NVIDIA GeForce GTX TITAN Z vs NVIDIA Tesla K40m Comparison

Head-to-Head Benchmarks

The database contains one directly comparable benchmark between these two NVIDIA Kepler cards: Geekbench OpenCL. In that test, the NVIDIA GeForce GTX TITAN Z records a score of 25,465 against the NVIDIA Tesla K40m's 19,885. The measured delta is 28.1%, making the TITAN Z the clear winner in compute performance as recorded by this workload.

Looking at the broader benchmark context, the TITAN Z's average benchmark score is 23,736. That places it in the 69th percentile of all GPUs in the database. Its nearest rivals include the NVIDIA GeForce RTX 3080 Mobile at 23,628 (0.5% slower), the AMD Radeon RX 9070 at 23,877 (0.6% faster), the NVIDIA GeForce RTX 3070 Ti Mobile at 23,518 (0.9% slower), and the AMD Radeon RX 6800S at 24,063 (1.4% faster). These deltas are all within a narrow band, suggesting the TITAN Z sits in a competitive performance cluster despite its age.

The Tesla K40m, by contrast, has an average benchmark score of 19,885, placing it in the 65th percentile. Its closest rivals are notably lower-performing cards: the AMD FirePro W7000 at 19,905 (0.1% slower), the AMD Radeon RX 6650 XT at 19,765 (0.6% faster), the AMD FirePro D300 at 19,637 (1.3% faster), and the NVIDIA Quadro K5200 at 19,602 (1.4% faster). The K40m's position among these rivals indicates it performs in line with mid-range workstation and consumer GPUs from a later era, which confirms its original high-end positioning.

The single head-to-head result shows a decisive 28.1% advantage for the TITAN Z in OpenCL compute. That is a substantial margin, especially considering both cards share the same GK110B chip, the same 28 nm process node, the same 7,080 million transistor count, and the same 561 mm² die size. The performance gap must therefore come from other specification differences, which the following sections explore.

FAQ

Q: Which card has a higher OpenCL benchmark score?

A: The NVIDIA GeForce GTX TITAN Z scores 25,465, while the NVIDIA Tesla K40m scores 19,885. The TITAN Z leads by 28.1% in this specific test.

Q: How do these cards compare to their nearest rivals?

A: The TITAN Z is within 1.4% of four rivals: the AMD Radeon RX 6800S is 1.4% faster, the AMD Radeon RX 9070 is 0.6% faster, the NVIDIA GeForce RTX 3080 Mobile is 0.5% slower, and the NVIDIA GeForce RTX 3070 Ti Mobile is 0.9% slower. The Tesla K40m's closest rival is the AMD FirePro W7000, which is 0.1% slower; the AMD Radeon RX 6650 XT is 0.6% faster, the AMD FirePro D300 is 1.3% faster, and the NVIDIA Quadro K5200 is 1.4% faster.

Q: Do both cards use the same GPU chip?

A: Yes. Both the NVIDIA GeForce GTX TITAN Z and the NVIDIA Tesla K40m are built on the GK110B chip, using NVIDIA's Kepler architecture, fabricated by TSMC on a 28 nm process.

Q: What is the memory difference between the two cards?

A: The TITAN Z has 6 GB of GDDR5 memory on a 384-bit bus with 336.0 GB/s bandwidth. The Tesla K40m has 12 GB of GDDR5 memory on the same 384-bit bus but with lower bandwidth at 288.4 GB/s.

Q: Which card has a higher base clock speed?

A: The Tesla K40m has a base clock of 745 MHz, while the TITAN Z has a base clock of 705 MHz. Both share the same boost clock of 876 MHz.

Q: What are the power requirements for each card?

A: The TITAN Z has a 375 W TDP with a 750 W suggested PSU and requires two 8-pin power connectors. The Tesla K40m has a 245 W TDP with a 550 W suggested PSU and lists no power connectors in the database.

Architecture Differences

Despite sharing the same GK110B chip, the same Kepler architecture, and the same 28 nm TSMC process, the two cards diverge significantly in their design intent and implementation.

The TITAN Z is a dual-GPU card. Its 2,880 shading units, 240 texture mapping units, and 48 render output units are distributed across two GK110B dies, each contributing half of the totals. This is evident from its triple-slot width and 62 mm thickness, which accommodates the dual-board design and the associated cooling solution. The TITAN Z is fundamentally a consumer-oriented product aimed at maximum compute throughput in a single slot footprint, bridging the gap between gaming and professional workloads.

The Tesla K40m, by contrast, is a single-GPU compute card. It uses one GK110B die with the same 2,880 shading units, 240 TMUs, and 48 ROPs, but packages them in a dual-slot design that is 267 mm long. The K40m has no display outputs at all, reflecting its role as a dedicated compute accelerator for data centers and research environments where rendering to a screen is irrelevant. The absence of display outputs also simplifies its power delivery, since it does not need to drive multiple video interfaces.

The memory architecture also differs in ways that reflect their intended use cases. The TITAN Z's 6 GB of GDDR5 is split across its two dies, giving each GPU 3 GB of dedicated memory. This configuration is typical for dual-GPU cards, where each die manages its own memory pool. The Tesla K40m's 12 GB of GDDR5 is allocated to a single die, providing a larger contiguous memory space for compute workloads that require substantial data sets. This makes the K40m better suited for tasks like deep learning training or scientific simulations where memory capacity is a bottleneck.

Clock behavior further distinguishes the two. The TITAN Z runs at a base clock of 705 MHz, while the K40m runs at 745 MHz. Both share a boost clock of 876 MHz. The K40m's higher base clock suggests it can sustain higher frequencies under sustained compute loads, which is a common trait for workstation accelerators designed for long-running jobs. The TITAN Z's lower base clock may reflect thermal constraints from housing two dies in one package.

The API support is identical: both cards support DirectX 12 (11_1), OpenGL 4.6, and Vulkan 1.2.175. The pixel rate and texture rate are also identical at 52.56 GPixel/s and 210.2 GTexel/s, respectively, and both deliver 5.046 TFLOPS of FP32 compute. The differences in real-world performance therefore stem from memory bandwidth, clock behavior, and the dual-GPU vs single-GPU arrangement.

Specification Differences

The following fields differ between the NVIDIA GeForce GTX TITAN Z and the NVIDIA Tesla K40m:

| Specification | NVIDIA GeForce GTX TITAN Z | NVIDIA Tesla K40m |

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

| Generation | GeForce 700 | Tesla Kepler (Kxx) |

| Base clock | 705 MHz | 745 MHz |

| Memory clock | 1750 MHz, 7 Gbps effective | 1502 MHz, 6 Gbps effective |

| Memory size | 6 GB | 12 GB |

| Memory bandwidth | 336.0 GB/s | 288.4 GB/s |

| TDP | 375 W | 245 W |

| Slot width | Triple-slot | Dual-slot |

| Power connectors | 2x 8-pin | None listed |

| Suggested PSU | 750 W | 550 W |

| Display outputs | 2x DVI, 1x HDMI 1.4a, 1x DisplayPort 1.2 | No outputs |

| Dimensions | 267 mm length, 111 mm height, 62 mm width | 267 mm length, height and width not listed |

| Release date | 2014-05-27 | 2013-11-21 |

| Predecessor | GeForce 600 | Tesla Fermi |

| Successor | GeForce 900 | Tesla Maxwell |

| Launch MSRP | 2,999 USD | 7,699 USD |

Shared specifications include the GK110B chip, Kepler architecture, 28 nm process, TSMC foundry, 7,080 million transistors, 561 mm² die size, 12.6M / mm² transistor density, 384-bit memory bus, 2,880 shading units, 240 TMUs, 48 ROPs, 876 MHz boost clock, GDDR5 memory type, 52.56 GPixel/s pixel rate, 210.2 GTexel/s texture rate, 5.046 TFLOPS FP32, PCIe 3.0 x16 interface, DirectX 12 (11_1), OpenGL 4.6, Vulkan 1.2.175, and end-of-life production status.

The most consequential differences are memory capacity (12 GB vs 6 GB), memory bandwidth (288.4 GB/s vs 336.0 GB/s), TDP (245 W vs 375 W), and physical design (dual-slot vs triple-slot, with vs without display outputs). The K40m's higher base clock (745 MHz vs 705 MHz) partially compensates for its lower memory bandwidth in compute tasks.

The Verdict

The data points to a clear split in suitability. The NVIDIA GeForce GTX TITAN Z wins the only direct benchmark comparison, delivering 28.1% higher OpenCL performance than the Tesla K40m. Its higher memory bandwidth (336.0 GB/s vs 288.4 GB/s) and higher effective memory clock (7 Gbps vs 6 Gbps) contribute to this advantage, even though it has half the memory capacity.

The TITAN Z also occupies a stronger position in the overall database ranking. Its average benchmark score of 23,736 places it in the 69th percentile, and its nearest rivals are modern GPUs like the RTX 3080 Mobile and RX 9070, with deltas under 1.5%. This suggests the TITAN Z remains competitive against much newer hardware in the recorded benchmarks.

The Tesla K40m, with an average score of 19,885 and a 65th percentile ranking, is closer to lower-tier rivals like the FirePro W7000 and Quadro K5200. Its 12 GB memory capacity is its standout feature, doubling the TITAN Z's 6 GB. For workloads that demand large memory footprints, the K40m is the better choice. Its lower TDP (245 W vs 375 W) also makes it easier to integrate into dense server environments, and its lack of display outputs is appropriate for headless compute nodes.

For general compute performance, the TITAN Z is the stronger card based on benchmark results. For memory-hungry workloads or power-constrained deployments, the Tesla K40m's larger memory pool and lower power draw give it a specific advantage. The K40m's higher launch MSRP of 7,699 USD versus the TITAN Z's 2,999 USD reflects its enterprise positioning, but the recorded benchmark data shows the TITAN Z delivering superior OpenCL performance.

Users who need maximum compute throughput from a single card should select the TITAN Z. Users who need to load very large datasets into GPU memory, or who operate in environments where power consumption is critical, should consider the Tesla K40m. The TITAN Z wins the performance crown; the K40m wins on capacity and efficiency.