NVIDIA B300 SXM6 AC vs NVIDIA Quadro GP100 Comparison

The Verdict

The data presents a stark generational divide. The NVIDIA B300 SXM6 AC is an absolute compute monster, scoring 369,831 in Geekbench OpenCL, which places it at the 100th percentile of all GPUs in the database. The Quadro GP100, a capable professional card in its own right, scores 87,445 and sits at the 93rd percentile. The B300 is 322.9% faster in this single benchmark, a gap that dwarfs the difference between the B300 and its nearest rivals. For anyone building a high-end server or AI compute node, the B300 is the only logical choice from this pair. The Quadro GP100, with its 16 GB of HBM2 memory, 10.34 TFLOPS FP32 performance, and display outputs, remains relevant only for legacy workstation tasks where the B300 cannot function, as the B300 has no display outputs and a TDP of 1100 W that demands a 1500 W power supply. The verdict is clear: the B300 is for modern data center brute force, while the GP100 is a dated, albeit still functional, workstation relic.

FAQ

Q: How much faster is the NVIDIA B300 SXM6 AC than the Quadro GP100?

A: In the Geekbench OpenCL benchmark, the B300 scores 369,831 compared to the GP100's 87,445, making it 322.9% faster.

Q: Which GPU has more memory, and what is the configuration?

A: The B300 has 288 GB of HBM3e memory on an 8192-bit bus, while the Quadro GP100 has 16 GB of HBM2 memory on a 4096-bit bus.

Q: Can the B300 be used in a standard desktop workstation?

A: The data suggests no. The B300 is an SXM Module with no display outputs and requires a 1500 W power supply, indicating it is designed for server racks, not desktop workstations.

Q: Does the Quadro GP100 support modern graphics APIs?

A: Yes, the GP100 supports DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.3. The B300's API support is listed as N/A, meaning it lacks these graphics interfaces.

Q: Which GPU is more power-efficient?

A: The Quadro GP100 has a TDP of 235 W, while the B300 has a TDP of 1100 W. However, the B300 delivers far more performance per unit of time, as its raw score is over 4 times higher.

Q: What is the production status of each card?

A: The B300 is listed as Active, while the Quadro GP100 is End-of-life. This aligns with their release dates, with the B300 released in September 2025 and the GP100 released in September 2016.

Architecture Differences

The two GPUs represent opposite ends of NVIDIA's architectural timeline. The B300 uses the GB110 chip built on the Blackwell Ultra architecture, fabricated on a 5 nm process at TSMC. It packs 208,000 million transistors into a massive 1628 mm² die, yielding a transistor density of 127.8 million per square millimeter. The Quadro GP100 uses the GP100 chip on the older Pascal architecture, built on a 16 nm process, also at TSMC. Its 15,300 million transistors occupy a 610 mm² die with a density of 25.1 million per square millimeter. The B300 has 18,944 shading units, 592 TMUs, and only 24 ROPs, while the GP100 has 3,584 shading units, 224 TMUs, and 96 ROPs. Notably, the B300 has 592 tensor cores, while the GP100 has none. The B300 also features 592 RT cores, but the data lists them as null, meaning the field is not applicable or not recorded. The GP100's ROP count is 4 times higher, which explains its relatively high pixel rate despite its age. The B300 supports PCIe 6.0 x16, while the GP100 supports PCIe 3.0 x16. The B300's memory clock is 2000 MHz (8 Gbps effective), whereas the GP100's memory runs at 715 MHz (1,430 Mbps effective). This is a fundamental generational shift in compute capability, with the B300 designed for tensor-heavy workloads and the GP100 for traditional graphics and compute.

Specification Differences

The specification sheet shows a clear divergence. The B300 has a base clock of 1665 MHz and a boost clock of 2032 MHz, while the GP100 has a base clock of 1304 MHz and a boost clock of 1443 MHz. The B300's memory bandwidth is 8.19 TB/s, which is over 11 times the GP100's 732.2 GB/s. In raw compute, the B300 delivers 76.99 TFLOPS FP32 and 76.99 TFLOPS FP16 (1:1 ratio), whereas the GP100 delivers 10.34 TFLOPS FP32 and 20.69 TFLOPS FP16 (2:1 ratio). The B300's texture rate is 1,202.9 GTexel/s versus the GP100's 323.2 GTexel/s. However, the GP100 has a higher pixel rate at 138.5 GPixel/s compared to the B300's 48.77 GPixel/s, due to its higher ROP count. The B300 is a dual-slot SXM module with no power connectors listed, while the GP100 is a dual-slot card with a single 8-pin power connector. The B300 has no display outputs, while the GP100 has 1x DVI and 4x DisplayPort 1.4a outputs. The GP100 is a physical card measuring 267 mm in length and 111 mm in height, while the B300's dimensions are not listed. The B300's TDP is 1100 W with a suggested PSU of 1500 W, while the GP100's TDP is 235 W with a suggested PSU of 550 W. The B300 is an active product, released in September 2025, and its predecessor is Server Hopper, with a successor of Server Rubin. The GP100 is end-of-life, released in September 2016, with a predecessor of Quadro Maxwell and a successor of Quadro Volta. Neither card has a launch MSRP listed.

Head-to-Head Benchmarks

The only recorded head-to-head benchmark is Geekbench OpenCL. The B300 scores 369,831, while the GP100 scores 87,445. This gives the B300 a 322.9% advantage, a massive delta. To contextualize this, the B300's nearest rival, the NVIDIA B200, scores 345,482, which is 7% slower. The NVIDIA H200 NVL scores 334,891, 10.4% behind, and the AMD Instinct MI300X scores 317,994, 16.3% behind. The NVIDIA L40S scores 295,763, 25% behind. The B300 is so far ahead that it sits at the 100th percentile of all GPUs. On the other side, the GP100's nearest rivals are much closer. The AMD Radeon PRO W7600 scores 87,108, only 0.4% behind, and the NVIDIA CMP 40HX scores 85,637, 2.1% behind. The NVIDIA RTX A4500 Mobile scores 91,134, which is 4% ahead of the GP100, and the NVIDIA RTX A4500 scores 91,671, 4.6% ahead. The GP100's 93rd percentile ranking is respectable, but it is in a completely different performance class from the B300. The data shows that the B300 is not just a generation ahead, it is a leap that dwarfs any incremental improvements seen in the GP100's own era.

Where Each One Wins

The B300 wins in every compute metric that matters for modern data center workloads. Its FP32 performance is 76.99 TFLOPS, which is 7.4 times the GP100's 10.34 TFLOPS. Its FP16 performance is 76.99 TFLOPS, which is 3.7 times the GP100's 20.69 TFLOPS. The B300 has 288 GB of HBM3e memory, enabling it to handle huge models, while the GP100's 16 GB is a limiting factor. The B300's 8.19 TB/s bandwidth is critical for memory-bound tasks. The B300's tensor cores are essential for AI and deep learning, a feature the GP100 lacks entirely. The B300 wins 1 benchmark in the head-to-head comparison.

The GP100 wins in legacy workstation scenarios. It has display outputs, enabling it to drive monitors, while the B300 has none. It supports DirectX 12, OpenGL 4.6, and Vulkan 1.3, making it usable for traditional graphics applications, whereas the B300's API support is listed as N/A. The GP100 has a higher pixel rate (138.5 GPixel/s versus 48.77 GPixel/s), which is relevant for rasterization tasks. Its lower TDP of 235 W makes it easier to integrate into existing workstation builds without requiring a 1500 W power supply. However, the GP100 wins 0 benchmarks in the head-to-head comparison. The data implies that the GP100 is only a viable choice for users who need a GPU in a desktop environment with graphics output and cannot accommodate the server-only B300. For raw computational throughput, the B300 is categorically superior.