NVIDIA GeForce RTX 4050 Mobile vs NVIDIA Tesla K20m Comparison

The NVIDIA Tesla K20m and the NVIDIA GeForce RTX 4050 Mobile represent two vastly different eras of GPU design, yet their average benchmark scores place them in the same performance tier. The data shows the RTX 4050 Mobile is the definitive winner in raw compute benchmarks, but the Tesla K20m’s legacy as a compute-focused workhorse keeps it competitive in aggregate scores. This analysis breaks down the numbers to show where each card excels and who should consider them.

Head-to-Head Benchmarks

The head-to-head data is unambiguous: the RTX 4050 Mobile wins both available benchmark tests by a massive margin. In Geekbench OpenCL, the RTX 4050 Mobile scores 74,748, while the Tesla K20m manages 16,241. That is a delta of -78.3% for the Tesla, meaning the RTX 4050 Mobile is roughly 4.6 times faster in this specific workload. The Geekbench Vulkan test tells a similar story, with the RTX 4050 Mobile scoring 75,235 against the Tesla’s 21,936, a delta of -70.8%. These are not incremental gains; they represent a generational leap in compute throughput.

Despite this dominance in the head-to-head, the overall average benchmark scores are remarkably close. The Tesla K20m has an average benchmark score of 19,089, while the RTX 4050 Mobile sits at 19,049. The delta between the two is a mere 0.2%, with the Tesla technically ahead by that fraction. This suggests that the RTX 4050 Mobile’s wins in OpenCL and Vulkan are balanced by other benchmarks where the Tesla performs relatively better, likely due to its different architecture and driver optimizations. The nearest rival data confirms this tight grouping: the AMD Radeon RX 6600 averages 19,036 (0.3% behind the Tesla), and the NVIDIA Quadro K6000 averages 19,030 (0.3% behind). The RTX 4050 Mobile’s own rival list shows the same picture, with the Tesla K20m just 0.2% ahead.

Architecture Differences

The architectural gap between these two GPUs is vast. The Tesla K20m uses the Kepler architecture (chip GK110) built on a 28 nm process at TSMC. It packs 7,080 million transistors on a 561 mm² die, giving a transistor density of 12.6 million per mm². In contrast, the RTX 4050 Mobile uses the Ada Lovelace architecture (chip AD107) on a 5 nm process, also from TSMC. It contains 18,900 million transistors on a much smaller 159 mm² die, achieving a density of 118.9 million per mm². That is nearly 10 times the transistor density, explaining the RTX 4050 Mobile’s efficiency.

Memory configurations differ significantly. The Tesla K20m has 5 GB of GDDR5 on a 320-bit bus, delivering 208.0 GB/s of bandwidth. The RTX 4050 Mobile has 6 GB of GDDR6 on a 96-bit bus, yielding 192.0 GB/s. While the Tesla has a wider bus and slightly more bandwidth, the RTX 4050 Mobile uses faster memory (16 Gbps effective vs 5.2 Gbps effective) and a newer type. The RTX 4050 Mobile also features 20 RT cores and 80 tensor cores, which are entirely absent from the Tesla K20m. These hardware units enable real-time ray tracing and AI-accelerated features that the Kepler card cannot perform.

Compute resources tell a story of specialization. The Tesla K20m has 2,496 shading units, 208 TMUs, and 40 ROPs. The RTX 4050 Mobile has 2,560 shading units, 80 TMUs, and 48 ROPs. While the shading unit count is similar, the texture unit count is drastically lower on the RTX 4050 Mobile. This leads to a texture rate of 140.4 GTexel/s for the RTX 4050 Mobile versus 146.8 GTexel/s for the Tesla. However, the RTX 4050 Mobile’s pixel rate is 84.24 GPixel/s, more than double the Tesla’s 36.71 GPixel/s. In raw FP32 compute, the RTX 4050 Mobile delivers 8.986 TFLOPS, over 2.5 times the Tesla’s 3.524 TFLOPS. The RTX 4050 Mobile also matches its FP16 performance at 8.986 TFLOPS (1:1), a feature the Tesla lacks entirely.

Where Each One Wins

The RTX 4050 Mobile wins decisively in modern compute workloads, as shown by its OpenCL and Vulkan scores. The 78.3% lead in OpenCL and 70.8% lead in Vulkan indicate that any application leveraging these APIs will see substantial performance gains. This makes the RTX 4050 Mobile the clear choice for contemporary gaming, ray tracing, and AI-assisted tasks. Its 20 RT cores and 80 tensor cores enable features like DLSS and ray-traced effects, which the Tesla K20m cannot handle. The RTX 4050 Mobile also supports DirectX 12 Ultimate (12_2) and Vulkan 1.4, while the Tesla is limited to DirectX 12 (11_0) and Vulkan 1.2.175.

The Tesla K20m’s strengths lie elsewhere. Its average benchmark score of 19,089 is technically higher than the RTX 4050 Mobile’s 19,049, suggesting it holds its own in certain legacy or compute-specific benchmarks not covered in the head-to-head. With 208 TMUs versus the RTX 4050 Mobile’s 80, the Tesla has a higher texture rate (146.8 GTexel/s vs 140.4 GTexel/s), which could benefit texture-heavy workloads. Its 320-bit memory bus, while older, provides bandwidth that is close to the newer card. The Tesla also has a higher transistor count on a larger die, which may indicate better raw compute throughput in specific scientific or professional applications that were optimized for Kepler.

Power consumption is a major differentiator. The Tesla K20m has a TDP of 225 W, requires both a 6-pin and 8-pin power connector, and needs a 550 W power supply. The RTX 4050 Mobile has a TDP of only 50 W, uses no power connectors, and is an IGP (integrated graphics processor) designed for laptops. This makes the RTX 4050 Mobile vastly more efficient, delivering 2.5 times the FP32 performance at less than a quarter of the power draw. The Tesla’s dual-slot design and 267 mm length also make it physically incompatible with most modern systems, while the RTX 4050 Mobile’s portable device-dependent outputs are designed for mobile integration.

The Verdict

From the data, the RTX 4050 Mobile is the superior GPU for virtually all modern use cases. It wins both head-to-head benchmarks by 70-78%, delivers 2.5 times the FP32 compute, supports the latest APIs, and does so at 50 W TDP versus the Tesla’s 225 W. The RTX 4050 Mobile is the only sensible choice for gaming, content creation, or any workload that uses DirectX 12 Ultimate or Vulkan 1.4. Its RT and tensor cores provide future-proofing for ray tracing and AI features that the Tesla cannot access.

The Tesla K20m should only be considered by someone with a legacy compute workload that specifically requires Kepler architecture, a 320-bit memory bus, or the higher TMU count. Its higher average benchmark score of 19,089 versus 19,049 is within the margin of error (0.2%), so it offers no practical advantage in overall performance. Given its end-of-life production status, lack of display outputs, and massive power requirements, the Tesla K20m is a poor choice for new builds. The RTX 4050 Mobile is active, supported, and clearly the better investment of the two.

FAQ

Q: Which GPU has a higher average benchmark score?

A: The NVIDIA Tesla K20m has an average benchmark score of 19,089, which is 0.2% higher than the RTX 4050 Mobile’s 19,049.

Q: How much faster is the RTX 4050 Mobile in Geekbench OpenCL?

A: The RTX 4050 Mobile scores 74,748 in Geekbench OpenCL, which is 78.3% higher than the Tesla K20m’s 16,241.

Q: Does the Tesla K20m support ray tracing?

A: No. The Tesla K20m has no RT cores, while the RTX 4050 Mobile features 20 RT cores for ray tracing workloads.

Q: What is the power consumption difference?

A: The Tesla K20m has a TDP of 225 W, while the RTX 4050 Mobile has a TDP of only 50 W.

Q: Which GPU has more memory bandwidth?

A: The Tesla K20m has 208.0 GB/s of bandwidth, slightly higher than the RTX 4050 Mobile’s 192.0 GB/s, despite the latter using faster GDDR6 memory.

Q: Which card supports the newer DirectX version?

A: The RTX 4050 Mobile supports DirectX 12 Ultimate (12_2), while the Tesla K20m is limited to DirectX 12 (11_0).

Specification Differences

| Specification | NVIDIA Tesla K20m | NVIDIA GeForce RTX 4050 Mobile |

|----------------|-------------------|-------------------------------|

| Architecture | Kepler | Ada Lovelace |

| Chip | GK110 | AD107 |

| Process Node | 28 nm | 5 nm |

| Transistors | 7,080 million | 18,900 million |

| Die Size | 561 mm² | 159 mm² |

| Transistor Density | 12.6M / mm² | 118.9M / mm² |

| Base Clock | N/A | 1455 MHz |

| Boost Clock | N/A | 1755 MHz |

| Memory | 5 GB GDDR5 | 6 GB GDDR6 |

| Memory Bus | 320 bit | 96 bit |

| Memory Bandwidth | 208.0 GB/s | 192.0 GB/s |

| Shading Units | 2496 | 2560 |

| TMUs | 208 | 80 |

| ROPs | 40 | 48 |

| RT Cores | N/A | 20 |

| Tensor Cores | N/A | 80 |

| Pixel Rate | 36.71 GPixel/s | 84.24 GPixel/s |

| Texture Rate | 146.8 GTexel/s | 140.4 GTexel/s |

| FP32 Performance | 3.524 TFLOPS | 8.986 TFLOPS |

| FP16 Performance | N/A | 8.986 TFLOPS (1:1) |

| TDP | 225 W | 50 W |

| Slot Width | Dual-slot | IGP |

| Power Connectors | 1x 6-pin + 1x 8-pin | None |

| Bus Interface | PCIe 2.0 x16 | PCIe 4.0 x8 |

| Display Outputs | No outputs | Portable Device Dependent |

| DirectX Support | 12 (11_0) | 12 Ultimate (12_2) |

| Vulkan Support | 1.2.175 | 1.4 |

| Production Status | End-of-life | Active |