AMD Radeon RX Vega M GL vs NVIDIA Tesla K80 Comparison

Head-to-Head Benchmarks

The recorded benchmark data shows the AMD Radeon RX Vega M GL ahead of the NVIDIA Tesla K80 in both tracked tests, with the margin widening considerably in the Vulkan workload. In Geekbench OpenCL, the AMD part scores 19549 against 18620 for the Tesla K80, a 5% advantage. That is a modest but consistent lead, placing the two products in a similar performance band for compute-oriented OpenCL tasks. The Vulkan test tells a different story: the RX Vega M GL reaches 22757 while the Tesla K80 manages 19111, yielding a 19.1% delta in favor of the AMD product. This is the single largest gap in the comparison, and it highlights how API-specific the performance difference can be.

The average benchmark score reinforces the same ordering. The RX Vega M GL posts an average of 21153 across its recorded tests, while the Tesla K80 settles at 18866. That difference of roughly 12% in the aggregate is driven almost entirely by the Vulkan result. In OpenCL, the two are close enough that the delta could be attributed to driver optimization or workload scheduling, but the Vulkan margin is substantial enough to be a genuine architectural differentiator.

Looking at the broader database context, the RX Vega M GL holds a 66th percentile rank among all GPUs, while the Tesla K80 sits at the 63rd percentile. That three-point gap in percentile positioning matches the observed benchmark outcomes. The nearest rivals for the AMD part include the AMD Radeon HD 8970M at 21237 (0.4% higher), the NVIDIA GeForce RTX 5050 at 21035 (0.6% lower), the NVIDIA RTX A4000 Mobile at 21379 (1.1% higher), and the AMD Radeon RX 5600 XT at 20713 (2.1% lower). For the Tesla K80, the nearest neighbors are the NVIDIA GeForce RTX 2070 at 18789 (0.4% higher), the NVIDIA RTX 2000 Ada Generation at 18954 (0.5% lower), the NVIDIA Quadro K6000 at 19030 (0.9% lower), and the AMD Radeon RX 6600 at 19036 (0.9% lower). These rival clusters show that the RX Vega M GL competes in a slightly higher performance tier, while the Tesla K80 sits in a lower band, despite its much larger memory pool and higher raw compute specifications.

The Verdict

The data points to a clear winner for general-purpose graphics and compute workloads: the AMD Radeon RX Vega M GL. It wins both head-to-head tests, holds a higher average score, and ranks higher in the global percentile distribution. For any user prioritizing OpenCL or Vulkan performance, the AMD part is the better choice according to the recorded measurements. The Vulkan lead of 19.1% is particularly decisive, suggesting that the GCN 4.0 architecture handles modern API workloads more efficiently than the Kepler-based Tesla K80.

However, the Tesla K80 should not be dismissed outright. Its 12 GB memory capacity is three times the 4 GB of the RX Vega M GL, and its memory bandwidth of 240.6 GB/s exceeds the 179.2 GB/s of the AMD part. For workloads that are memory-capacity-bound rather than compute-bound, the NVIDIA card could still be relevant. The Tesla K80 also draws its power from a 300 W TDP versus 65 W for the RX Vega M GL, which means it requires far more substantial cooling and power delivery. But the benchmark scores do not reflect any advantage from that extra power draw. The recorded data shows the AMD part winning on every measured performance metric.

The choice comes down to workload type. If the task is general compute or graphics acceleration using modern APIs, the RX Vega M GL wins outright. If the task requires more than 4 GB of memory and can tolerate the higher power envelope, the Tesla K80 offers a capacity advantage that no benchmark in this database captures.

FAQ

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

A: The AMD Radeon RX Vega M GL scores 19549 in Geekbench OpenCL, while the NVIDIA Tesla K80 scores 18620. The AMD part is 5% ahead.

Q: How large is the Vulkan performance difference?

A: The AMD Radeon RX Vega M GL scores 22757 in Geekbench Vulkan, versus 19111 for the NVIDIA Tesla K80. That is a 19.1% advantage for the AMD part.

Q: Does the Tesla K80 have any memory advantage?

A: Yes. The Tesla K80 features 12 GB of GDDR5 memory with a 384-bit bus and 240.6 GB/s bandwidth, while the RX Vega M GL has 4 GB of HBM2 with a 1024-bit bus and 179.2 GB/s bandwidth.

Q: What is the average benchmark score for each GPU?

A: The AMD Radeon RX Vega M GL has an average benchmark score of 21153, and the NVIDIA Tesla K80 has an average of 18866.

Q: Which GPU ranks higher in the overall database percentile?

A: The AMD Radeon RX Vega M GL ranks at the 66th percentile among all GPUs, while the NVIDIA Tesla K80 ranks at the 63rd percentile.

Q: How do the nearest rivals compare for each GPU?

A: The RX Vega M GL's closest rival is the AMD Radeon HD 8970M at 21237 (0.4% higher), while the Tesla K80's closest rival is the NVIDIA GeForce RTX 2070 at 18789 (0.4% higher).

Specification Differences

The two GPUs differ across nearly every major specification category. The AMD Radeon RX Vega M GL is built on a 14 nm process at GlobalFoundries, with 5,000 million transistors on a 208 mm² die. The NVIDIA Tesla K80 uses a 28 nm process at TSMC, packing 7,100 million transistors into a 561 mm² die. Transistor density reflects the process gap: 24.0M per mm² for the AMD part versus 12.7M per mm² for the NVIDIA part.

Clock speeds show a significant divergence. The RX Vega M GL runs at a base clock of 931 MHz and a boost clock of 1011 MHz, while the Tesla K80 operates at 562 MHz base and 824 MHz boost. The memory clock also differs: the AMD part uses 700 MHz (1400 Mbps effective) HBM2, while the NVIDIA part uses 1253 MHz (5 Gbps effective) GDDR5.

Memory configuration is a major differentiator. The RX Vega M GL has 4 GB of HBM2 on a 1024-bit bus, whereas the Tesla K80 has 12 GB of GDDR5 on a 384-bit bus. Despite the wider bus, the AMD part delivers lower bandwidth at 179.2 GB/s versus 240.6 GB/s for the NVIDIA card.

Compute unit counts also vary. The RX Vega M GL has 1280 shading units, 80 texture mapping units, and 32 ROPs. The Tesla K80 has 2496 shading units, 208 TMUs, and 48 ROPs. Pixel rate and texture rate follow: the AMD part achieves 32.35 GPixel/s and 80.88 GTexel/s, while the NVIDIA part reaches 42.85 GPixel/s and 171.4 GTexel/s. FP32 throughput favors the Tesla K80 at 4.113 TFLOPS versus 2.588 TFLOPS for the AMD part. The AMD GPU supports FP16 at 2.588 TFLOPS with a 1:1 ratio, while the Tesla K80 has no recorded FP16 capability.

Power and physical specifications diverge sharply. The RX Vega M GL has a TDP of 65 W and is listed as an IGP with a portable-device-dependent display output. The Tesla K80 has a TDP of 300 W, is a dual-slot card requiring a single 8-pin power connector and a suggested 700 W power supply, uses a PCIe 3.0 x16 interface, has no display outputs, and measures 267 mm (10.5 inches) in length.

Architecture Differences

The architectural gap between these two products is substantial. The AMD Radeon RX Vega M GL uses the Polaris 22 chip built on GCN 4.0 architecture, representing the Vega generation. The NVIDIA Tesla K80 uses the GK210 chip built on Kepler 2.0 architecture, belonging to the Tesla Kepler generation. The process nodes reflect the generational difference: 14 nm for AMD versus 28 nm for NVIDIA.

The AMD part supports DirectX 12 (12_0), OpenGL 4.6, and Vulkan 1.3. The NVIDIA part supports DirectX 12 (11_1), OpenGL 4.6, and Vulkan 1.2.175. The DirectX version difference is notable: the AMD part reaches the full 12_0 feature level, while the NVIDIA part is limited to 11_1. The Vulkan version also favors AMD by a small margin.

The Tesla K80 has a documented predecessor (Tesla Fermi) and successor (Tesla Maxwell), while the RX Vega M GL has no recorded predecessor or successor in the database. The NVIDIA part is also a dual-slot, PCIe-based accelerator with no display outputs, positioning it as a compute-only device. The AMD part is an integrated graphics processor (IGP) with display output dependent on the portable device. The Tesla K80's Kepler architecture was designed for high-throughput compute, but the benchmark data shows that the newer GCN 4.0 design in the RX Vega M GL achieves better real-world results in the tested APIs.

Where Each One Wins

The AMD Radeon RX Vega M GL wins in every recorded benchmark. It leads by 5% in Geekbench OpenCL and by 19.1% in Geekbench Vulkan. The average benchmark score of 21153 versus 18866 gives the AMD part a clear aggregate advantage. The 66th percentile ranking versus the 63rd percentile for the Tesla K80 confirms that the AMD part sits in a higher overall performance tier.

The Tesla K80 wins on specifications that are not captured in the benchmark suite. Its 12 GB memory capacity is three times larger than the 4 GB on the AMD part, and its 240.6 GB/s memory bandwidth exceeds the 179.2 GB/s of the AMD part. The Tesla K80 also has higher raw FP32 throughput at 4.113 TFLOPS versus 2.588 TFLOPS, along with higher pixel rate and texture rate. These numbers suggest that for workloads that are heavily memory-bound or that can utilize more than 4 GB of VRAM, the Tesla K80 may hold an advantage that the recorded benchmarks do not reflect.

For modern API-based workloads, particularly Vulkan, the AMD part is clearly superior. The 19.1% Vulkan delta is the most decisive single metric in this comparison. For OpenCL, the AMD part still wins, but the margin is narrow enough that driver optimizations or specific workload characteristics could shift the balance. The RX Vega M GL is also far more power-efficient on paper, with a 65 W TDP versus 300 W for the Tesla K80, which makes it suitable for integrated or portable deployments where the NVIDIA card cannot physically fit.

The Tesla K80's appeal rests entirely on its memory capacity and raw compute specifications. For users with workloads that require holding large datasets in GPU memory, the 12 GB capacity is a decisive feature. The RX Vega M GL cannot match that capacity, and its smaller memory pool could be a bottleneck for certain compute tasks. The data suggests a split: the AMD part for general compute and graphics acceleration, the NVIDIA part for memory-intensive applications that exceed 4 GB.