NVIDIA Quadro GP100 vs NVIDIA RTX A3000 Mobile Comparison
NVIDIA Quadro GP100
RTX A3000 Mobile
PERFORMANCE BENCHMARKS
Analysis: NVIDIA Quadro GP100 vs NVIDIA RTX A3000 Mobile
Head-to-Head Benchmarks
The only shared benchmark between these two cards is Geekbench OpenCL, and the result is a clear, though not overwhelming, victory for the older desktop card. The NVIDIA Quadro GP100 scores 87,445, while the NVIDIA RTX A3000 Mobile manages 79,091. That gives the GP100 a 10.6% lead. In practical terms, this means the Pascal-based workstation card sustains a meaningful advantage in raw compute workloads that scale well across its massive memory bus and high shader count.
Placing these scores in context shows just how close the contest really is. The GP100’s nearest rival, the AMD Radeon PRO W7600, scores 87,108 — a delta of only 0.4%, so the GP100 is essentially trading blows with a modern workstation card. Meanwhile, the RTX A3000 Mobile sits within 0.2% of the NVIDIA Quadro P6000 (69,986) and 0.4% of the AMD Radeon Pro WX 8200 (69,870). The gap between the two contenders here is larger than the gap between each card and its own immediate competitors.
The RTX A3000 Mobile does have a second benchmark to its name — Geekbench Vulkan — where it scores 61,189. The GP100 has no Vulkan result in the data, so it is impossible to compare them on that API. The absence of a second data point for the GP100 is worth noting: the A3000 Mobile’s average benchmark score of 70,140 is dragged down by its Vulkan result, while the GP100’s average equals its OpenCL score of 87,445. The percentile rankings reflect this: the GP100 sits at the 93rd percentile of all GPUs, while the A3000 Mobile sits at the 91st.
Looking at the delta percentages against the GP100’s rivals, the picture sharpens. The RTX A4500 Mobile scores 91,134, which is 4% higher than the GP100. The desktop RTX A4500 scores 91,671, 4.6% higher. So while the GP100 beats the A3000 Mobile, it trails those two Ampere-generation options by a noticeable margin. For the A3000 Mobile, the nearest rival data shows it is 1% behind the AMD Radeon RX 6600 LE (70,829) and 1.7% ahead of the NVIDIA CMP 90HX (69,000). The GP100 is 2.1% ahead of the NVIDIA CMP 40HX (85,637).
FAQ
Q: Which card has the higher peak compute throughput?
A: The GP100 reaches 10.34 TFLOPS FP32 and 20.69 TFLOPS FP16 (2:1), while the A3000 Mobile hits 10.08 TFLOPS FP32 and 10.08 TFLOPS FP16 (1:1). The GP100 leads in both, with a 0.26 TFLOPS advantage in FP32 and double the FP16 rate.
Q: Does the RTX A3000 Mobile support hardware ray tracing?
A: Yes. The A3000 Mobile includes 32 RT cores and 128 tensor cores, part of the Ampere architecture. The GP100 has no RT cores or tensor cores listed, so it lacks dedicated ray tracing and tensor hardware.
Q: What is the memory bandwidth difference?
A: The GP100 offers 732.2 GB/s over a 4096-bit HBM2 interface, while the A3000 Mobile provides 264.0 GB/s over a 192-bit GDDR6 bus. The GP100’s bandwidth is nearly 2.8 times higher.
Q: Which card has a higher transistor density despite the larger die?
A: The A3000 Mobile packs 44.4M transistors per mm² on its 392 mm² die (17,400 million total), while the GP100 has 25.1M per mm² on a 610 mm² die (15,300 million total). The Ampere chip is denser despite having fewer total transistors on a smaller die.
Q: How do their power requirements compare?
A: The GP100 has a 235 W TDP and requires a 550 W suggested PSU with a single 8-pin connector. The A3000 Mobile has a 70 W TDP and lists no power connectors or PSU recommendation, reflecting its mobile design.
Q: Are there any benchmark results where the A3000 Mobile wins?
A: In the shared Geekbench OpenCL test, no. The GP100 wins that one. The A3000 Mobile does have a Geekbench Vulkan score of 61,189, but the GP100 has no Vulkan result for comparison.
Where Each One Wins
The GP100 is the clear winner in compute-heavy, memory-hungry workloads. Its 16 GB of HBM2 with a 4096-bit bus delivers 732.2 GB/s of bandwidth, which is the kind of headroom that matters for large datasets, scientific simulation, and GPU compute tasks that saturate memory. The 10.6% OpenCL lead over the A3000 Mobile supports this. The GP100 also has a higher pixel rate (138.5 GPixel/s vs 78.72 GPixel/s) and texture rate (323.2 GTexel/s vs 157.4 GTexel/s), so it wins on rasterization throughput as well. Its 96 ROPs versus the A3000 Mobile’s 64 only reinforces that.
The A3000 Mobile wins on efficiency and modern feature support. Its 70 W TDP is a fraction of the GP100’s 235 W, which makes it viable in laptops and compact workstations where power and thermals are constrained. It also brings ray tracing, tensor cores, and DirectX 12 Ultimate support, none of which the GP100 can offer. The A3000 Mobile’s FP16 performance matches its FP32 rate (10.08 TFLOPS each), which is useful for mixed-precision workloads that do not benefit from the GP100’s 2:1 FP16 ratio. Its PCIe 4.0 interface doubles the bus bandwidth of the GP100’s PCIe 3.0, which helps with data transfer to and from the CPU in systems that support it.
For a builder deciding between these two, the choice comes down to what is being optimized. If the workload is pure compute with massive memory footprints, the GP100 is the data-center-style workhorse. If the workload is modern graphics, ray-traced rendering, or a mobile workstation chassis, the A3000 Mobile is the more practical pick.
Specification Differences
The two cards differ in nearly every major specification category. The GP100 uses a GP100 chip on a 16 nm TSMC process, with 15,300 million transistors on a 610 mm² die. The A3000 Mobile uses a GA104 chip on an 8 nm Samsung process, with 17,400 million transistors on a 392 mm² die. The A3000 Mobile has more transistors packed into a smaller area.
Clocks are starkly different. The GP100 runs at a 1304 MHz base and 1443 MHz boost, while the A3000 Mobile runs at a 600 MHz base and 1230 MHz boost. The GP100’s higher clocks contribute to its pixel and texture rate advantages.
Memory is another major split. The GP100 has 16 GB of HBM2 on a 4096-bit bus, with memory clocked at 715 MHz (1430 Mbps effective) and bandwidth of 732.2 GB/s. The A3000 Mobile has 6 GB of GDDR6 on a 192-bit bus, with memory at 1375 MHz (11 Gbps effective) and bandwidth of 264.0 GB/s. That is a 6 GB capacity advantage and a 2.77x bandwidth advantage for the GP100.
Compute units differ in configuration. The GP100 has 3584 shading units, 224 TMUs, and 96 ROPs. The A3000 Mobile has 4096 shading units, 128 TMUs, and 64 ROPs. The A3000 Mobile actually has more shaders, but the GP100’s higher clocks and wider ROP/TMU counts give it the throughput edge. The A3000 Mobile adds 32 RT cores and 128 tensor cores, which the GP100 lacks entirely.
Power and physical design diverge completely. The GP100 is a dual-slot card, 267 mm long and 111 mm tall, drawing 235 W with a 1x 8-pin connector and a 550 W suggested PSU. The A3000 Mobile has no listed dimensions, no power connectors, and a 70 W TDP. The bus interface is PCIe 3.0 x16 for the GP100 and PCIe 4.0 x16 for the A3000 Mobile. Display outputs are 1x DVI plus 4x DisplayPort 1.4a for the GP100, while the A3000 Mobile is listed as "Portable Device Dependent."
Architecture Differences
The architectural gap is generational. The GP100 is built on Pascal, NVIDIA’s compute-focused architecture from the Quadro Pascal generation. It uses a 16 nm TSMC process. The A3000 Mobile is Ampere, from the Ampere-MW generation, built on Samsung’s 8 nm process. This node shrink explains the transistor density jump from 25.1M / mm² to 44.4M / mm².
The GP100’s Pascal design prioritizes raw FP32 and FP16 throughput, with the 2:1 FP16 ratio indicating a compute-oriented approach. The A3000 Mobile’s Ampere design introduces dedicated RT cores and tensor cores, which the GP100 does not have. That changes the feature set entirely: the A3000 Mobile supports hardware-accelerated ray tracing and AI-accelerated tensor operations, while the GP100 relies on traditional shader compute for everything.
Memory architecture also reflects different design goals. The GP100 uses HBM2 with a 4096-bit bus, a hallmark of high-performance computing parts that need extreme bandwidth. The A3000 Mobile uses GDDR6 on a 192-bit bus, which is more common for mobile parts where board space and power are limited. The GP100’s 16 GB capacity is double-plus the A3000 Mobile’s 6 GB, and the bandwidth gap is even larger.
API support differs as well. The GP100 supports DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.3. The A3000 Mobile supports DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4. The 12_2 feature level and Vulkan 1.4 support on the A3000 Mobile reflect its newer architecture and additional hardware features like ray tracing.
The Verdict
The data points to two different buyers. The NVIDIA Quadro GP100 is for someone who prioritizes compute throughput above all else. Its 10.6% OpenCL lead over the A3000 Mobile, combined with 16 GB of HBM2 and 732.2 GB/s of bandwidth, makes it the stronger choice for large-scale simulations, data processing, and any workload that saturates memory. Its 93rd percentile ranking versus the A3000 Mobile’s 91st confirms the overall performance edge. The GP100 also wins on pixel rate and texture rate, so it is not a slouch in traditional rendering either.
The NVIDIA RTX A3000 Mobile is for someone who needs modern features and mobility. It has more shading units (4096 vs 3584), tensor cores, RT cores, and a smaller process node. Its 70 W TDP makes it feasible in laptops, whereas the GP100’s 235 W TDP requires a desktop chassis with adequate cooling and a 550 W PSU. The A3000 Mobile’s DirectX 12 Ultimate and Vulkan 1.4 support future-proof it for software that leverages ray tracing or variable rate shading.
If the choice is strictly about benchmark scores, the GP100 wins the only head-to-head test. If the choice is about what hardware features matter to the software being run, the A3000 Mobile has capabilities the GP100 cannot match. A builder with a fixed workstation and a compute-heavy workload should take the GP100. A builder with a mobile chassis or a need for ray tracing should take the A3000 Mobile. Neither card is a universal winner, but each is the right tool for a specific job.