NVIDIA T1000 vs NVIDIA Tesla M40 Comparison

Where Each One Wins

The recorded benchmark data splits cleanly between these two NVIDIA workstation cards. The Tesla M40 wins both recorded head-to-head tests, taking the Geekbench OpenCL and Vulkan comparisons. The T1000 does not win any of the recorded tests in this comparison. This is not a close contest in terms of raw score output, but the nature of the wins matters more than the simple count.

The Tesla M40’s victories are anchored in its massive compute configuration. It fields 3072 shading units, 192 texture mapping units, and 96 render output units. That hardware scale translates directly into a 6.832 TFLOPS FP32 rating, which is roughly 2.7 times the T1000’s 2.500 TFLOPS. For workloads that hammer raw shading throughput, the M40 is the clear choice. The OpenCL test reflects this strength, as the M40 posts 39192 against the T1000’s 37704.

The Vulkan test shows an even wider gap. The M40 scores 44602, while the T1000 manages 34874. That is a 27.9% delta, the largest single margin in the entire comparison. Vulkan tends to expose driver overhead and raw geometry throughput, and the M40’s older Maxwell architecture still has enough brute force to dominate here. The T1000’s Turing architecture brings newer features, but the recorded data shows it cannot translate those features into a Vulkan win.

Where the T1000 might find its footing is in efficiency and practical deployment, though the benchmark scores do not reward it. The T1000 draws only 50 W, runs single-slot, and requires no auxiliary power connectors. The M40 draws 250 W, needs an 8-pin EPS connector, and occupies dual slots. The T1000 also has four mini-DisplayPort 1.4a outputs, while the M40 has no display outputs at all. For a desktop workstation that needs to drive monitors, the T1000 is the only option. The data does not capture this directly, but the specification fields make it clear.

Architecture Differences

The two cards come from different architectural generations and target different use cases. The Tesla M40 uses the GM200 chip, built on Maxwell 2.0 architecture, fabricated on a 28 nm process at TSMC. The die is massive at 601 mm² and contains 8,000 million transistors. The T1000 uses the TU117 chip, built on Turing architecture, fabricated on a 12 nm process, also at TSMC. Its die is much smaller at 200 mm², holding 4,700 million transistors. The transistor density tells the story: the T1000 packs 23.5 million transistors per mm², while the M40 manages only 13.3 million per mm². Turing is the denser design, but Maxwell 2.0 compensates with sheer scale.

Memory configurations diverge sharply. The M40 carries 12 GB of GDDR5 on a 384 bit bus, yielding 288.4 GB/s of bandwidth. The T1000 has 4 GB of GDDR6 on a 128 bit bus, producing 160.0 GB/s. Even though the T1000 uses newer memory technology, its narrower bus and smaller capacity hold it back. The M40’s memory bandwidth is 80% higher, which matters for large datasets and high-resolution textures.

Clock speeds favor the T1000. It runs at a 1065 MHz base and 1395 MHz boost, while the M40 sits at 948 MHz base and 1112 MHz boost. The T1000 also has a higher effective memory clock at 10 Gbps versus the M40’s 6 Gbps. But the T1000’s superior clocks cannot overcome its smaller core count. The M40 has 3072 shading units against the T1000’s 896, and 192 TMUs against 56. The M40 also has 96 ROPs versus 32.

Feature support is identical for the APIs that matter: both support DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.4. Neither card has ray tracing cores or tensor cores, so the Turing generation advantage is limited to process efficiency and clock speed. The T1000 does support FP16 at 5.000 TFLOPS with a 2:1 ratio, while the M40 has no recorded FP16 capability. That could be relevant for mixed-precision workloads, but the benchmark data does not test it.

Head-to-Head Benchmarks

The Geekbench OpenCL test opens the comparison. The Tesla M40 scores 39192, and the T1000 scores 37704. The M40 wins by 3.9%. That is a modest margin, closer than the raw specification differences might suggest. The T1000’s higher clocks and newer memory help it close the gap, but the M40’s 288.4 GB/s bandwidth and 3072 cores still carry the day. For OpenCL workloads that scale across many cores, the M40’s architecture is better suited.

The Vulkan test is where the M40 runs away. It scores 44602 against the T1000’s 34874, a 27.9% delta. This is the decisive benchmark of the pair. Vulkan’s lower-level API tends to reward raw throughput and driver efficiency. The M40’s 96 ROPs and 213.5 GTexel/s texture rate give it a clear advantage in fill-rate-bound scenes. The T1000’s 44.64 GPixel/s pixel rate and 78.12 GTexel/s texture rate are less than half the M40’s 106.8 GPixel/s and 213.5 GTexel/s. The data suggests the M40 is disproportionately strong in Vulkan relative to its OpenCL showing.

Relative to the wider market, the M40 sits at the 83rd percentile of all GPUs, while the T1000 sits at the 80th. The M40’s average benchmark score is 41897, and the T1000’s is 36289. That is a 15.5% gap in average score. The M40’s nearest rival, the Tesla M40 24 GB, scores 41707, just 0.5% lower. The T1000’s nearest rival, the AMD Radeon RX 5300M, scores 36529, which is 0.7% higher than the T1000. The T1000 is effectively trading blows with mobile-class GPUs, while the M40 is competing with high-end desktop parts like the RTX 3080 Ti, which scores 41187.

FAQ

Q: Which card has a higher average benchmark score?

A: The Tesla M40 has an average benchmark score of 41897, while the T1000 has 36289. The M40 leads by roughly 15.5%.

Q: Does the T1000 win any recorded benchmark?

A: No. The T1000 loses both the Geekbench OpenCL test (37704 vs 39192) and the Geekbench Vulkan test (34874 vs 44602).

Q: What explains the large Vulkan gap between the two cards?

A: The M40 wins the Vulkan test by 27.9%, posting 44602 against 34874. Its higher ROP count (96 vs 32) and pixel rate (106.8 GPixel/s vs 44.64 GPixel/s) likely drive this advantage.

Q: Which card has more memory bandwidth?

A: The Tesla M40 offers 288.4 GB/s over a 384 bit bus, while the T1000 has 160.0 GB/s over a 128 bit bus. The M40 provides 80% more bandwidth.

Q: Are both cards limited to the same API support?

A: Yes, both support DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.4. Neither has ray tracing cores or tensor cores.

Q: How does the T1000 compare to its nearest rival?

A: The T1000’s average score is 36289, and its closest rival, the AMD Radeon RX 5300M, scores 36529, which is 0.7% higher. The T1000 is slightly behind that rival.

The Verdict

The data points to a straightforward choice for raw compute performance: the Tesla M40 wins both recorded benchmarks and holds a 15.5% lead in average score. It also sits higher in the overall GPU percentile ranking at 83 versus the T1000’s 80. For anyone running OpenCL or Vulkan workloads that stress shading, fill rate, and memory bandwidth, the M40 is the stronger card. Its 12 GB memory capacity and 288.4 GB/s bandwidth make it suitable for large datasets, and its 6.832 TFLOPS FP32 rating is more than double the T1000’s.

The T1000 is not without merit, but its advantages are not visible in the benchmark scores. It consumes only 50 W, needs no power connectors, and is single-slot. It also has four mini-DisplayPort outputs, making it usable as a display adapter, which the M40 cannot do. Its 4 GB GDDR6 memory is newer but smaller, and its 5.000 TFLOPS FP16 capability is a feature the M40 lacks entirely. For a low-profile workstation that must drive multiple monitors and run modest compute tasks, the T1000 is the practical pick, but the recorded data shows it is not the performance leader.

The verdict depends on priorities. If the goal is maximum compute throughput in the benchmarks tested, the Tesla M40 is the clear choice. If the goal is a low-power, display-capable card for light workloads, the T1000 fits that role, despite its lower scores. The M40’s 27.9% Vulkan lead is the single strongest argument in this comparison, and it alone justifies choosing the M40 for Vulkan-based applications.

Specification Differences

| Specification | NVIDIA Tesla M40 | NVIDIA T1000 |

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

| Architecture | Maxwell 2.0 | Turing |

| Process Node | 28 nm | 12 nm |

| Transistors | 8,000 million | 4,700 million |

| Die Size | 601 mm² | 200 mm² |

| Transistor Density | 13.3M / mm² | 23.5M / mm² |

| Base Clock | 948 MHz | 1065 MHz |

| Boost Clock | 1112 MHz | 1395 MHz |

| Memory Clock | 1502 MHz, 6 Gbps effective | 1250 MHz, 10 Gbps effective |

| Memory Size | 12 GB | 4 GB |

| Memory Type | GDDR5 | GDDR6 |

| Memory Bus | 384 bit | 128 bit |

| Memory Bandwidth | 288.4 GB/s | 160.0 GB/s |

| Shading Units | 3072 | 896 |

| TMUs | 192 | 56 |

| ROPs | 96 | 32 |

| Pixel Rate | 106.8 GPixel/s | 44.64 GPixel/s |

| Texture Rate | 213.5 GTexel/s | 78.12 GTexel/s |

| FP32 | 6.832 TFLOPS | 2.500 TFLOPS |

| FP16 | None recorded | 5.000 TFLOPS (2:1) |

| TDP | 250 W | 50 W |

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

| Power Connectors | 8-pin EPS | None |

| Suggested PSU | 600 W | 250 W |

| Display Outputs | No outputs | 4x mini-DisplayPort 1.4a |

| Length | 267 mm, 10.5 inches | 156 mm, 6.1 inches |

| Height | Not specified | 69 mm, 2.7 inches |

| Release Date | 2015-11-09 | 2021-05-05 |

| Predecessor | Tesla Kepler | Quadro Volta |

| Successor | Tesla Pascal | Workstation Ampere |