NVIDIA RTX 4000 Mobile Ada Generation vs NVIDIA Rubin GPU Comparison

# Head-to-Head Benchmarks

The database records no direct benchmark scores for either the NVIDIA RTX 4000 Mobile Ada Generation or the NVIDIA Rubin GPU. Both entries show an average benchmark score of zero and zero wins in head-to-head comparisons. The percentile ranking against all GPUs is identical at 50 for both parts, meaning neither has established a measured performance position relative to the broader GPU landscape.

What the recorded data does provide is a stark contrast in raw compute specifications. The RTX 4000 Mobile Ada Generation delivers 24.72 TFLOPS of FP32 performance, while the Rubin GPU delivers 130.0 TFLOPS of FP32 performance. That places the Rubin GPU at roughly 5.3 times the FP32 throughput of the mobile part. In FP16 workloads, the gap widens further. The RTX 4000 Mobile Ada Generation sustains 24.72 TFLOPS with a 1:1 FP16 to FP32 ratio, whereas the Rubin GPU reaches 260.0 TFLOPS due to a 2:1 ratio. The Rubin GPU therefore provides approximately 10.5 times the FP16 throughput.

Texture processing follows a similar pattern. The RTX 4000 Mobile Ada Generation achieves a texture rate of 386.3 GTexel/s from 232 texture mapping units. The Rubin GPU reaches 2,031.2 GTexel/s from 896 texture mapping units, a 5.3 times advantage. Pixel throughput tells a different story. The mobile part produces 133.2 GPixel/s from 80 ROPs, while the Rubin GPU produces only 54.41 GPixel/s from just 24 ROPs. The RTX 4000 Mobile Ada Generation holds a 2.4 times advantage in pixel fill rate despite its far lower overall compute capacity.

Memory bandwidth presents one of the largest deltas. The RTX 4000 Mobile Ada Generation uses a 192-bit bus with 12 GB of GDDR6 memory at 18 Gbps effective, yielding 432.0 GB/s. The Rubin GPU uses a 16384-bit bus with 288 GB of HBM4 memory at 10.8 Gbps effective, yielding 22.1 TB/s. The Rubin GPU delivers 51.2 times the memory bandwidth. That difference is consistent with the Rubin GPU being designed for data-center scale workloads rather than interactive rendering.

Clock behavior also differs substantially. The RTX 4000 Mobile Ada Generation has a base clock of 1290 MHz and a boost clock of 1665 MHz, a modest 375 MHz uplift. The Rubin GPU has a base clock of 700 MHz but a boost clock of 2267 MHz, a 1567 MHz uplift. The Rubin GPU's boost clock exceeds the mobile part's boost clock by 602 MHz, but its base clock sits 590 MHz lower. This suggests the Rubin GPU has a much wider dynamic range, likely due to thermal and power management requirements at server scale.

Shader throughput per clock helps clarify the architectural difference. The RTX 4000 Mobile Ada Generation carries 7424 shading units. At its boost clock of 1665 MHz, that yields the recorded 24.72 TFLOPS. The Rubin GPU carries 28672 shading units. At its boost clock of 2267 MHz, that yields the recorded 130.0 TFLOPS. The Rubin GPU has 3.9 times the shading units and achieves 5.3 times the FP32 throughput.

The Verdict

The recorded data points to two entirely different deployment classes. The RTX 4000 Mobile Ada Generation is a 110 W part with an IGP slot width, no power connectors, and portable-device-dependent display outputs. It is built for mobile workstations where power draw and physical size are constrained. The Rubin GPU is a 2300 W SXM module requiring a 2700 W suggested power supply, with no display outputs at all. It is a server accelerator for compute-heavy environments.

For FP32 and FP16 compute workloads, the Rubin GPU is the clear choice. It provides 130.0 TFLOPS against 24.72 TFLOPS in FP32, and 260.0 TFLOPS against 24.72 TFLOPS in FP16. For texture-heavy work, the Rubin GPU also wins decisively with 2,031.2 GTexel/s versus 386.3 GTexel/s. Memory capacity and bandwidth overwhelmingly favor the Rubin GPU: 288 GB versus 12 GB, and 22.1 TB/s versus 432.0 GB/s. Any workload that fits within the Rubin GPU's memory footprint and can utilize its compute resources will finish dramatically faster.

The RTX 4000 Mobile Ada Generation wins only in pixel throughput. Its 133.2 GPixel/s exceeds the Rubin GPU's 54.41 GPixel/s. It also supports display outputs, while the Rubin GPU has none. For rasterization-heavy tasks that require driving displays or producing high pixel fill rates, the mobile part is the only option among the two.

The API support further separates them. The RTX 4000 Mobile Ada Generation supports DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4. The Rubin GPU reports N/A for DirectX, OpenGL, and Vulkan. The Rubin GPU is not a graphics card in the conventional sense; it is a compute accelerator. Anyone needing graphics API compatibility must choose the RTX 4000 Mobile Ada Generation.

The production status for both is listed as Active, and both release dates are recorded in the database. The RTX 4000 Mobile Ada Generation carries a release date of 2023-03-20, while the Rubin GPU carries a release date of 2025-12-31. Neither has a launch MSRP recorded.

FAQ

Q: Which GPU has higher FP32 performance?

A: The NVIDIA Rubin GPU delivers 130.0 TFLOPS of FP32 compute, while the NVIDIA RTX 4000 Mobile Ada Generation delivers 24.72 TFLOPS. The Rubin GPU is approximately 5.3 times faster in FP32.

Q: How do the memory subsystems compare?

A: The RTX 4000 Mobile Ada Generation has 12 GB of GDDR6 memory on a 192-bit bus with 432.0 GB/s bandwidth. The Rubin GPU has 288 GB of HBM4 memory on a 16384-bit bus with 22.1 TB/s bandwidth. The Rubin GPU provides 51.2 times the bandwidth and 24 times the capacity.

Q: Which GPU supports graphics APIs?

A: The RTX 4000 Mobile Ada Generation supports DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4. The Rubin GPU reports N/A for all three graphics APIs.

Q: What is the difference in pixel fill rate?

A: The RTX 4000 Mobile Ada Generation achieves 133.2 GPixel/s from 80 ROPs. The Rubin GPU achieves 54.41 GPixel/s from 24 ROPs. The mobile part is 2.4 times faster in pixel throughput.

Q: What are the power requirements for each?

A: The RTX 4000 Mobile Ada Generation has a TDP of 110 W and uses no power connectors. The Rubin GPU has a TDP of 2300 W and requires a suggested power supply of 2700 W.

Q: How do the tensor core counts compare?

A: The RTX 4000 Mobile Ada Generation has 232 tensor cores. The Rubin GPU has 896 tensor cores. The Rubin GPU has 3.9 times the tensor core count.

Specification Differences

The two GPUs differ across nearly every recorded specification. Process node: the RTX 4000 Mobile Ada Generation uses a 5 nm process, while the Rubin GPU uses a 3 nm process. Transistor count: 35,800 million versus 336,000 million. Die size: 294 mm² versus 1456 mm². Transistor density: 121.8M per mm² versus 230.8M per mm².

Clock speeds differ significantly. Base clock: 1290 MHz versus 700 MHz. Boost clock: 1665 MHz versus 2267 MHz. Memory clock: 2250 MHz with 18 Gbps effective for the mobile part, versus 2695 MHz with 10.8 Gbps effective for the Rubin GPU.

Memory configuration: 12 GB GDDR6 versus 288 GB HBM4. Bus width: 192 bit versus 16384 bit. Bandwidth: 432.0 GB/s versus 22.1 TB/s.

Compute units: 7424 shading units versus 28672 shading units. TMUs: 232 versus 896. ROPs: 80 versus 24. RT cores: 58 for the mobile part, with no recorded value for the Rubin GPU. Tensor cores: 232 versus 896.

Pixel rate: 133.2 GPixel/s versus 54.41 GPixel/s. Texture rate: 386.3 GTexel/s versus 2,031.2 GTexel/s. FP32: 24.72 TFLOPS versus 130.0 TFLOPS. FP16: 24.72 TFLOPS (1:1) versus 260.0 TFLOPS (2:1).

Physical and interface differences: TDP of 110 W versus 2300 W. Slot width of IGP versus SXM Module. Power connectors of None versus no recorded value. Suggested PSU of none versus 2700 W. Bus interface of PCIe 4.0 x16 versus PCIe 6.0 x16. Display outputs of Portable Device Dependent versus No outputs.

API support: DirectX 12 Ultimate (12_2) versus N/A. OpenGL 4.6 versus N/A. Vulkan 1.4 versus N/A.

Production status is Active for both. Release dates differ: 2023-03-20 versus 2025-12-31. Predecessors: Ampere-MW versus Server Blackwell. Successor: Blackwell-MW for the mobile part, none recorded for the Rubin GPU.

Architecture Differences

The RTX 4000 Mobile Ada Generation uses the AD104 chip built on the Ada Lovelace architecture, fabricated by TSMC on a 5 nm process. It belongs to the GeForce 40-series and the Ada-MW generation. The chip contains 35,800 million transistors on a 294 mm² die, giving a transistor density of 121.8M per mm². The architecture includes 58 RT cores and 232 tensor cores, supporting DirectX 12 Ultimate, OpenGL 4.6, and Vulkan 1.4. The memory subsystem uses GDDR6 on a 192-bit bus.

The NVIDIA Rubin GPU uses the GR100 chip built on the Rubin architecture, also fabricated by TSMC but on a 3 nm process. It belongs to the Server Rubin generation with the identifier Rxx. The chip contains 336,000 million transistors on a 1456 mm² die, giving a transistor density of 230.8M per mm². The architecture includes 896 tensor cores with no recorded RT core count. It reports no graphics API support. The memory subsystem uses HBM4 on a 16384-bit bus.

The transistor density difference reflects the process node change. The 3 nm node packs 230.8M transistors per mm² versus 121.8M per mm² on 5 nm. The Rubin GPU uses this density advantage to reach 336,000 million transistors, nearly 9.4 times the transistor count of the AD104.

The FP16 ratio differs between the architectures. The RTX 4000 Mobile Ada Generation runs FP16 at a 1:1 ratio with FP32, both at 24.72 TFLOPS. The Rubin GPU runs FP16 at a 2:1 ratio, reaching 260.0 TFLOPS against 130.0 TFLOPS FP32. This indicates the Rubin architecture dedicates more hardware to reduced-precision compute.

The Rubin GPU uses a PCIe 6.0 x16 interface, while the RTX 4000 Mobile Ada Generation uses PCIe 4.0 x16. The Rubin GPU is packaged as an SXM Module with no display outputs, consistent with a server accelerator. The RTX 4000 Mobile Ada Generation is packaged as an IGP with portable-device-dependent display outputs, consistent with a mobile workstation part.

Where Each One Wins

The NVIDIA Rubin GPU wins decisively in compute throughput. FP32 performance of 130.0 TFLOPS versus 24.72 TFLOPS gives it a 5.3 times advantage. FP16 performance of 260.0 TFLOPS versus 24.72 TFLOPS gives it a 10.5 times advantage. Texture rate of 2,031.2 GTexel/s versus 386.3 GTexel/s gives it a 5.3 times advantage. Memory bandwidth of 22.1 TB/s versus 432.0 GB/s gives it a 51.2 times advantage. Memory capacity of 288 GB versus 12 GB gives it a 24 times advantage. Tensor core count of 896 versus 232 gives it a 3.9 times advantage.

The Rubin GPU also wins on process technology. The 3 nm node with 230.8M transistors per mm² exceeds the 5 nm node with 121.8M per mm². The boost clock of 2267 MHz exceeds the mobile part's 1665 MHz. The bus interface of PCIe 6.0 x16 is newer than PCIe 4.0 x16.

The RTX 4000 Mobile Ada Generation wins in pixel throughput. Its 133.2 GPixel/s from 80 ROPs exceeds the Rubin GPU's 54.41 GPixel/s from 24 ROPs by a factor of 2.4. This makes it better suited for rasterization workloads that depend on pixel fill.

The RTX 4000 Mobile Ada Generation also wins on graphics API support. It provides DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4, while the Rubin GPU reports N/A for all three. Any application requiring these APIs can only run on the mobile part.

The RTX 4000 Mobile Ada Generation wins on power efficiency. Its 110 W TDP produces 24.72 TFLOPS FP32, while the Rubin GPU's 2300 W TDP produces 130.0 TFLOPS FP32. The mobile part achieves 0.225 TFLOPS per watt, the Rubin GPU achieves 0.057 TFLOPS per watt, a 3.9 times efficiency advantage for the mobile part.

The RTX 4000 Mobile Ada Generation wins on base clock. Its 1290 MHz base clock exceeds the Rubin GPU's 700 MHz. It also wins on memory clock at 2250 MHz versus 2695 MHz when normalized to effective data rate, though the Rubin GPU's wider bus more than compensates. The mobile part has 58 RT cores, while the Rubin GPU has no recorded RT core count.

For deployment, the RTX 4000 Mobile Ada Generation suits mobile workstations, portable devices, and any environment requiring display output or graphics API compatibility. The Rubin GPU suits server installations, data-center compute, and workloads that can consume 2300 W and use a 2700 W power supply. The pixel rate advantage of the mobile part makes it the only option for rendering to displays, while the Rubin GPU's massive memory and compute resources target large-scale parallel workloads.