 16 ROPs. The Tesla also has a much wider memory bus (384 bit vs. 128 bit) and nearly double the memory bandwidth (143.4 GB/s vs. 72.00 GB/s). The Tesla's 6 GB of GDDR5 memory is also 50% larger than the R9 M360's 4 GB. For large datasets, large textures, or memory-bandwidth-hungry compute tasks, the Tesla is clearly the better tool. Its pixel rate of 16.07 GPixel/s and texture rate of 32.14 GTexel/s both exceed the AMD's 14.80 GPixel/s and 29.60 GTexel/s, respectively.

The AMD Radeon R9 M360 wins on software and connectivity features. It supports Vulkan 1.2.170, which the Tesla does not. It has a DirectX 12 (11_1) feature level versus the Tesla's DirectX 12 (11_0), meaning the AMD part is more capable in modern graphics APIs. The R9 M360 also uses a PCIe 3.0 x16 interface, while the Tesla is limited to PCIe 2.0 x16. That newer bus interface can matter for data transfer speeds in some workloads, though the Tesla's higher memory bandwidth may compensate in compute-heavy tasks. The AMD card also has a higher base clock (900 MHz vs. unspecified for the Tesla) and a boost clock of 925 MHz, which helps in workloads that scale with clock speed rather than raw core count. The 28 nm process node means the AMD chip is smaller and likely more power-efficient, though without a TDP listing for the R9 M360, that remains an inference from the node size, not a measured fact.

For use cases: the Tesla is for CUDA-style compute, OpenCL acceleration, and heavy graphics workloads that saturate memory bandwidth. The AMD is for Vulkan-based applications, DX12-era games, or any environment where the newer API support is a hard requirement. If the software stack needs Vulkan, the R9 M360 is the only option. If the software stack needs raw throughput, the Tesla wins without contest.

FAQ

Q: Which GPU has the higher OpenCL benchmark score?

A: The NVIDIA Tesla C2070 scores 9716, while the AMD Radeon R9 M360 scores 8211. The Tesla leads by 18.3%.

Q: Does the AMD Radeon R9 M360 win any benchmark in the head-to-head comparison?

A: No. The head-to-head table shows one win for the Tesla C2070 and zero wins for the R9 M360. The only shared test is Geekbench OpenCL, where the Tesla is faster.

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

A: The Tesla C2070 has 6 GB of GDDR5 memory on a 384-bit bus, yielding 143.4 GB/s bandwidth. The R9 M360 has 4 GB of GDDR5 on a 128-bit bus, yielding 72.00 GB/s bandwidth.

Q: Which card supports Vulkan?

A: Only the AMD Radeon R9 M360 lists Vulkan support, with version 1.2.170. The NVIDIA Tesla C2070 has no Vulkan support recorded in the database.

Q: How does each card compare to its nearest rivals?

A: The Tesla C2070's 9716 score is within 0.7% of the Tesla M10 (9724), Quadro P4000 (9665), Radeon Pro WX 2100 (9653), and GeForce GTX 1070 (9780). The R9 M360's 8211 score is within 0.6% of the GTX 950M (8135), GeForce 945M (8099), GTX 980 (8167), and GRID K2 (8080).

Q: What are the process node and transistor counts?

A: The Tesla C2070 uses a 40 nm process with 3,100 million transistors on a 529 mm² die. The R9 M360 uses a 28 nm process with 1,500 million transistors on a 123 mm² die.

Architecture Differences

The two GPUs come from completely different architectural generations and design philosophies. The NVIDIA Tesla C2070 is built on the Fermi architecture, specifically the GF100 chip, and belongs to the Tesla Fermi generation (x20xx series). It was released in 2011 and is now end-of-life. The AMD Radeon R9 M360 uses the GCN 1.0 architecture with the Tropo chip, from the Gem System generation (R9 M300 series), released in 2015 and also end-of-life. The Fermi design is older, but it was NVIDIA's high-performance compute architecture of its era, built for datacenter and professional workloads. The GCN 1.0 architecture on the AMD side was designed for gaming and general-purpose compute, with a focus on efficiency and scalability.

The process nodes tell a clear story of generational progress. The Tesla is fabricated on TSMC's 40 nm node, while the R9 M360 uses TSMC's 28 nm node. The Tesla packs 3,100 million transistors into a 529 mm² die, giving a transistor density of 5.9M per mm². The R9 M360 has 1,500 million transistors on a much smaller 123 mm² die, achieving a density of 12.2M per mm². The AMD chip is more than twice as dense, which is a direct result of the smaller node. However, that density advantage does not translate into compute performance, as the OpenCL scores show. The Tesla's larger die allows for more functional units: 448 shading units, 56 TMUs, and 48 ROPs versus the AMD's 512 shading units, 32 TMUs, and 16 ROPs. The Tesla has fewer shaders but more TMUs and three times the ROPs, which helps in memory-intensive and texture-heavy workloads.

Memory architecture differs sharply as well. The Tesla uses a 384-bit memory bus with 6 GB of GDDR5, running at an effective 3 Gbps, for a bandwidth of 143.4 GB/s. The R9 M360 uses a 128-bit bus with 4 GB of GDDR5, at an effective 4.5 Gbps, for a bandwidth of 72.00 GB/s. The Tesla has double the bandwidth despite slower memory chips because its bus is three times wider. Memory size also favors the Tesla: 6 GB versus 4 GB, which matters for large compute datasets. The R9 M360's memory clock is listed at 1125 MHz (4.5 Gbps effective), while the Tesla's memory clock is 747 MHz (3 Gbps effective). Higher effective memory speed on the AMD card does not overcome the bus width deficit.

Compute throughput numbers align with the benchmark results. The Tesla C2070 delivers 1,027.7 GFLOPS of FP32 performance, while the R9 M360 delivers 947.2 GFLOPS. The Tesla also has higher pixel rate (16.07 GPixel/s vs. 14.80 GPixel/s) and texture rate (32.14 GTexel/s vs. 29.60 GTexel/s). The Tesla's TDP is 238 W, with a dual-slot cooler and a 1x 6-pin plus 1x 8-pin power connector setup, and it requires a 550 W suggested PSU. The R9 M360 has no TDP, power connector, or PSU requirements listed, which is typical for a mobile-oriented GPU. The Tesla uses PCIe 2.0 x16, while the R9 M360 uses PCIe 3.0 x16. Display outputs are listed only for the Tesla (1x DVI), with none specified for the AMD card.

API support is the final differentiator. Both cards support OpenGL 4.6 and DirectX 12, but the feature levels differ: the Tesla lists DirectX 12 (11_0), while the R9 M360 lists DirectX 12 (11_1). The AMD card has Vulkan 1.2.170 support; the Tesla has none. For any modern Vulkan-based workload, the R9 M360 is the only viable choice. For raw OpenCL compute and memory bandwidth, the Tesla C2070 is superior in every measured metric.