NVIDIA GeForce GTX 1650 SUPER vs NVIDIA Tesla M10 Comparison

Head-to-Head Benchmarks

The recorded head-to-head data contains only two matching benchmark entries, both compute-oriented API tests. In Geekbench OpenCL, the NVIDIA GeForce GTX 1650 SUPER scores 43,875 against the NVIDIA Tesla M10's 10,318, a delta of 325.2%. This is not a marginal edge; the GTX 1650 SUPER delivers more than four times the raw OpenCL throughput of the Tesla M10 in this specific workload.

The Vulkan result is even more lopsided. The GTX 1650 SUPER posts 50,519 in Geekbench Vulkan, while the Tesla M10 manages 9,130. That represents a 453.3% advantage for the GeForce card. In other words, the GTX 1650 SUPER is roughly 5.5 times faster in this test. The Tesla M10 does not win either recorded benchmark, so the win count stands at 2 for the GTX 1650 SUPER and 0 for the Tesla M10.

Context from the database helps frame these deltas. The GTX 1650 SUPER's average benchmark score across all recorded tests is 11,047, placing it at the 50th percentile of all GPUs. Its nearest rivals include the AMD Radeon RX 550 at 11,075 (-0.2% delta), the NVIDIA RTX PRO 6000D Blackwell Max-Q at 11,088 (-0.4%), and the NVIDIA GeForce MX350 at 10,883 (+1.5%). The GTX 1650 SUPER sits essentially level with these cards in aggregate scoring, yet its two head-to-head results against the Tesla M10 are vastly larger than the differences among its closest peers.

The Tesla M10, by contrast, has an average benchmark score of 9,724, placing it at the 47th percentile. Its nearest rivals include the NVIDIA Tesla C2070 at 9,716 (+0.1%), the NVIDIA GeForce GTX 1070 at 9,780 (-0.6%), the NVIDIA Quadro P4000 at 9,665 (+0.6%), and the AMD Radeon Pro WX 2100 at 9,653 (+0.7%). The Tesla M10 is well within 1% of these cards in aggregate scoring, which makes the 325% to 453% gaps against the GTX 1650 SUPER all the more striking given how close the two cards are in overall percentile rank.

The disparity between the aggregate scores (11,047 versus 9,724, roughly 13.6% difference) and the head-to-head deltas (325% to 453%) deserves attention. The GTX 1650 SUPER's average includes several Passmark legacy DirectX tests where its scores are modest, dragging the aggregate down. The Tesla M10 has only two recorded benchmarks, both Geekbench entries, so its average is built from a much smaller sample. When the two cards are compared directly on identical tests, the GTX 1650 SUPER dominates by a wide margin.

Where Each One Wins

The GTX 1650 SUPER wins in every measurable compute scenario covered by the head-to-head data. In OpenCL, which is commonly used for general-purpose GPU compute across professional and consumer applications, the 325.2% advantage indicates substantially higher raw throughput. In Vulkan, a modern graphics and compute API, the 453.3% lead shows that the GeForce card handles the newer API with far greater efficiency.

The Tesla M10 has no recorded wins in any benchmark. Its two Geekbench scores, 10,318 in OpenCL and 9,130 in Vulkan, are both far below the GTX 1650 SUPER's corresponding results. The Tesla M10's aggregate average of 9,724 across those two tests is itself lower than the GTX 1650 SUPER's average of 11,047, but that comparison flatters the Tesla M10 relative to the head-to-head deltas because the GeForce card's average is diluted by weaker legacy DirectX scores.

Looking at the GTX 1650 SUPER's full benchmark suite, its strongest individual result is Geekbench Vulkan at 50,519, followed by Geekbench OpenCL at 43,875. Its Passmark G3D score of 10,179 and Passmark G2D score of 749 are more moderate, and the legacy DirectX tests (DirectX 9 at 148, DirectX 10 at 50, DirectX 11 at 73, DirectX 12 at 45) are low in absolute terms but are common patterns for this class of card. The GPU compute Passmark score of 4,477 rounds out the picture.

For use-case analysis, the GTX 1650 SUPER is the clear choice for any workload that leverages OpenCL or Vulkan. This includes modern game engines, Vulkan-based emulation, and OpenCL compute tasks in content creation. The Tesla M10, with no recorded wins and no display outputs, appears oriented toward server-side or virtualized workloads where its 8 GB memory capacity might be relevant, but the database shows no benchmark evidence of any compute advantage.

FAQ

Q: Which card has the higher average benchmark score?

A: The NVIDIA GeForce GTX 1650 SUPER has an average benchmark score of 11,047, compared to the NVIDIA Tesla M10's 9,724. The GTX 1650 SUPER also sits at the 50th percentile of all GPUs, while the Tesla M10 sits at the 47th percentile.

Q: How large is the GTX 1650 SUPER's lead in Geekbench OpenCL?

A: The GTX 1650 SUPER scores 43,875 in Geekbench OpenCL, while the Tesla M10 scores 10,318. This is a 325.2% advantage for the GTX 1650 SUPER.

Q: Does the Tesla M10 win any head-to-head benchmark?

A: No. The head-to-head data shows two tests, Geekbench OpenCL and Geekbench Vulkan, and the Tesla M10 loses both. The recorded win count is 2 for the GTX 1650 SUPER and 0 for the Tesla M10.

Q: What is the GTX 1650 SUPER's lead in Geekbench Vulkan?

A: The GTX 1650 SUPER scores 50,519 in Geekbench Vulkan, against 9,130 for the Tesla M10, a delta of 453.3%.

Q: How do the two cards compare to their nearest rivals?

A: The GTX 1650 SUPER's nearest rival is the AMD Radeon RX 550 with an average score of 11,075, a delta of -0.2%, meaning the GTX 1650 SUPER trails it by only 0.2%. The Tesla M10's nearest rival is the NVIDIA Tesla C2070 at 9,716, a delta of +0.1%, meaning the Tesla M10 leads by 0.1%.

Q: How much memory does each card have?

A: The GTX 1650 SUPER has 4 GB of GDDR6 memory on a 128-bit bus with 192.0 GB/s bandwidth. The Tesla M10 has 8 GB of GDDR5 memory on a 128-bit bus with 83.20 GB/s bandwidth.

Specification Differences

The two cards differ across nearly every specification category. The GTX 1650 SUPER uses 4 GB of GDDR6 memory with a 128-bit bus and 192.0 GB/s bandwidth, while the Tesla M10 uses 8 GB of GDDR5 on the same 128-bit bus but with only 83.20 GB/s bandwidth. The Tesla M10 doubles the memory capacity but delivers less than half the bandwidth.

Clock speeds differ substantially. The GTX 1650 SUPER has a base clock of 1530 MHz and a boost clock of 1725 MHz. The Tesla M10 has a base clock of 1033 MHz and a boost of 1306 MHz. Memory clocks also differ: the GTX 1650 SUPER runs at 1500 MHz with 12 Gbps effective speed, while the Tesla M10 runs at 1300 MHz with 5.2 Gbps effective.

Compute resources are heavily skewed toward the GTX 1650 SUPER. It has 1280 shading units, 80 texture mapping units, and 32 ROPs. The Tesla M10 has 640 shading units, 40 TMUs, and 16 ROPs. Pixel rate on the GTX 1650 SUPER is 55.20 GPixel/s versus 20.90 GPixel/s, and texture rate is 138.0 GTexel/s versus 52.24 GTexel/s. FP32 throughput is 4.416 TFLOPS for the GTX 1650 SUPER and 1.672 TFLOPS for the Tesla M10. The GTX 1650 SUPER also lists FP16 at 8.832 TFLOPS (2:1), while the Tesla M10 has no recorded FP16 capability.

Power and physical specifications diverge as well. The GTX 1650 SUPER has a TDP of 100 W, a suggested PSU of 300 W, and a single 6-pin power connector. The Tesla M10 has a TDP of 225 W, a suggested PSU of 550 W, and a single 8-pin connector. Both are dual-slot cards, but the GTX 1650 SUPER is 229 mm (9 inches) long, while the Tesla M10 is 267 mm (10.5 inches) long. The GTX 1650 SUPER has display outputs (1x DVI, 1x HDMI 2.0, 1x DisplayPort 1.4a), while the Tesla M10 has no outputs.

The GTX 1650 SUPER has a launch MSRP of 159 USD. The Tesla M10 has no recorded launch MSRP.

Architecture Differences

The GTX 1650 SUPER is built on the Turing architecture using the TU116 chip, fabricated on a 12 nm process at TSMC. It contains 6,600 million transistors on a 284 mm² die, giving a transistor density of 23.2M per mm². The Tesla M10 uses the Maxwell architecture with the GM107 chip, on a 28 nm process also at TSMC. It contains 1,870 million transistors on a 148 mm² die, with a density of 12.6M per mm². The GTX 1650 SUPER uses a smaller process node, packs over three times the transistor count, and achieves nearly double the transistor density.

The GTX 1650 SUPER belongs to the GeForce 16 generation and is the successor to GeForce 10, with its own successor being GeForce 20. The Tesla M10 belongs to the Tesla Maxwell generation, with Tesla Kepler as its predecessor and Tesla Pascal as its successor. The GTX 1650 SUPER was released in 2019, while the Tesla M10 was released in 2016. Both are end-of-life products.

Neither card has ray tracing cores or tensor cores. API support is similar but not identical: both support OpenGL 4.6 and Vulkan 1.4, but the GTX 1650 SUPER supports DirectX 12 (12_1) while the Tesla M10 supports DirectX 12 (11_0). The GTX 1650 SUPER lists FP16 compute at 8.832 TFLOPS with a 2:1 ratio, while the Tesla M10 has no FP16 figure recorded.

The Tesla M10's 8 GB memory capacity and lack of display outputs suggest a different design intent, likely for virtualized or server-side graphics workloads where framebuffer size matters more than raw throughput. The GTX 1650 SUPER, with its display outputs, lower power draw, and much higher compute throughput, is clearly aimed at consumer desktop use.

The Verdict

The data points to a decisive outcome. The GTX 1650 SUPER wins both recorded head-to-head benchmarks, with leads of 325.2% in Geekbench OpenCL and 453.3% in Geekbench Vulkan. Its aggregate benchmark score of 11,047 exceeds the Tesla M10's 9,724, and it sits at a higher percentile rank (50 versus 47). The GTX 1650 SUPER also offers more than double the FP32 throughput (4.416 TFLOPS versus 1.672 TFLOPS), more than double the texture rate (138.0 GTexel/s versus 52.24 GTexel/s), and more than double the pixel rate (55.20 GPixel/s versus 20.90 GPixel/s).

The Tesla M10's only hardware advantage is memory capacity, 8 GB versus 4 GB, but that comes with less than half the bandwidth (83.20 GB/s versus 192.0 GB/s). It also consumes more power (225 W versus 100 W), requires a larger PSU (550 W versus 300 W), and offers no display outputs.

For users choosing between these two cards, the GTX 1650 SUPER is the better option for any workload measured in the database. It dominates in compute benchmarks, has a more modern architecture, runs cooler and more efficiently, and supports newer DirectX features. The Tesla M10 is only preferable in scenarios where 8 GB of memory is a hard requirement and where the lack of display outputs is acceptable, but the recorded benchmark data shows no workload where the Tesla M10 outperforms the GTX 1650 SUPER.