NVIDIA GeForce RTX 4080 Mobile vs NVIDIA Quadro M6000 24 GB Comparison

The NVIDIA Quadro M6000 24 GB and NVIDIA GeForce RTX 4080 Mobile represent two distinct eras of GPU design, separated by nearly seven years of architectural evolution. The data shows a decisive victory for the modern mobile part, yet the workstation card retains specific traits that matter in professional contexts. This analysis breaks down the benchmark results, architectural differences, and practical implications strictly from the provided specifications.

Head-to-Head Benchmarks

The benchmark comparison is stark and one-sided. In the Geekbench OpenCL test, the RTX 4080 Mobile scores 159,575, while the Quadro M6000 24 GB manages 40,098. That is a 74.9% advantage for the mobile GPU, meaning the RTX 4080 Mobile delivers nearly four times the raw compute performance in this API. The Vulkan result tells a similar story: the RTX 4080 Mobile posts 145,807 against the Quadro’s 46,425, a 68.2% lead. Both deltas are massive, and the head-to-head table records 2 wins for the RTX 4080 Mobile and 0 for the Quadro.

What makes these numbers more striking is the context of the nearest rivals. The Quadro M6000 24 GB has an average benchmark score of 43,262, sitting at the 83rd percentile of all GPUs. Its closest competitors include the GeForce RTX 5050 Mobile (43,268, 0% delta), the Quadro M6000 (43,301, -0.1%), and the RTX 4070 SUPER (43,223, 0.1%). This places the Quadro in a performance band where it trades blows with modern mid-range parts. Meanwhile, the RTX 4080 Mobile’s average score of 38,135 puts it at the 81st percentile, with nearest rivals like the GeForce MX570 (38,299, -0.4%) and RTX 5080 Mobile (38,349, -0.6%). The average scores seem counterintuitive given the head-to-head results, but the RTX 4080 Mobile’s average is dragged down by its additional Passmark tests, which score much lower than its Geekbench numbers.

The real story is the per-test dominance. The RTX 4080 Mobile’s OpenCL score is 298% higher than the Quadro’s, and its Vulkan score is 214% higher. These are not marginal gains; they reflect a fundamental shift in compute architecture. The Quadro’s best individual result is its Vulkan score of 46,425, which is still 68.2% below the RTX 4080 Mobile’s worst Geekbench score. When comparing raw throughput, the RTX 4080 Mobile’s FP32 performance of 24.72 TFLOPS dwarfs the Quadro’s 6.844 TFLOPS, a 3.6x difference that aligns closely with the OpenCL delta.

Where Each One Wins

Given the benchmark data, the RTX 4080 Mobile wins outright in every measured test. There are no benchmark categories where the Quadro M6000 24 GB comes out ahead. However, the win distribution is not just about speed—it is about workload suitability.

The RTX 4080 Mobile’s victories in both OpenCL and Vulkan make it the clear choice for compute-heavy tasks that leverage these APIs. OpenCL is widely used in scientific computing, video encoding, and machine learning inference, while Vulkan is increasingly common in professional visualization and modern game engines. The 74.9% and 68.2% deltas mean that any workload relying on these APIs will see dramatic speedups. Furthermore, the RTX 4080 Mobile’s 12 GB of GDDR6 memory on a 192-bit bus delivers 432.0 GB/s of bandwidth, which is 36% higher than the Quadro’s 317.4 GB/s. This bandwidth advantage supports its higher compute throughput, especially in memory-bound tasks like texture-heavy rendering or large dataset processing.

The Quadro M6000 24 GB, despite losing all benchmarks, wins on capacity and compatibility. Its 24 GB of VRAM is double the RTX 4080 Mobile’s 12 GB, which matters for workloads that require loading entire datasets into memory without PCIe transfers. The Quadro also supports 1x DVI and 4x DisplayPort 1.2 outputs, making it a plug-and-play solution for multi-monitor professional setups. Its 96 ROPs exceed the RTX 4080 Mobile’s 80 ROPs, which could theoretically benefit certain rasterization-heavy tasks, though the benchmark data does not confirm this advantage in practice. The Quadro’s 384-bit memory bus, while narrower in bandwidth, provides more parallel memory channels, which can help in specific access patterns.

For the RTX 4080 Mobile, its 58 RT cores and 232 tensor cores are absent on the Quadro entirely. This means ray-traced workloads and AI-accelerated tasks are simply not comparable—the RTX 4080 Mobile has dedicated hardware for these, while the Quadro relies on brute-force compute. The RTX 4080 Mobile’s support for DirectX 12 Ultimate (12_2) versus the Quadro’s DirectX 12 (12_1) also indicates better support for modern graphics features like mesh shaders and variable rate shading, though the benchmark pack does not include tests for these.

The Verdict

The data is unambiguous: the NVIDIA GeForce RTX 4080 Mobile is the superior performer in every benchmark recorded. If the choice is purely about speed in OpenCL or Vulkan workloads, the RTX 4080 Mobile is 68-75% faster, and that gap is insurmountable for the older Quadro. The RTX 4080 Mobile also brings modern features—58 RT cores, 232 tensor cores, and a 5 nm process—that the Quadro cannot match. For any user running compute-heavy applications, rendering, or AI inference, the RTX 4080 Mobile is the only rational pick from a performance standpoint.

However, the Quadro M6000 24 GB still has a niche. Its 24 GB of VRAM is the largest memory pool in this comparison, and for professionals who need to fit entire models or scenes in memory without resorting to spills, that capacity is critical. The Quadro also has a higher percentile ranking (83rd vs 81st), suggesting that its average performance across all GPUs is slightly better than the RTX 4080 Mobile’s, despite the head-to-head losses. This is because the Quadro’s two benchmark scores are both high, while the RTX 4080 Mobile’s average is diluted by its lower Passmark results. The Quadro’s launch MSRP was 4,999 USD, positioning it as a flagship workstation product, whereas the RTX 4080 Mobile has no listed MSRP, reflecting its mobile OEM nature.

Who should pick which? The RTX 4080 Mobile is for anyone who prioritizes raw compute speed and modern API support. The Quadro is for those who need maximum VRAM capacity and are willing to sacrifice performance for that memory size. The data shows that the RTX 4080 Mobile wins 2-0 in head-to-head tests, and that is the final word for most users.

FAQ

Q: How much faster is the RTX 4080 Mobile in OpenCL?

A: The RTX 4080 Mobile scores 159,575 in Geekbench OpenCL, while the Quadro M6000 24 GB scores 40,098. This is a 74.9% advantage for the RTX 4080 Mobile.

Q: Does the Quadro M6000 24 GB win any benchmark?

A: No. In the head-to-head benchmarks, the RTX 4080 Mobile wins both Geekbench OpenCL and Geekbench Vulkan. The Quadro has 0 wins out of 2 tests.

Q: What is the VRAM capacity difference?

A: The Quadro M6000 24 GB has 24 GB of GDDR5 memory, while the RTX 4080 Mobile has 12 GB of GDDR6. The Quadro has twice the memory capacity, but the RTX 4080 Mobile has higher bandwidth at 432.0 GB/s versus 317.4 GB/s.

Q: Which GPU has better ray tracing support?

A: The RTX 4080 Mobile has 58 dedicated RT cores, while the Quadro M6000 24 GB has none listed. This makes the RTX 4080 Mobile the only option for hardware-accelerated ray tracing.

Q: How do their average benchmark scores compare?

A: The Quadro M6000 24 GB has an average benchmark score of 43,262, placing it in the 83rd percentile. The RTX 4080 Mobile has an average of 38,135, placing it in the 81st percentile. Despite this, the RTX 4080 Mobile wins every head-to-head test.

Q: What are the closest rivals for each GPU?

A: For the Quadro, the nearest rival is the RTX 5050 Mobile with a 0% delta. For the RTX 4080 Mobile, the nearest rival is the GeForce MX570 with a -0.4% delta.

Architecture Differences

The architectural gap between these two GPUs is generational. The Quadro M6000 24 GB uses the GM200 chip, built on the Maxwell 2.0 architecture at TSMC’s 28 nm process. It packs 8,000 million transistors on a 601 mm² die, yielding a transistor density of 13.3M per mm². The chip has 3,072 shading units, 192 TMUs, and 96 ROPs. Its base clock is 988 MHz with a boost of 1114 MHz, and it achieves 6.844 TFLOPS of FP32 performance. The memory subsystem consists of 24 GB of GDDR5 on a 384-bit bus, running at 1653 MHz (6.6 Gbps effective) for 317.4 GB/s bandwidth. The Quadro has no RT cores or tensor cores, and its pixel rate is 106.9 GPixel/s with a texture rate of 213.9 GTexel/s. It uses a PCIe 3.0 x16 interface and consumes 250 W TDP, requiring a dual-slot cooler and a 1x 8-pin power connector.

In contrast, the RTX 4080 Mobile uses the AD104 chip, built on the Ada Lovelace architecture at a 5 nm process. It contains 35,800 million transistors on a 294 mm² die, giving a transistor density of 121.8M per mm²—a 9.2x improvement in density. The chip has 7,424 shading units, 232 TMUs, and 80 ROPs, along with 58 RT cores and 232 tensor cores. Its base clock is 1290 MHz with a boost of 1665 MHz, producing 24.72 TFLOPS of FP32 and FP16 performance (1:1 ratio). The 12 GB of GDDR6 memory runs on a 192-bit bus at 2250 MHz (18 Gbps effective) for 432.0 GB/s bandwidth. The RTX 4080 Mobile achieves 133.2 GPixel/s and 386.3 GTexel/s. It uses a PCIe 4.0 x16 interface and has a TDP of just 110 W, with no dedicated power connectors and an IGP slot width.

The architectural differences translate directly into the benchmark results. The RTX 4080 Mobile has 2.4x more shading units, 3.6x higher FP32 throughput, and 36% more memory bandwidth. It also supports DirectX 12 Ultimate (12_2) versus the Quadro’s DirectX 12 (12_1), and both support OpenGL 4.6 and Vulkan 1.4. The process node shrink from 28 nm to 5 nm allows the RTX 4080 Mobile to deliver higher performance at less than half the power (110 W vs 250 W). The Quadro’s 601 mm² die is more than twice the size of the RTX 4080 Mobile’s 294 mm², yet it contains fewer transistors, highlighting the density advantage of modern manufacturing. The RTX 4080 Mobile’s tensor cores enable AI acceleration, and its RT cores enable real-time ray tracing, features entirely absent on the Maxwell-based Quadro. These are not incremental upgrades; they represent a complete redesign of the GPU compute model, and the benchmark data confirms the impact.