NVIDIA Tesla K20m vs NVIDIA Tesla M4 Comparison

The NVIDIA Tesla K20m and NVIDIA Tesla M4 represent two distinct generations of NVIDIA's compute-oriented accelerator lineup, with the K20m built on the Kepler architecture and the M4 on Maxwell 2.0. The recorded data shows that the Tesla M4 wins the only shared benchmark test, yet the two cards serve very different roles based on their underlying designs. The K20m offers far larger compute resources and memory bandwidth, while the M4 delivers a dramatically lower power draw in a smaller physical footprint. This analysis walks through the head-to-head results, architectural differences, and use-case implications based strictly on the database measurements.

Head-to-Head Benchmarks

The only benchmark test shared between the two cards in the database is Geekbench OpenCL. The Tesla M4 scores 16,932 points, while the Tesla K20m scores 16,241 points. The M4 leads by 4.1 percent in this test, as indicated by the delta percentage of -4.1 from the K20m's perspective. This is a notable result because the K20m has substantially higher raw compute specifications, suggesting that the Maxwell 2.0 architecture in the M4 extracts better real-world performance per unit of theoretical throughput.

Looking at the broader benchmark context, the K20m has an average benchmark score of 19,089 points across its two recorded tests (Geekbench OpenCL at 16,241 and Geekbench Vulkan at 21,936). The M4 has only one recorded benchmark, Geekbench OpenCL at 16,932, which also serves as its average score. The K20m's Vulkan score of 21,936 is significantly higher than its OpenCL score, indicating that the card performs better under that API, though the M4 has no Vulkan result in the database for direct comparison.

Relative to their nearest rivals, the two cards sit in similar performance tiers. The K20m's average score of 19,089 places it within 0.2 percent of the NVIDIA GeForce RTX 4050 Mobile (19,049), within 0.3 percent of the AMD Radeon RX 6600 (19,036), and within 0.3 percent of the NVIDIA Quadro K6000 (19,030). It trails the NVIDIA GeForce GTX 780 (19,164) by 0.4 percent. The M4's average score of 16,932 is 0.5 percent behind the AMD Radeon HD 7970M (17,019), 0.6 percent behind the NVIDIA GeForce GTX 690 (17,037), and 0.9 percent behind the AMD Radeon RX 7600 XT (17,083). The M4 leads the NVIDIA T400 4 GB (16,792) by 0.8 percent. These rival comparisons show the K20m competing with much newer consumer and workstation parts, while the M4 sits closer to older high-end cards.

The percentile rankings reinforce this picture. The K20m sits at the 64th percentile among all GPUs, while the M4 sits at the 60th percentile. The K20m's higher percentile despite a lower OpenCL score reflects its stronger Vulkan performance, which boosts its average. The M4's single benchmark result limits its average, but the OpenCL score alone still places it above 60 percent of all recorded GPUs.

Architecture Differences

The two cards come from different architectures and generations. The K20m uses the GK110 chip under the Kepler architecture, part of the Tesla Kepler (Kxx) generation. The M4 uses the GM206 chip under the Maxwell 2.0 architecture, part of the Tesla Maxwell (Mxx) generation. Both are fabricated on a 28 nm process at TSMC, so the manufacturing node is identical, but the chip designs diverge significantly.

The K20m packs 7,080 million transistors on a 561 mm² die, giving a transistor density of 12.6 million per square millimeter. The M4 has 2,940 million transistors on a 228 mm² die, with a slightly higher density of 12.9 million per square millimeter. The K20m is a massive chip by comparison, with roughly 2.4 times the transistor count and a die more than twice the area. The M4's higher density suggests a more efficient layout, consistent with the architectural improvements in Maxwell.

Compute resources differ sharply. The K20m has 2,496 shading units, 208 texture mapping units, and 40 raster output units. The M4 has 1,024 shading units, 64 texture mapping units, and 32 raster output units. The K20m has nearly 2.5 times the shading units and more than 3 times the texture units. Pixel fill rates are close, however: the K20m achieves 36.71 GPixel/s versus the M4's 34.30 GPixel/s, a narrow margin. Texture fill rates diverge more, with the K20m at 146.8 GTexel/s and the M4 at 68.61 GTexel/s. Floating-point performance (FP32) also favors the K20m, which delivers 3.524 TFLOPS versus 2.195 TFLOPS for the M4.

Memory configurations differ substantially. The K20m has 5 GB of GDDR5 on a 320-bit bus, producing 208.0 GB/s of bandwidth. The M4 has 4 GB of GDDR5 on a 128-bit bus, yielding 88.00 GB/s. The K20m's memory clock is 1300 MHz with 5.2 Gbps effective transfer rate, while the M4 runs at 1375 MHz with 5.5 Gbps effective. The M4's memory runs faster per pin, but the K20m's much wider bus gives it over 2.3 times the total bandwidth.

Clock behavior also differs. The K20m has no recorded base or boost clock in the database, while the M4 has a base clock of 872 MHz and a boost clock of 1072 MHz. This means the K20m's performance figures rely on its fixed clock behavior, whereas the M4 can dynamically raise its clock under load.

The power profiles are dramatically different. The K20m has a TDP of 225 W, uses a dual-slot cooling layout, and requires both a 6-pin and an 8-pin power connector. The M4 has a TDP of 50 W, uses a single-slot layout, and has no power connectors listed, suggesting it draws power entirely from the PCIe slot. The suggested PSU ratings reflect this: 550 W for the K20m versus 250 W for the M4. The M4 is a low-power accelerator, while the K20m is a high-consumption compute card.

Interface and API support also differ. The K20m uses PCIe 2.0 x16, while the M4 uses PCIe 3.0 x16. Both have no display outputs, consistent with their compute-only roles. The K20m supports DirectX 12 (11_0), OpenGL 4.6, and Vulkan 1.2.175. The M4 supports DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.4. The M4 has a higher DirectX feature level and a newer Vulkan version, reflecting its later release.

Physical dimensions are only partially recorded. The K20m measures 267 mm in length (10.5 inches). The M4's dimensions are not listed. The K20m's dual-slot design contrasts with the M4's single-slot, which matters for dense server deployments.

Where Each One Wins

The M4 wins the only direct head-to-head benchmark, the Geekbench OpenCL test, by 4.1 percent. This suggests that for applications relying on OpenCL compute, the M4 delivers better performance despite having far fewer shading units and lower theoretical TFLOPS. The Maxwell 2.0 architecture appears more efficient at executing OpenCL workloads, possibly due to better instruction scheduling or memory access patterns.

The K20m wins in scenarios that benefit from raw compute throughput. Its 3.524 TFLOPS of FP32 performance exceeds the M4's 2.195 TFLOPS by roughly 60 percent. Applications that are heavily shader-bound, such as large-scale floating-point simulations or dense matrix operations, would favor the K20m. The K20m's 208.0 GB/s memory bandwidth versus 88.00 GB/s also gives it a decisive advantage in memory-intensive workloads, such as large dataset processing or multi-stream data analysis. The K20m's higher texture rate of 146.8 GTexel/s versus 68.61 GTexel/s further supports texture-heavy compute tasks.

The M4 wins in power-constrained environments. With a TDP of 50 W versus 225 W, the M4 consumes less than a quarter of the power while still achieving a higher OpenCL score. This means the M4 can be deployed in systems with smaller power supplies (250 W suggested versus 550 W) and in single-slot configurations, allowing higher card density per server. The M4's lack of external power connectors simplifies cabling and reduces installation complexity. The M4 also supports PCIe 3.0, doubling the bus transfer rate compared to the K20m's PCIe 2.0, which helps with data transfer to and from the host system.

The K20m wins in raw capacity. Its 5 GB of memory exceeds the M4's 4 GB, and its 320-bit bus provides 208.0 GB/s bandwidth, which is essential for large working sets that do not fit in smaller memory pools. The K20m's 2,496 shading units and 208 texture units provide headroom for workloads that scale with core count, even if the OpenCL benchmark does not reflect that advantage.

The M4 wins on software compatibility with newer APIs. Its Vulkan 1.4 support and DirectX 12 (12_1) feature level exceed the K20m's Vulkan 1.2.175 and DirectX 12 (11_0). Applications built against newer API versions will run more efficiently on the M4.

The Verdict

The data points to a clear split. For users prioritizing raw compute resources, memory bandwidth, and high memory capacity, the NVIDIA Tesla K20m is the stronger choice. Its 3.524 TFLOPS, 208.0 GB/s bandwidth, and 5 GB memory provide a substantial theoretical foundation for demanding compute tasks. The K20m's higher percentile ranking (64th versus 60th) and higher average benchmark score (19,089 versus 16,932) also indicate stronger overall performance when accounting for its Vulkan result.

For users prioritizing efficiency, density, and modern API support, the NVIDIA Tesla M4 is the better option. It wins the OpenCL head-to-head by 4.1 percent, consumes 50 W versus 225 W, fits in a single slot, requires no external power connectors, and supports PCIe 3.0 and newer API versions. The M4's nearest rivals include the NVIDIA T400 4 GB, which is a similar low-profile workstation card, and it beats that card by 0.8 percent.

The K20m's nearest rivals include the NVIDIA Quadro K6000, which has nearly the same average score (19,030, delta 0.3 percent), indicating that the K20m performs at a level comparable to a much newer professional card. The K20m also matches the NVIDIA GeForce GTX 780 within 0.4 percent, suggesting its compute performance remains relevant despite its age.

The M4's rivals include the AMD Radeon HD 7970M and NVIDIA GeForce GTX 690, both of which slightly outperform it in the database, but the M4's power advantage is not captured in those scores. The M4's 50 W TDP makes it suitable for passive cooling or low-power servers, while the K20m's 225 W TDP requires robust cooling and power delivery.

There is no single winner across all criteria. The K20m is the compute-workhorse choice, while the M4 is the efficiency-focused choice. The recorded data favors the M4 in the only direct benchmark, but the K20m's broader capabilities in raw throughput and memory bandwidth make it the pick for workloads that can use those resources. The M4 is the pick for environments where power and space are at a premium.

FAQ

Q: Which GPU has a higher average benchmark score?

A: The NVIDIA Tesla K20m has an average benchmark score of 19,089, while the NVIDIA Tesla M4 has an average score of 16,932.

Q: What is the difference in the Geekbench OpenCL test?

A: The NVIDIA Tesla M4 scores 16,932 versus the K20m's 16,241, giving the M4 a 4.1 percent lead.

Q: How do the memory bandwidths compare?

A: The K20m has 208.0 GB/s bandwidth from a 320-bit bus, while the M4 has 88.00 GB/s from a 128-bit bus.

Q: What is the power consumption difference?

A: The K20m has a TDP of 225 W, while the M4 has a TDP of 50 W. The K20m requires a 550 W suggested PSU, while the M4 requires 250 W.

Q: Which GPU supports a newer Vulkan version?

A: The M4 supports Vulkan 1.4, while the K20m supports Vulkan 1.2.175.

Q: What are the nearest rivals for each card?

A: The K20m's nearest rivals include the NVIDIA GeForce RTX 4050 Mobile (delta 0.2 percent) and AMD Radeon RX 6600 (delta 0.3 percent). The M4's nearest rivals include the NVIDIA T400 4 GB (delta 0.8 percent) and AMD Radeon HD 7970M (delta -0.5 percent).

Specification Differences

| Specification | NVIDIA Tesla K20m | NVIDIA Tesla M4 |

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

| Architecture | Kepler | Maxwell 2.0 |

| Generation | Tesla Kepler (Kxx) | Tesla Maxwell (Mxx) |

| Chip | GK110 | GM206 |

| Process Node | 28 nm | 28 nm |

| Transistors | 7,080 million | 2,940 million |

| Die Size | 561 mm² | 228 mm² |

| Transistor Density | 12.6M / mm² | 12.9M / mm² |

| Base Clock | Not listed | 872 MHz |

| Boost Clock | Not listed | 1072 MHz |

| Memory Clock | 1300 MHz, 5.2 Gbps effective | 1375 MHz, 5.5 Gbps effective |

| Memory Size | 5 GB | 4 GB |

| Memory Bus Width | 320 bit | 128 bit |

| Memory Bandwidth | 208.0 GB/s | 88.00 GB/s |

| Shading Units | 2496 | 1024 |

| TMUs | 208 | 64 |

| ROPs | 40 | 32 |

| Pixel Rate | 36.71 GPixel/s | 34.30 GPixel/s |

| Texture Rate | 146.8 GTexel/s | 68.61 GTexel/s |

| FP32 | 3.524 TFLOPS | 2.195 TFLOPS |

| TDP | 225 W | 50 W |

| Slot Width | Dual-slot | Single-slot |

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

| Suggested PSU | 550 W | 250 W |

| Bus Interface | PCIe 2.0 x16 | PCIe 3.0 x16 |

| DirectX | 12 (11_0) | 12 (12_1) |

| Vulkan | 1.2.175 | 1.4 |

| Length | 267 mm (10.5 inches) | Not listed |

| Release Date | 2013-01-04 | 2015-11-09 |

| Predecessor | Tesla Fermi | Tesla Kepler |

| Successor | Tesla Maxwell | Tesla Pascal |

| Launch MSRP | 3,199 USD | Not listed |