NVIDIA RTX 4000 SFF Ada Generation vs NVIDIA RTX A3000 Mobile Comparison

The NVIDIA RTX 4000 SFF Ada Generation and the NVIDIA RTX A3000 Mobile represent two distinct approaches to professional graphics, separated by architecture and design philosophy. The recorded data shows a clear performance hierarchy, with the desktop-oriented SFF model decisively outperforming the older mobile part in every measured category. This analysis breaks down where each card excels, the architectural differences that explain the gap, and the raw benchmark numbers that define the comparison.

Where Each One Wins

Based on the two recorded benchmark tests, the NVIDIA RTX 4000 SFF Ada Generation wins every head-to-head matchup. It holds a 57.8% lead in Geekbench OpenCL and a 78.7% lead in Geekbench Vulkan. There are no tests in the database where the RTX A3000 Mobile comes out ahead.

The RTX 4000 SFF Ada Generation is the clear choice for workloads that rely on compute throughput. Its FP32 rating of 19.17 TFLOPS is nearly double the 10.08 TFLOPS of the A3000 Mobile, and its texture rate of 299.5 GTexel/s vastly exceeds the 157.4 GTexel/s of the older card. For rendering, simulation, or any GPU-accelerated task that scales with raw shading and texture throughput, the data points squarely at the Ada part.

The RTX A3000 Mobile, by contrast, offers no benchmark wins. Its strengths are contextual rather than absolute. As a mobile part with a 70 W TDP, it was designed for portable workstations where physical size and power draw are constrained. Its 6 GB memory capacity is smaller than the 20 GB on the SFF card, but for its generation it represented a capable option for on-the-go professional work. The database shows it sits in the 91st percentile of all GPUs, meaning it was a strong performer relative to the broader field, just not relative to the newer SFF card.

The use-case split is therefore simple: the RTX 4000 SFF Ada Generation for maximum compute performance in a compact desktop chassis, and the RTX A3000 Mobile for scenarios requiring a mobile form factor, accepting a significant performance penalty. The SFF card is currently Active in production, while the A3000 Mobile is End-of-life, indicating NVIDIA has moved on.

Architecture Differences

The two GPUs come from different architectural generations and different foundries. The RTX 4000 SFF Ada Generation uses the AD104 chip on the Ada Lovelace architecture, fabricated by TSMC on a 5 nm process. The RTX A3000 Mobile uses the GA104 chip on the Ampere architecture, fabricated by Samsung on an 8 nm process. This process gap is a major contributor to the performance difference: the Ada chip packs 35,800 million transistors into a 294 mm² die, yielding a transistor density of 121.8M per mm². The Ampere chip has 17,400 million transistors on a 392 mm² die, for a density of 44.4M per mm².

The Ada chip is smaller and denser, allowing more compute resources in a more efficient package. The RTX 4000 SFF Ada Generation has 6144 shading units, 192 texture mapping units, 64 ROPs, 48 RT cores, and 192 tensor cores. The RTX A3000 Mobile has 4096 shading units, 128 TMUs, 64 ROPs, 32 RT cores, and 128 tensor cores. Every compute block except ROPs is larger on the Ada part, and the ROP count is equal at 64.

Clock speeds also favor the newer card. The RTX 4000 SFF Ada Generation runs at a 720 MHz base and 1560 MHz boost, while the RTX A3000 Mobile runs at 600 MHz base and 1230 MHz boost. Combined with the higher core count, this yields a 19.17 TFLOPS FP32 rating versus 10.08 TFLOPS, a 90% advantage. FP16 performance is also 1:1 on both cards, meaning the same TFLOPS figures apply for half-precision work.

Memory configurations differ substantially. The RTX 4000 SFF Ada Generation has 20 GB of GDDR6 on a 160-bit bus, with 1750 MHz memory clock and 14 Gbps effective speed, delivering 280.0 GB/s bandwidth. The RTX A3000 Mobile has 6 GB of GDDR6 on a 192-bit bus, with 1375 MHz memory clock and 11 Gbps effective speed, delivering 264.0 GB/s bandwidth. The Ada card has over three times the capacity and slightly more bandwidth despite the narrower bus, thanks to faster memory clocks.

The transistor density difference is stark. The Ada chip crams 121.8M transistors per mm², more than 2.7 times the 44.4M per mm² of the Ampere chip. This efficiency gain is central to why the SFF card can deliver nearly double the compute throughput while maintaining the same 70 W TDP as the mobile part.

FAQ

Q: Which GPU has higher FP32 compute performance?

A: The NVIDIA RTX 4000 SFF Ada Generation is rated at 19.17 TFLOPS, while the NVIDIA RTX A3000 Mobile is rated at 10.08 TFLOPS. The Ada card delivers roughly 90% more FP32 throughput.

Q: How do the memory capacities compare?

A: The RTX 4000 SFF Ada Generation has 20 GB of GDDR6, whereas the RTX A3000 Mobile has 6 GB of GDDR6. The Ada card also has slightly higher bandwidth at 280.0 GB/s versus 264.0 GB/s.

Q: Are both GPUs based on the same architecture?

A: No. The RTX 4000 SFF Ada Generation uses the Ada Lovelace architecture with the AD104 chip, fabricated by TSMC on a 5 nm process. The RTX A3000 Mobile uses the Ampere architecture with the GA104 chip, fabricated by Samsung on an 8 nm process.

Q: What is the transistor count for each chip?

A: The AD104 chip in the RTX 4000 SFF Ada Generation contains 35,800 million transistors on a 294 mm² die. The GA104 chip in the RTX A3000 Mobile contains 17,400 million transistors on a 392 mm² die.

Q: Which card has more RT and tensor cores?

A: The RTX 4000 SFF Ada Generation has 48 RT cores and 192 tensor cores. The RTX A3000 Mobile has 32 RT cores and 128 tensor cores.

Q: What is the production status of each GPU?

A: The RTX 4000 SFF Ada Generation is listed as Active in production. The RTX A3000 Mobile is listed as End-of-life.

Specification Differences

The two cards differ across nearly every major specification category. The RTX 4000 SFF Ada Generation uses the AD104 chip, while the RTX A3000 Mobile uses the GA104 chip. The process nodes are 5 nm (TSMC) for the Ada card and 8 nm (Samsung) for the Ampere card. Transistor counts are 35,800 million versus 17,400 million, and die sizes are 294 mm² versus 392 mm². Transistor density is 121.8M per mm² versus 44.4M per mm².

Clock speeds differ: 720 MHz base and 1560 MHz boost on the Ada card, versus 600 MHz base and 1230 MHz boost on the Ampere card. Memory clock is 1750 MHz (14 Gbps effective) versus 1375 MHz (11 Gbps effective). Memory size is 20 GB versus 6 GB, both GDDR6, with bus widths of 160-bit versus 192-bit. Bandwidth is 280.0 GB/s versus 264.0 GB/s.

Compute resources differ: 6144 shading units versus 4096, 192 TMUs versus 128, 64 ROPs versus 64, 48 RT cores versus 32, and 192 tensor cores versus 128. Pixel rates are 99.84 GPixel/s versus 78.72 GPixel/s, and texture rates are 299.5 GTexel/s versus 157.4 GTexel/s. FP32 and FP16 are both 19.17 TFLOPS on the Ada card versus 10.08 TFLOPS on the Ampere card.

The power envelope is identical at 70 W TDP, and both use no external power connectors. The Ada card is dual-slot and measures 168 mm in length and 69 mm in height, with 4x mini-DisplayPort 1.4a outputs. The A3000 Mobile has no listed dimensions or slot width, and its display outputs are "Portable Device Dependent." The Ada card has a suggested PSU of 250 W, while the A3000 Mobile has none listed.

Bus interface is PCIe 4.0 x16 for both. API support is identical: DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4. Release dates differ: the RTX 4000 SFF Ada Generation launched on 2023-03-20, while the RTX A3000 Mobile launched on 2021-04-11. The Ada card's predecessor is Workstation Ampere and its successor is Blackwell PRO W. The A3000 Mobile's predecessor is Quadro Turing-M and its successor is Ada-MW.

Head-to-Head Benchmarks

The two recorded benchmark tests show a dominant performance gap. In Geekbench OpenCL, the RTX 4000 SFF Ada Generation scores 124812, while the RTX A3000 Mobile scores 79091. This is a 57.8% delta in favor of the Ada card. The result is consistent with the FP32 throughput difference: the Ada card's 19.17 TFLOPS versus 10.08 TFLOPS gives it a massive advantage in compute-heavy OpenCL workloads.

In Geekbench Vulkan, the gap widens further. The RTX 4000 SFF Ada Generation scores 109364, while the RTX A3000 Mobile scores 61189. This is a 78.7% delta, suggesting the Ada architecture's improvements in graphics and compute pipeline efficiency are amplified under Vulkan. The combination of more shading units, higher clocks, and faster memory contributes to this larger margin.

The average benchmark score tells a similar story. The RTX 4000 SFF Ada Generation has an average score of 117088, placing it in the 95th percentile of all GPUs. The RTX A3000 Mobile has an average score of 70140, placing it in the 91st percentile. While both are strong performers relative to the full GPU landscape, the absolute gap between them is substantial: the Ada card's average score is nearly 67% higher.

Context from nearest rivals reinforces the positioning. The RTX 4000 SFF Ada Generation's closest competitor is the NVIDIA GB10, which scores 117393, just 0.3% higher. The AMD Radeon PRO W7700 scores 118976, 1.6% higher, while the NVIDIA Tesla V100 SXM2 16 GB scores 114395, 2.4% lower. The NVIDIA RTX A5500 Mobile scores 113944, 2.8% lower. This places the SFF Ada card in a tight competitive cluster at the top of the workstation stack.

The RTX A3000 Mobile sits in a different performance tier. Its closest rival, the NVIDIA Quadro P6000, scores 69986, just 0.2% lower. The AMD Radeon Pro WX 8200 scores 69870, 0.4% lower. The AMD Radeon RX 6600 LE scores 70829, 1% higher, and the NVIDIA CMP 90HX scores 69000, 1.7% lower. These rivals are all within a narrow band, indicating the A3000 Mobile is competitive with older professional and mid-range consumer parts, but far from the performance class of the newer Ada generation.

The wins tally is decisive: 2 wins for the RTX 4000 SFF Ada Generation, 0 wins for the RTX A3000 Mobile. No benchmark in the database shows the mobile part ahead. The performance gap is not marginal; it is a generational leap in compute resources, memory capacity, and clock speeds. For anyone choosing between these two based purely on recorded performance, the data leaves no ambiguity.