NVIDIA T1000 vs NVIDIA Tesla M40 24 GB Comparison

Where Each One Wins

The recorded benchmark data splits these two NVIDIA workstation cards almost perfectly down the middle, with one win apiece. The NVIDIA Tesla M40 24 GB takes the Geekbench Vulkan test decisively, scoring 45,975 against the T1000's 34,874, a 31.8% advantage. That is a massive gap in a modern graphics API workload, and it shows the M40's raw compute muscle still matters even though it is built on an older architecture. The T1000, by contrast, wins the Geekbench OpenCL test by a narrow margin, 37,704 versus 37,439, a 0.7% edge that is essentially a statistical tie but still counts as a win in the database.

If you are running Vulkan-based applications, the M40 24 GB is the clear pick based on these numbers. The 31.8% lead is not a small difference; it is the kind of gap that changes whether a scene renders smoothly or stutters. The M40 also lands in the 83rd percentile of all GPUs, while the T1000 sits at the 80th, so the M40 has a slightly higher overall standing in the database's aggregate rankings. Its average benchmark score of 41,707 also tops the T1000's 36,289, meaning the M40 is the stronger card on average across the two recorded tests.

The T1000's win in OpenCL is real but marginal, and its overall profile leans toward efficiency and compactness rather than peak performance. The T1000 draws only 50 W, which is one-fifth of the M40's 250 W, and it fits in a single slot at 156 mm long, while the M40 needs a dual-slot layout and 267 mm of space. If your workload is OpenCL-heavy and you care about power draw and physical footprint, the T1000 is the more practical option, but the performance difference in that test is so small that it will not be the deciding factor in most real-world scenarios.

FAQ

Q: Which card performs better in Vulkan workloads?

A: The NVIDIA Tesla M40 24 GB wins the Geekbench Vulkan test by a wide margin, scoring 45,975 compared to the T1000's 34,874, a 31.8% difference. This is the largest performance gap between the two cards in any recorded benchmark.

Q: How close is the OpenCL performance between these two cards?

A: The NVIDIA T1000 edges out the M40 in Geekbench OpenCL, scoring 37,704 versus 37,439, a 0.7% lead. This is within the margin of noise for most workloads, so OpenCL performance should be considered effectively equivalent.

Q: Which card has more memory?

A: The NVIDIA Tesla M40 24 GB has 24 GB of GDDR5 memory on a 384-bit bus, while the T1000 has 4 GB of GDDR6 on a 128-bit bus. The M40's memory bandwidth is 288.4 GB/s versus 160.0 GB/s for the T1000.

Q: Can the T1000 display output to monitors?

A: Yes, the T1000 has four mini-DisplayPort 1.4a outputs. The M40 has no display outputs at all, so it requires a separate GPU for any display tasks.

Q: What is the power consumption difference?

A: The T1000 has a 50 W TDP with no power connectors, while the M40 has a 250 W TDP and requires an 8-pin EPS connector. The suggested power supply is 250 W for the T1000 and 600 W for the M40.

Q: How do these cards rank against all other GPUs?

A: The M40 is in the 83rd percentile of all GPUs with an average benchmark score of 41,707. The T1000 is in the 80th percentile with an average score of 36,289.

Head-to-Head Benchmarks

Looking at the two recorded head-to-head tests, the pattern is clear: the M40 dominates in Vulkan, while the T1000 barely squeaks ahead in OpenCL.

The Geekbench Vulkan result is the headline number. The M40 scores 45,975, and the T1000 scores 34,874, giving the M40 a 31.8% win. To put that in context, the M40's nearest rivals in the database include the NVIDIA GeForce RTX 3080 Ti at 41,187 and the AMD Radeon RX 7650 GRE at 42,723, both of which the M40's average score of 41,707 sits near. But in this specific Vulkan test, the M40 pulls far ahead of its own average, suggesting the test favors its Maxwell architecture's raw throughput. The T1000, by comparison, trails its own average in Vulkan, which drags its overall numbers down.

The Geekbench OpenCL result flips the script, but only slightly. The T1000 wins 37,704 to 37,439, a 0.7% margin. This is the kind of result that shows up in the database as a win but would be imperceptible in actual use. The T1000's OpenCL score aligns closely with its nearest rivals: the AMD Radeon RX 5300M scores 36,529, and the NVIDIA GeForce GTX TITAN X scores 36,530, both within a fraction of the T1000's average of 36,289. The M40's OpenCL score of 37,439 is lower than its average, which means the Vulkan result is doing most of the heavy lifting for its aggregate standing.

What the data does not show is a middle ground. There is no test where both cards perform comparably and the outcome depends on other factors. The two tests are sharply divergent: one is a landslide for the M40, the other is a photo finish for the T1000. If your workload leans on Vulkan, the M40 is the obvious choice. If it leans on OpenCL, the T1000's win is so narrow that other factors like power, size, and memory capacity will likely matter more than the raw score.

Specification Differences

The specifications tell a story of two very different design philosophies. The M40 is a high-performance compute card from 2015, built for server racks and rendering farms. The T1000 is a 2021 workstation card designed for desktop integration and low-power operation.

Memory is the biggest differentiator. The M40 has 24 GB of GDDR5 on a 384-bit bus, delivering 288.4 GB/s of bandwidth. The T1000 has 4 GB of GDDR6 on a 128-bit bus, delivering 160.0 GB/s. That is a six-fold difference in capacity and nearly a two-fold difference in bandwidth. For large datasets, 3D textures, or multi-GPU compute tasks, the M40's memory advantage is enormous.

Compute resources follow the same pattern. The M40 has 3,072 shading units, 192 texture mapping units, and 96 raster output units. The T1000 has 896 shading units, 56 TMUs, and 32 ROPs. The M40's pixel rate is 106.8 GPixel/s versus 44.64 GPixel/s for the T1000, and its texture rate is 213.5 GTexel/s versus 78.12 GTexel/s. The FP32 throughput is 6.832 TFLOPS for the M40 and 2.500 TFLOPS for the T1000, a 2.7x advantage for the older card. The T1000 does have FP16 capability at 5.000 TFLOPS with a 2:1 ratio, which the M40 lacks entirely.

Clock speeds favor the T1000. Its base clock is 1065 MHz with a boost of 1395 MHz, while the M40 runs at 948 MHz base and 1112 MHz boost. The T1000's memory runs at 1250 MHz with 10 Gbps effective, while the M40's memory runs at 1502 MHz with 6 Gbps effective. But the T1000's higher clocks cannot overcome the M40's massive resource advantage in raw compute.

Physical specifications diverge sharply. The M40 is a dual-slot card at 267 mm (10.5 inches) long, with a 250 W TDP and an 8-pin EPS power connector. It has no display outputs. The T1000 is a single-slot card at 156 mm (6.1 inches) long and 69 mm (2.7 inches) high, with a 50 W TDP, no power connectors, and four mini-DisplayPort 1.4a outputs. The suggested power supply is 600 W for the M40 and 250 W for the T1000.

Architecture Differences

The M40 uses the GM200 chip built on TSMC's 28 nm process, representing the Maxwell 2.0 architecture. It packs 8,000 million transistors into a 601 mm² die, giving a transistor density of 13.3 million per square millimeter. The M40 belongs to the Tesla Maxwell (Mxx) generation, and its production status is end-of-life, with Tesla Kepler as its predecessor and Tesla Pascal as its successor.

The T1000 uses the TU117 chip built on TSMC's 12 nm process, representing the Turing architecture. It has 4,700 million transistors in a 200 mm² die, giving a transistor density of 23.5 million per square millimeter, which is significantly higher than the M40 despite the older process. The T1000 belongs to the Quadro Turing (Tx000) generation, with Quadro Volta as its predecessor and Workstation Ampere as its successor.

The architectural differences are not just about node size. Maxwell 2.0 is a compute-focused design with no dedicated ray tracing or tensor cores, and the M40's feature set reflects that. Turing, while also lacking RT and tensor cores in this TU117 implementation, brings architectural improvements in geometry processing and memory compression that the 12 nm process enables. The T1000 supports FP16 at 5.000 TFLOPS with a 2:1 ratio, a feature Maxwell 2.0 does not offer at all.

Both cards support DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.4, so API compatibility is identical. The M40's release date is November 2015, while the T1000's is May 2021, a gap of more than five years. The process node difference, 28 nm versus 12 nm, explains why the T1000 can deliver comparable compute in a fraction of the power envelope. The M40's 250 W TDP versus the T1000's 50 W TDP is the direct consequence of that architectural and process evolution.

The Verdict

The data points to a clear split based on workload. The NVIDIA Tesla M40 24 GB is the performance leader in Vulkan by a 31.8% margin, and its 24 GB memory capacity makes it suitable for large compute tasks that exceed the T1000's 4 GB limit. Its average benchmark score of 41,707 is 14.9% higher than the T1000's 36,289, and its 83rd percentile ranking beats the T1000's 80th. If your software uses Vulkan and demands large memory footprints, the M40 is the stronger card.

The NVIDIA T1000 wins the OpenCL test by 0.7%, which is negligible in practice, but it offers a completely different set of practical advantages. It draws 50 W instead of 250 W, fits in a single slot at 156 mm instead of a dual-slot 267 mm, requires no power connectors, and has four display outputs. The M40 has no display outputs at all, so it cannot function as a standalone desktop card. For OpenCL workloads in a desktop workstation where power efficiency and physical space matter, the T1000 is the practical choice.

The verdict comes down to your priorities. Choose the M40 24 GB if you need maximum compute throughput, Vulkan performance, and large memory capacity, and you have the power budget and physical space to accommodate a 250 W dual-slot card. Choose the T1000 if you need a compact, low-power card that can drive displays, and your OpenCL workloads do not require more than 4 GB of memory. The M40's Vulkan dominance is the single biggest performance gap in the data, but the T1000's efficiency and versatility make it the better all-around workstation card for most desktop environments.