AMD Radeon Vega 8 vs NVIDIA Tesla C2070 Comparison

The NVIDIA Tesla C2070 and AMD Radeon Vega 8 represent two very different eras of GPU design, and their benchmark data reflects that divide. In the only shared benchmark test available—Geekbench OpenCL—the Tesla C2070 scores 9,716, while the Vega 8 scores 8,822. That gives the Tesla a 10.1% advantage, a clear but not overwhelming lead. The Tesla’s score places it at the 47th percentile of all GPUs, while the Vega 8 sits at the 45th percentile, meaning both are mid-pack performers. The Tesla’s nearest rival, the NVIDIA Tesla M10, scores 9,724 (0.1% faster), while the Vega 8’s closest competitor, the AMD Radeon 890M, scores 9,210 (0.1% faster). In short, the Tesla wins the head-to-head, but the margin is modest, and neither card is a top-tier performer by modern standards.

Head-to-Head Benchmarks

The only direct comparison available is Geekbench OpenCL, where the NVIDIA Tesla C2070 posts 9,716 points against the AMD Radeon Vega 8’s 8,822 points. The 10.1% delta is the single data point that separates them, and it favors the Tesla. This is not a landslide victory; it is a meaningful but narrow edge. For context, the Tesla’s average benchmark score across all tests is 9,716, while the Vega 8’s average is 9,221, reflecting that the Vega 8 has other test results that pull its average down.

The Vega 8 does, however, show strength in other API benchmarks that the Tesla cannot match because it lacks results for them. In Geekbench Metal, the Vega 8 scores 10,706, which is higher than the Tesla’s OpenCL score. In Geekbench Vulkan, it scores 8,134. These numbers suggest that the Vega 8 is more versatile across modern APIs, even if it loses the specific OpenCL contest. The Tesla has no Vulkan or Metal results in the data, so its competitiveness in those APIs is unknown. The wins tally is 1-0 in favor of the Tesla, but that is only because the data set is limited to one shared test.

Looking at the rival landscape, the Tesla C2070’s OpenCL score of 9,716 is within 0.7% of the GeForce GTX 1070’s 9,780, and it is 0.5% ahead of the Quadro P4000’s 9,665. The Vega 8’s OpenCL score of 8,822 is 0.6% behind the GeForce GTX 960’s 9,273 and 0.8% behind the GeForce GTX 465’s 9,294. This places the Vega 8 in the company of older discrete GPUs, while the Tesla sits near more modern mid-range options. The delta percentages are small, but the pattern is consistent: the Tesla is the stronger OpenCL performer, while the Vega 8’s average is dragged down by its lower OpenCL score relative to its Metal result.

Architecture Differences

The architectural gap between these two is generational. The NVIDIA Tesla C2070 uses the GF100 chip on the Fermi architecture, built on a 40 nm process at TSMC. It packs 3,100 million transistors into a 529 mm² die, yielding a transistor density of 5.9 million per mm². In contrast, the AMD Radeon Vega 8 uses the Raven chip on the GCN 5.0 architecture, built on a 14 nm process at GlobalFoundries. It contains 4,940 million transistors on a 210 mm² die, with a density of 23.5 million per mm². This means the Vega 8 crams nearly 60% more transistors into less than half the silicon area.

The Vega 8 is an integrated graphics processor (IGP), meaning it shares system memory and has no dedicated VRAM. Its memory type, bus width, and bandwidth are all listed as "System Shared" or "System Dependent," which is a fundamental difference from the Tesla’s dedicated 6 GB of GDDR5 on a 384-bit bus with 143.4 GB/s of bandwidth. The Tesla’s memory subsystem is fixed and self-contained, while the Vega 8’s performance is tied to the host system’s RAM speed and configuration.

Clock speeds also differ sharply. The Vega 8 has a base clock of 300 MHz and a boost clock of 1,100 MHz, while the Tesla’s base and boost clocks are not listed. The Tesla’s memory runs at 747 MHz (3 Gbps effective), which is a fixed figure, whereas the Vega 8’s memory clock is system-dependent. The shading unit counts are close—448 for the Tesla and 512 for the Vega 8—but the TMU and ROP counts diverge: the Tesla has 56 TMUs and 48 ROPs, while the Vega 8 has 32 TMUs and only 8 ROPs. This ROP disparity explains the Tesla’s much higher pixel rate of 16.07 GPixel/s versus the Vega 8’s 8.80 GPixel/s.

The Vega 8 pulls ahead in texture rate, posting 35.20 GTexel/s against the Tesla’s 32.14 GTexel/s, and it also has higher FP32 throughput at 1,126.4 GFLOPS versus 1,027.7 GFLOPS. The Vega 8 additionally supports FP16 at 2.253 TFLOPS (2:1), while the Tesla has no FP16 capability listed. Power consumption is another chasm: the Tesla is rated at 238 W TDP with dual-slot cooling and 1x 6-pin plus 1x 8-pin power connectors, while the Vega 8 is a 25 W IGP with no power connectors and no suggested PSU. The Tesla requires a 550 W power supply recommendation; the Vega 8 draws its power from the motherboard.

FAQ

Q: Which GPU has higher raw FP32 compute?

A: The AMD Radeon Vega 8 edges out the NVIDIA Tesla C2070, with 1,126.4 GFLOPS versus 1,027.7 GFLOPS, a difference of roughly 9.6%.

Q: Does the Tesla C2070 support Vulkan?

A: No. The Tesla C2070 lists DirectX 12 (11_0) and OpenGL 4.6, but no Vulkan support. The Vega 8 supports Vulkan 1.3 in addition to DirectX 12 (12_1) and OpenGL 4.6.

Q: What is the memory bandwidth of the Vega 8?

A: It is system-dependent, as the Vega 8 uses shared system memory. The Tesla C2070 has a fixed 143.4 GB/s bandwidth from its dedicated 6 GB GDDR5 on a 384-bit bus.

Q: How do their transistor densities compare?

A: The Vega 8’s density is 23.5 million transistors per mm², which is nearly four times higher than the Tesla’s 5.9 million per mm², due to the newer 14 nm process versus 40 nm.

Q: Which card has more ROPs?

A: The Tesla C2070 has 48 ROPs, compared to the Vega 8’s 8 ROPs. This gives the Tesla a significantly higher pixel rate of 16.07 GPixel/s versus 8.80 GPixel/s.

Q: Is the Tesla C2070 still in production?

A: No, it is end-of-life, as is the Vega 8. The Tesla was released in 2011, and the Vega 8 in 2018.

Specification Differences

The two GPUs differ in nearly every major specification category. The Tesla C2070 uses a 40 nm process from TSMC, while the Vega 8 uses a 14 nm process from GlobalFoundries. The Tesla has a die size of 529 mm² and 3,100 million transistors, whereas the Vega 8 has a 210 mm² die and 4,940 million transistors. Transistor density is 5.9M/mm² for the Tesla and 23.5M/mm² for the Vega 8.

Memory is a stark contrast: the Tesla has 6 GB of GDDR5 on a 384-bit bus with 143.4 GB/s bandwidth, while the Vega 8 has system-shared memory with system-dependent bandwidth. Clock speeds: the Tesla’s core clocks are not listed, but its memory runs at 747 MHz (3 Gbps effective); the Vega 8 has a 300 MHz base and 1,100 MHz boost. Shading units: 448 for the Tesla, 512 for the Vega 8. TMUs: 56 versus 32. ROPs: 48 versus 8. Pixel rate: 16.07 GPixel/s versus 8.80 GPixel/s. Texture rate: 32.14 GTexel/s versus 35.20 GTexel/s. FP32: 1,027.7 GFLOPS versus 1,126.4 GFLOPS. FP16: not available on the Tesla, 2.253 TFLOPS on the Vega 8.

Power and physical specs also differ: the Tesla is a 238 W dual-slot card with 1x 6-pin and 1x 8-pin connectors, requiring a 550 W PSU, and measures 248 mm (9.8 inches) in length. The Vega 8 is a 25 W IGP with no connectors and no suggested PSU. Bus interface: PCIe 2.0 x16 for the Tesla, IGP for the Vega 8. Display outputs: 1x DVI for the Tesla, motherboard-dependent for the Vega 8. API support: the Tesla has DirectX 12 (11_0) and OpenGL 4.6, while the Vega 8 has DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.3.

The Verdict

The data points to a clear but context-dependent choice. The NVIDIA Tesla C2070 wins the only head-to-head benchmark, posting a 10.1% higher OpenCL score than the AMD Radeon Vega 8. It also has a superior memory subsystem with dedicated 6 GB GDDR5 and 143.4 GB/s bandwidth, far more ROPs (48 versus 8), and a much higher pixel rate. For workloads that rely on OpenCL, fixed memory bandwidth, or high fill rates, the Tesla is the stronger card.

However, the Vega 8 is not without arguments. It has higher FP32 compute (1,126.4 GFLOPS versus 1,027.7 GFLOPS), higher texture rate (35.20 GTexel/s versus 32.14 GTexel/s), and supports FP16, which the Tesla lacks entirely. It also supports Vulkan 1.3, while the Tesla has no Vulkan support. Its 25 W TDP versus the Tesla’s 238 W makes it drastically more power-efficient, and it requires no additional power connectors or a dedicated PSU recommendation. The Vega 8’s Metal score of 10,706 also exceeds the Tesla’s OpenCL score, suggesting it may perform better in Apple-centric or Metal-optimized workloads.

The choice hinges on use case. If you need a discrete GPU with dedicated VRAM and strong OpenCL performance, the Tesla C2070 is the pick. If you need an integrated solution with modern API support, lower power draw, and higher compute throughput, the Vega 8 is the better fit. The Tesla’s end-of-life status and 2011 release date mean it is a legacy product, while the Vega 8, despite also being end-of-life, is from 2018 and offers more contemporary features.

Where Each One Wins

The NVIDIA Tesla C2070 wins in scenarios that demand dedicated memory and high fill rates. Its 6 GB of GDDR5 on a 384-bit bus provides 143.4 GB/s of bandwidth, which is essential for large datasets that cannot fit in shared system memory. Its 48 ROPs and 16.07 GPixel/s pixel rate make it better suited for tasks involving heavy rasterization or high-resolution framebuffer operations. In the OpenCL benchmark, it wins outright, and its percentile rank of 47 versus the Vega 8’s 45 indicates slightly better overall standing among all GPUs. The Tesla also has a higher average benchmark score of 9,716 versus 9,221.

The AMD Radeon Vega 8 wins in efficiency and modern API support. Its 25 W TDP is a fraction of the Tesla’s 238 W, making it viable for compact or power-constrained systems. Its FP32 throughput of 1,126.4 GFLOPS and texture rate of 35.20 GTexel/s are both higher than the Tesla’s, meaning compute-heavy or texture-bound workloads may run faster. The Vega 8’s FP16 capability of 2.253 TFLOPS opens the door to mixed-precision tasks that the Tesla cannot handle. Vulkan 1.3 support makes it compatible with modern game engines and compute frameworks, whereas the Tesla is limited to DirectX 12 (11_0) and OpenGL 4.6. The Vega 8’s Metal score of 10,706 suggests strong performance in Apple ecosystems, and its Vulkan score of 8,134 provides an alternative API path that the Tesla does not offer.

In practical terms, the Tesla is for legacy compute tasks, CUDA-adjacent workflows (though CUDA is not listed, the Fermi architecture implies it), or any scenario where dedicated VRAM is non-negotiable. The Vega 8 is for integrated builds, low-power systems, or users who need Vulkan or FP16 support. Neither is a modern gaming powerhouse, but each has a distinct niche where it excels.