GPU Comparison

# Head-to-Head Benchmarks

The benchmark data presents a clear picture: the NVIDIA Quadro M4000M wins both recorded head-to-head tests against the NVIDIA Tesla K80, though the margins are modest rather than decisive. In Geekbench OpenCL, the Quadro M4000M scores 19,989 against the Tesla K80's 18,620, a 7.4% advantage. The Vulkan test shows a slightly larger gap, with the Quadro M4000M reaching 20,971 while the Tesla K80 manages 19,111, a 9.7% lead.

What makes these results intriguing is how they contrast with the raw specifications. The Tesla K80 carries significantly more shading units (2,496 versus 1,280), more texture mapping units (208 versus 80), and nearly double the FP32 throughput (4.113 TFLOPS versus 2.593 TFLOPS). Yet in both recorded workloads, the Quadro M4000M emerges victorious. This suggests that architectural efficiency and clock speeds matter more than sheer core counts in these particular benchmarks.

The average benchmark scores reinforce this narrative. The Quadro M4000M averages 20,480 across its benchmark suite, while the Tesla K80 averages 18,866, a gap of roughly 8.5%. When placed against their nearest rivals, both cards occupy similar competitive territory. The Quadro M4000M sits just 0.3% behind the NVIDIA GeForce RTX 3070 Mobile (20,534) and 0.4% behind the Intel Arc B570 (20,556). The Tesla K80, meanwhile, edges out the NVIDIA GeForce RTX 2070 by 0.4% (18,789) and trails the NVIDIA RTX 2000 Ada Generation by just 0.5% (18,954). These percentile placements, 65th for the Quadro M4000M and 63rd for the Tesla K80, show both cards hovering in similar mid-range territory despite their very different designs.

# Architecture Differences

The architectural divide between these two NVIDIA offerings is substantial. The Quadro M4000M uses the GM204 chip built on Maxwell 2.0 architecture, while the Tesla K80 employs the GK210 chip based on Kepler 2.0. Both are manufactured on a 28 nm process at TSMC, but that is where the similarities end.

The transistor counts tell a story of scale versus efficiency. The Tesla K80 packs 7,100 million transistors onto a 561 mm² die, yielding a transistor density of 12.7M per mm². The Quadro M4000M, by contrast, uses 5,200 million transistors on a smaller 398 mm² die, achieving a higher density of 13.1M per mm². This tighter packing in the Quadro M4000M hints at a more modern design that extracts more performance per transistor.

Clock speeds reveal another fundamental difference. The Quadro M4000M runs at a 975 MHz base clock with a 1013 MHz boost, while the Tesla K80 operates at a much lower 562 MHz base and 824 MHz boost. This clock advantage, roughly 73% higher at base and 23% higher at boost, helps explain how the Quadro M4000M can outperform the Tesla K80 in benchmarks despite having roughly half the shading units. The Tesla K80's higher core count simply cannot compensate for its slower operating frequency in these workloads.

Memory configurations diverge sharply as well. The Quadro M4000M offers 4 GB of GDDR5 on a 256-bit bus, delivering 160.4 GB/s of bandwidth. The Tesla K80 provides 12 GB of GDDR5 on a wider 384-bit bus, achieving 240.6 GB/s. Both use the same 1253 MHz memory clock with 5 Gbps effective speed, but the wider bus gives the Tesla K80 a 50% bandwidth advantage. This makes the Tesla K80 better suited for memory-intensive tasks, even if its compute performance lags in the recorded benchmarks.

The feature sets also reflect their different lineages. The Quadro M4000M supports DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.4. The Tesla K80, being an older compute-focused design, supports DirectX 12 (11_1), OpenGL 4.6, but only Vulkan 1.2.175. Neither card includes ray tracing or tensor cores, which is unsurprising given their respective release periods.

# Where Each One Wins

The Quadro M4000M's strengths lie in graphics-oriented workloads, as evidenced by its 9.7% Vulkan advantage and 7.4% OpenCL lead. Its higher clock speeds and Maxwell 2.0 architecture appear better suited to the kind of immediate-mode rendering and compute tasks these benchmarks represent. The card's 64.83 GPixel/s pixel rate and 81.04 GTexel/s texture rate, both higher than the Tesla K80's 42.85 GPixel/s and 171.4 GTexel/s respectively, suggest it can handle rasterization and pixel processing more efficiently, even though the Tesla K80's texture rate is actually higher due to its 208 TMUs.

The Tesla K80, despite losing both head-to-head benchmarks, has clear advantages in specific scenarios. Its 12 GB memory capacity is triple that of the Quadro M4000M, and its 240.6 GB/s bandwidth provides 50% more memory throughput. For workloads that require large datasets resident in GPU memory, such as deep learning training batches, scientific simulations, or large-scale data processing, the Tesla K80's memory subsystem would be significantly more capable. Its 4.113 TFLOPS FP32 compute also suggests that in compute-bound tasks that scale well with core count, it could outperform the Quadro M4000M, even if the recorded benchmarks do not show this.

The Tesla K80's 300 W TDP and 700 W suggested PSU requirement indicate it is designed for server racks and dedicated compute nodes, not desktop workstations. The Quadro M4000M, at 100 W with no power connectors and an MXM module form factor, is built for mobile workstations. This means the Quadro M4000M wins in any scenario requiring portability or low power draw, while the Tesla K80 is restricted to fixed installations where its power appetite is acceptable.

# FAQ

Q: Which card has the higher average benchmark score?

A: The NVIDIA Quadro M4000M averages 20,480 across its benchmarks, compared to 18,866 for the NVIDIA Tesla K80. This represents an approximately 8.5% overall advantage for the Quadro M4000M.

Q: How do the two cards compare in Vulkan performance specifically?

A: The Quadro M4000M scores 20,971 in Geekbench Vulkan against the Tesla K80's 19,111. This gives the Quadro M4000M a 9.7% lead in this particular test.

Q: Does the Tesla K80 have any memory advantages?

A: Yes. The Tesla K80 offers 12 GB of GDDR5 memory on a 384-bit bus with 240.6 GB/s bandwidth. The Quadro M4000M provides 4 GB on a 256-bit bus with 160.4 GB/s. The Tesla K80 delivers triple the capacity and 50% more bandwidth.

Q: What is the transistor density difference between these two chips?

A: The Quadro M4000M's GM204 chip achieves 13.1M transistors per mm², while the Tesla K80's GK210 chip manages 12.7M per mm². Both are fabricated on TSMC's 28 nm process.

Q: How does the Quadro M4000M compare to the GeForce RTX 3070 Mobile?

A: The Quadro M4000M's average score of 20,480 is just 0.3% behind the GeForce RTX 3070 Mobile's 20,534, placing them in essentially the same performance tier.

Q: Which card supports a newer version of Vulkan?

A: The Quadro M4000M supports Vulkan 1.4, while the Tesla K80 only supports Vulkan 1.2.175. The Quadro M4000M also supports DirectX 12 (12_1) versus the Tesla K80's DirectX 12 (11_1).

# The Verdict

The data suggests a straightforward choice for most users: the NVIDIA Quadro M4000M is the better performer in the recorded benchmarks. It wins both head-to-head tests, achieves a higher average score, and ranks at the 65th percentile versus the Tesla K80's 63rd. Its higher clock speeds, more modern Maxwell 2.0 architecture, and superior API support make it the more capable card for general compute and graphics tasks.

However, the Tesla K80 is not without its merits. For workloads that demand large memory capacity, the 12 GB versus 4 GB difference is substantial, or that benefit from the 50% higher memory bandwidth, the Tesla K80 could be the better choice. Its 4.113 TFLOPS FP32 throughput is also notably higher, suggesting that in compute-heavy scenarios that fully utilize its 2,496 shading units, it could outperform the Quadro M4000M despite its slower clocks.

The power and form factor differences also point to different use cases. The Quadro M4000M's 100 W TDP and MXM module design make it suitable for mobile workstations where power efficiency and space are critical. The Tesla K80's 300 W TDP, dual-slot design, 267 mm length, and 700 W PSU requirement restrict it to desktop or server environments where such constraints are less relevant.

For users seeking a versatile GPU for workstation tasks, the Quadro M4000M is the data-supported choice. For those running memory-intensive compute workloads in a fixed installation, the Tesla K80's capacity advantages could prove decisive. The benchmark data cannot settle that second question, but it clearly favors the Quadro M4000M in the tests that were recorded.

# Specification Differences

| Specification | NVIDIA Quadro M4000M | NVIDIA Tesla K80 |

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

| Architecture | Maxwell 2.0 | Kepler 2.0 |

| Chip | GM204 | GK210 |

| Process Node | 28 nm | 28 nm |

| Transistors | 5,200 million | 7,100 million |

| Die Size | 398 mm² | 561 mm² |

| Transistor Density | 13.1M / mm² | 12.7M / mm² |

| Base Clock | 975 MHz | 562 MHz |

| Boost Clock | 1013 MHz | 824 MHz |

| Memory Size | 4 GB | 12 GB |

| Memory Bus Width | 256 bit | 384 bit |

| Memory Bandwidth | 160.4 GB/s | 240.6 GB/s |

| Shading Units | 1280 | 2496 |

| TMUs | 80 | 208 |

| ROPs | 64 | 48 |

| Pixel Rate | 64.83 GPixel/s | 42.85 GPixel/s |

| Texture Rate | 81.04 GTexel/s | 171.4 GTexel/s |

| FP32 | 2.593 TFLOPS | 4.113 TFLOPS |

| TDP | 100 W | 300 W |

| Slot Width | MXM Module | Dual-slot |

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

| Suggested PSU |, | 700 W |

| Display Outputs | Portable Device Dependent | No outputs |

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

| Vulkan | 1.4 | 1.2.175 |

| Length |, | 267 mm (10.5 inches) |

| Release Date | 2015-08-17 | 2014-11-16 |

| Generation | Quadro Maxwell-M (Mx000M) | Tesla Kepler (Kxx) |

| Predecessor | Quadro Kepler-M | Tesla Fermi |

| Successor | Quadro Pascal-M | Tesla Maxwell |