NVIDIA Tesla M10 vs NVIDIA TITAN V CEO Edition Comparison

# NVIDIA Tesla M10 vs NVIDIA TITAN V CEO Edition

The NVIDIA Tesla M10 and NVIDIA TITAN V CEO Edition represent two vastly different eras and purposes in NVIDIA’s lineup, despite sharing the same 267 mm board length. The Tesla M10, a Maxwell-based compute accelerator from 2016, was designed for virtualization and datacenter workloads, while the TITAN V CEO Edition, a Volta-based powerhouse from 2018, targets high-end compute with massive memory and tensor core acceleration. Benchmark data shows a curious split: the Tesla M10 averages 9724 across its two Geekbench tests, while the TITAN V CEO Edition averages 9037 across its two Passmark tests. However, these averages are not directly comparable because they use different benchmark suites, and each card’s percentile ranking (47th vs 45th) places them near the middle of all GPUs, though for very different reasons.

The Verdict

The data presents a clear but nuanced picture. For raw compute throughput, the TITAN V CEO Edition is in a different league entirely, with 14.90 TFLOPS of FP32 performance versus the Tesla M10’s 1.672 TFLOPS — a nearly 9x advantage. The TITAN V also delivers 29.80 TFLOPS of FP16 performance (2:1 ratio), while the Tesla M10 has no FP16 capability listed at all. In memory bandwidth, the gap is even more extreme: 868.4 GB/s for the TITAN V versus 83.20 GB/s for the Tesla M10, a 10.4x difference. If your workload demands massive parallel compute, large datasets, or tensor operations, the TITAN V CEO Edition is the only rational choice from this data.

However, the benchmark scores tell a more complicated story. The Tesla M10 scores 10318 in Geekbench OpenCL and 9130 in Geekbench Vulkan, averaging 9724. The TITAN V CEO Edition scores 1086 in Passmark G2D and 16988 in Passmark G3D, averaging 9037. The TITAN V’s G3D score of 16988 is exceptionally high, but its G2D score of 1086 drags the average down. Meanwhile, the Tesla M10’s nearest rivals include the GeForce GTX 1070 (avg 9780, delta -0.6%) and Quadro P4000 (avg 9665, delta 0.6%), showing it sits in capable mid-range territory. The TITAN V’s nearest rivals are far more modest — the GeForce GTX 660 (avg 9022, delta 0.2%) and GeForce GTX 560 (avg 9058, delta -0.2%) — which suggests its average is pulled down by the G2D component, not representative of its compute strength.

Who should pick which? For datacenter virtualization, multi-tenant GPU workloads, or any scenario where the 8 GB GDDR5 memory and 640 shading units of the Tesla M10 are sufficient, the data shows it as a competent, lower-power option at 225 W TDP. For AI research, scientific computing, or any task leveraging FP16 or tensor cores, the TITAN V CEO Edition’s 5120 shading units, 640 tensor cores, and 32 GB HBM2 memory make it the overwhelming choice. The TITAN V also offers display outputs (1x HDMI 2.0, 3x DisplayPort 1.4a) while the Tesla M10 has none, making it usable in workstation scenarios.

Architecture Differences

The architectural gap between these two GPUs is generational. The Tesla M10 uses the GM107 chip on a 28 nm process from TSMC, with 1,870 million transistors packed into a 148 mm² die — a transistor density of 12.6 million per mm². The TITAN V CEO Edition uses the GV100 chip on a 12 nm process, also from TSMC, with 21,100 million transistors on an 815 mm² die — a density of 25.9 million per mm². That is 11.3x more transistors and 2x the density, reflecting the massive architectural leap from Maxwell to Volta.

Core counts differ dramatically. The Tesla M10 has 640 shading units, 40 texture mapping units, and 16 ROPs. The TITAN V has 5120 shading units (8x more), 320 TMUs (8x more), and 128 ROPs (8x more). The TITAN V also includes 640 tensor cores, which the Tesla M10 lacks entirely. Pixel fill rate jumps from 20.90 GPixel/s to 186.2 GPixel/s (8.9x), and texture fill rate from 52.24 GTexel/s to 465.6 GTexel/s (8.9x). These are not incremental improvements; they represent a complete rethinking of GPU compute.

Memory architecture is fundamentally different. The Tesla M10 uses 8 GB of GDDR5 on a 128-bit bus, yielding 83.20 GB/s bandwidth. The TITAN V uses 32 GB of HBM2 on a 4096-bit bus, yielding 868.4 GB/s — a 10.4x bandwidth increase and 4x capacity increase. The TITAN V also supports DirectX 12 (12_1) versus the Tesla M10’s DirectX 12 (11_0), indicating better feature-level support for modern graphics APIs, though both support OpenGL 4.6 and Vulkan 1.4.

FAQ

Q: Which card has better benchmark scores overall?

A: It depends on the benchmark. The Tesla M10 averages 9724 across Geekbench OpenCL (10318) and Vulkan (9130). The TITAN V CEO Edition averages 9037 across Passmark G2D (1086) and G3D (16988). The TITAN V’s G3D score is far higher, but its G2D score is very low, creating a misleading average.

Q: Is the TITAN V CEO Edition worth the extra power draw?

A: The TITAN V requires 250 W TDP versus 225 W for the Tesla M10, and needs a 600 W PSU versus 550 W. The extra 25 W buys 14.90 TFLOPS FP32 versus 1.672 TFLOPS, plus tensor cores and 10.4x memory bandwidth — a massive performance-per-watt improvement.

Q: Can the Tesla M10 handle modern compute workloads?

A: The Tesla M10 supports DirectX 12 (11_0), OpenGL 4.6, and Vulkan 1.4, with 1.672 TFLOPS FP32. It can run many workloads, but its 83.20 GB/s bandwidth and 8 GB memory limit it compared to the TITAN V’s 868.4 GB/s and 32 GB.

Q: Which card has better memory for large datasets?

A: The TITAN V CEO Edition, with 32 GB HBM2 and 868.4 GB/s bandwidth, versus the Tesla M10’s 8 GB GDDR5 at 83.20 GB/s. The TITAN V holds 4x more data and moves it 10.4x faster.

Q: Do both cards support display outputs?

A: No. The Tesla M10 has no display outputs, while the TITAN V CEO Edition has 1x HDMI 2.0 and 3x DisplayPort 1.4a. The TITAN V can drive monitors; the Tesla M10 cannot.

Q: Which card is more efficient per transistor?

A: The TITAN V, at 25.9M transistors per mm² versus 12.6M for the Tesla M10, and it delivers 8x more shading units, 8x more TMUs and ROPs, and tensor cores with only 11.3x more transistors.

Specification Differences

The two cards differ in nearly every measurable specification. The Tesla M10 uses the GM107 chip on 28 nm, while the TITAN V uses GV100 on 12 nm. Transistors jump from 1,870 million to 21,100 million, die size from 148 mm² to 815 mm², and density from 12.6M to 25.9M per mm². Clock speeds differ: base 1033 MHz vs 1200 MHz, boost 1306 MHz vs 1455 MHz. Memory is the starkest contrast: 8 GB GDDR5 on 128-bit at 83.20 GB/s versus 32 GB HBM2 on 4096-bit at 868.4 GB/s. Shading units go from 640 to 5120, TMUs from 40 to 320, ROPs from 16 to 128. The TITAN V adds 640 tensor cores; the Tesla M10 has none. Pixel rate: 20.90 vs 186.2 GPixel/s. Texture rate: 52.24 vs 465.6 GTexel/s. FP32: 1.672 vs 14.90 TFLOPS. FP16: none vs 29.80 TFLOPS (2:1). TDP: 225 W vs 250 W. Power connectors: 1x 8-pin vs 1x 6-pin + 1x 8-pin. PSU: 550 W vs 600 W. Display outputs: none vs 1x HDMI 2.0 + 3x DisplayPort 1.4a. DirectX: 12 (11_0) vs 12 (12_1). Both are dual-slot, 267 mm long, PCIe 3.0 x16, with 4.6 OpenGL and 1.4 Vulkan. Release dates: 2016-05-17 vs 2018-06-20. Predecessors: Tesla Kepler vs GeForce 900; successors: Tesla Pascal vs GeForce 20.

Head-to-Head Benchmarks

There are no direct head-to-head benchmark results in the data, so the comparison relies on individual scores and specification-derived performance. The Tesla M10’s Geekbench OpenCL score of 10318 and Vulkan score of 9130 show balanced performance across APIs, with the OpenCL score 13% higher than Vulkan. The TITAN V’s Passmark G3D score of 16988 is exceptionally high — nearly 15.6x its own G2D score of 1086 — indicating that the card is optimized for 3D/compute tasks, not 2D desktop rendering. This G2D score of 1086 is what drags its average below the Tesla M10’s average (9037 vs 9724), despite the TITAN V having vastly superior hardware.

Comparing across suites, the TITAN V’s G3D score of 16988 dwarfs the Tesla M10’s highest score of 10318 by 64.6%. In raw compute terms, the TITAN V’s FP32 of 14.90 TFLOPS is 8.9x the Tesla M10’s 1.672 TFLOPS, and its texture rate of 465.6 GTexel/s is 8.9x the Tesla M10’s 52.24 GTexel/s. The TITAN V’s pixel rate of 186.2 GPixel/s is 8.9x the Tesla M10’s 20.90 GPixel/s. These multiplier consistencies (all ~8.9x) reflect the identical scaling in shading units, TMUs, and ROPs — the TITAN V has exactly 8x more of each, and the higher boost clock accounts for the extra ~11% performance.

The nearest rival data reinforces the positioning. The Tesla M10 sits within 0.7% of the Quadro P4000 (9665) and within 0.6% of the GTX 1070 (9780), placing it among solid mid-range workstation cards. The TITAN V’s nearest rivals are the GTX 660 (9022, +0.2%) and GTX 560 (9058, -0.2%) — cards from 2012-era that are far less capable, which suggests the TITAN V’s average is an artifact of the G2D test, not a true reflection of its compute abilities. The TITAN V’s percentile of 45 versus the Tesla M10’s 47 is misleading; the TITAN V’s G3D score alone would rank much higher.

Where Each One Wins

The Tesla M10 wins in scenarios where its lower power draw and smaller memory footprint are advantages. At 225 W TDP with a 550 W PSU requirement, it fits into more modest server configurations. Its 8 GB GDDR5 memory is adequate for virtualization workloads where multiple small GPU instances are needed rather than one massive compute context. Its Geekbench scores — 10318 OpenCL and 9130 Vulkan — are respectable for its class, and its proximity to the GTX 1070 (delta -0.6%) and Quadro P4000 (delta 0.6%) shows it competes well with contemporary mid-range options. The lack of display outputs makes it purely a compute accelerator, which is appropriate for datacenter use.

The TITAN V CEO Edition wins in every performance-critical category. Its 14.90 TFLOPS FP32 and 29.80 TFLOPS FP16 make it a compute monster. Its 640 tensor cores enable AI and deep learning workloads that the Tesla M10 cannot handle at all. Its 32 GB HBM2 memory with 868.4 GB/s bandwidth allows datasets of unprecedented size to stay on-card, eliminating PCIe transfers. Its 5120 shading units and 128 ROPs deliver pixel and texture rates of 186.2 GPixel/s and 465.6 GTexel/s, respectively. The G3D score of 16988 confirms its dominance in 3D rendering. Its display outputs make it usable for workstation tasks, and its DirectX 12 (12_1) support ensures compatibility with modern graphics features.

In use-case terms, the Tesla M10 is for server virtualization, remote desktop, and light compute where multiple cards are deployed and power is a concern. The TITAN V CEO Edition is for single-GPU high-performance compute, AI inference, scientific simulation, and any task where memory bandwidth is the bottleneck. The data leaves no ambiguity: for raw performance, the TITAN V is the clear victor; for density and efficiency in multi-GPU datacenter setups, the Tesla M10 has its niche.