AMD FirePro S9300 X2 vs NVIDIA Quadro GV100 Comparison

The NVIDIA Quadro GV100 and AMD FirePro S9300 X2 represent two very different approaches to professional computing, separated by two years of architectural evolution and targeting distinct workloads. The data shows a clear performance hierarchy, but the FirePro S9300 X2 holds its own in specific legacy scenarios. This analysis breaks down the benchmark results, architectural divergences, and practical implications based strictly on the provided specifications.

Head-to-Head Benchmarks

The benchmark comparison between these two cards is decisively one-sided in favor of the NVIDIA Quadro GV100. In the Geekbench OpenCL test, the GV100 scores 150,004 points against the FirePro S9300 X2’s 27,971 points, a staggering 436.3% delta. This is not a marginal lead; it represents a fundamental generational gap in compute capability. For context, the GV100’s average benchmark score of 35,520 places it in the 80th percentile of all GPUs, while the FirePro’s 32,540 average sits in the 77th percentile. The OpenCL result alone explains most of that percentile gap.

The Vulkan test tells a similar story, though with a slightly smaller margin. The GV100 scores 139,526 points versus the FirePro’s 37,109, resulting in a 276% delta. While both are professional cards, Vulkan performance is less critical for typical workstation loads than OpenCL or DirectX, but the sheer magnitude of the lead remains notable. Across both head-to-head tests, the NVIDIA card wins 2 out of 2, with no benchmark where the AMD card comes out ahead.

Looking at the rival landscape, the GV100’s average score of 35,520 puts it within 0.2% of the NVIDIA GeForce RTX 5070 Ti Mobile (35,435) and 0.9% behind the AMD Radeon Pro Duo (35,860). This suggests the GV100, despite being from the Volta generation, still competes with much newer mobile parts. The FirePro S9300 X2’s average of 32,540 is nearly identical to the AMD Radeon RX 590 GME (32,601, a -0.2% delta) and the AMD Radeon RX 7900 GRE (32,456, a +0.3% delta). This indicates that while the FirePro is older, its compute performance remains competitive with mid-range consumer cards from much later generations.

The disparity is further highlighted by the available DirectX and Passmark scores for the GV100, which are entirely absent for the FirePro. The GV100 posts 207 in Passmark DirectX 9, 168 in DirectX 11, 140 in DirectX 10, and 84 in DirectX 12. Its Passmark G3D score is 19,650, and GPU compute is 9,069. The FirePro has no comparable data, meaning its DirectX and rasterization performance is either untested or so poor that it was not recorded. For a card with 64 ROPs and a GCN 3.0 architecture, this is expected, but it means the only valid cross-card comparisons are the two Geekbench tests.

Architecture Differences

The architectural gap between these two cards is enormous. The NVIDIA Quadro GV100 uses the GV100 chip on a 12 nm process at TSMC, packing 21,100 million transistors onto an 815 mm² die. The AMD FirePro S9300 X2 uses the Capsaicin chip on a 28 nm process, also at TSMC, with 8,900 million transistors on a 596 mm² die. The transistor density tells the story: the GV100 achieves 25.9 million transistors per mm², while the FirePro manages only 14.9 million per mm². This is a direct consequence of the process node difference, and it explains why the GV100 can fit more than twice the transistors into a die that is only 37% larger.

The GV100 is built on the Volta architecture, which introduces dedicated tensor cores (640 of them) for AI and deep learning workloads. The FirePro S9300 X2, based on GCN 3.0, has no tensor cores at all. This is a critical differentiator for modern compute tasks. Additionally, the GV100 features 5,120 shading units, 320 TMUs, and 128 ROPs, compared to the FirePro’s 4,096 shading units, 256 TMUs, and 64 ROPs. The NVIDIA card has 25% more shading units, 25% more TMUs, and double the ROPs.

Memory is another major divergence. The GV100 comes with 32 GB of HBM2 on a 4096-bit bus, delivering 868.4 GB/s of bandwidth. The FirePro has only 4 GB of HBM on an identical 4096-bit bus, yielding 512.0 GB/s. While both use a wide bus, the FirePro’s memory runs at 500 MHz (1000 Mbps effective) versus the GV100’s 848 MHz (1696 Mbps effective). The result is that the GV100 offers 8 times the capacity and nearly 70% more bandwidth. For large datasets or high-resolution rendering, this is a decisive advantage.

The GV100 also supports FP16 compute at 33.32 TFLOPS (2:1 ratio), while the FirePro lists no FP16 capability at all. In FP32, the GV100 delivers 16.66 TFLOPS versus the FirePro’s 7.987 TFLOPS, a 2.08x lead. Pixel and texture rates follow suit: the GV100 achieves 208.3 GPixel/s and 520.6 GTexel/s, while the FirePro manages 62.40 GPixel/s and 249.6 GTexel/s. The power draw is also notable: the GV100 has a 250 W TDP with a single 8-pin connector, while the FirePro has a 300 W TDP with two 8-pin connectors. The FirePro also requires a 700 W suggested PSU versus 600 W for the GV100.

The Verdict

The data is unambiguous: for any modern compute, rendering, or AI workload, the NVIDIA Quadro GV100 is the superior card. Its 436.3% lead in OpenCL and 276% lead in Vulkan are not incremental; they are transformative. The GV100’s 32 GB of HBM2 memory, tensor cores, and higher FP32 throughput make it suitable for tasks that the FirePro simply cannot handle. The FirePro S9300 X2, with its 4 GB memory limit and lack of FP16 support, is confined to legacy applications or specific server deployments where its dual-GPU design (implied by the “X2” naming) was optimized for a narrow set of scientific workloads.

However, the FirePro is not without merit. Its 77th percentile ranking shows it still outperforms a majority of GPUs, and its average score of 32,540 is within 0.3% of the AMD Radeon RX 7900 GRE, a much newer card. For users with existing software optimized for GCN 3.0 and 4 GB memory requirements, the FirePro remains a functional option. The GV100, meanwhile, sits in the 80th percentile, with its average score of 35,520 nearly tied with the NVIDIA T1000 (36,289, a -2.1% delta) and the NVIDIA A2 (34,690, a +2.4% delta).

Who should pick which? From the data alone, the GV100 is the choice for anyone prioritizing raw compute, large memory footprints, or AI acceleration. The FirePro S9300 X2 is only justifiable for specific legacy server environments where its dual-chip design and lower launch MSRP (5,999 USD vs 8,999 USD) were the deciding factors at purchase time. There is no benchmark in the provided data where the FirePro wins, so any decision to choose it must be based on software compatibility rather than performance.

Specification Differences

The following specifications differ between the two cards:

• Chip: GV100 vs Capsaicin
• Architecture: Volta vs GCN 3.0
• Generation: Quadro Volta (Vx000) vs FirePro Server (Sx300)
• Process Node: 12 nm vs 28 nm
• Transistors: 21,100 million vs 8,900 million
• Die Size: 815 mm² vs 596 mm²
• Transistor Density: 25.9M / mm² vs 14.9M / mm²
• Memory Clock: 848 MHz (1696 Mbps effective) vs 500 MHz (1000 Mbps effective)
• Memory Size: 32 GB vs 4 GB
• Memory Type: HBM2 vs HBM
• Memory Bandwidth: 868.4 GB/s vs 512.0 GB/s
• Shading Units: 5,120 vs 4,096
• TMUs: 320 vs 256
• ROPs: 128 vs 64
• Tensor Cores: 640 vs None
• Pixel Rate: 208.3 GPixel/s vs 62.40 GPixel/s
• Texture Rate: 520.6 GTexel/s vs 249.6 GTexel/s
• FP32: 16.66 TFLOPS vs 7.987 TFLOPS
• FP16: 33.32 TFLOPS (2:1) vs None
• TDP: 250 W vs 300 W
• Power Connectors: 1x 8-pin vs 2x 8-pin
• Suggested PSU: 600 W vs 700 W
• Display Outputs: 4x DisplayPort 1.4a vs No outputs
• DirectX Support: 12 (12_1) vs 12 (12_0)
• Vulkan Support: 1.4 vs 1.2.170
• Release Date: 2018-03-26 vs 2016-03-30
• Predecessor: Quadro Pascal vs FirePro Terascale
• Successor: Quadro Turing vs Radeon Pro GCN
• Launch MSRP: 8,999 USD vs 5,999 USD

FAQ

Q: Which card is faster in OpenCL?

A: The NVIDIA Quadro GV100 is significantly faster, scoring 150,004 points versus the AMD FirePro S9300 X2’s 27,971 points, a 436.3% delta.

Q: Does the AMD FirePro S9300 X2 have any benchmark win over the NVIDIA Quadro GV100?

A: No. Across the two head-to-head benchmarks (Geekbench OpenCL and Geekbench Vulkan), the NVIDIA card wins both. The FirePro has zero wins.

Q: How much memory does each card have?

A: The NVIDIA Quadro GV100 has 32 GB of HBM2 memory with 868.4 GB/s bandwidth, while the AMD FirePro S9300 X2 has 4 GB of HBM memory with 512.0 GB/s bandwidth.

Q: Are there any tensor cores on the AMD FirePro S9300 X2?

A: No. The FirePro S9300 X2, based on GCN 3.0, has no tensor cores. The NVIDIA Quadro GV100 has 640 tensor cores.

Q: What is the FP32 compute performance difference?

A: The NVIDIA Quadro GV100 delivers 16.66 TFLOPS of FP32 performance, while the AMD FirePro S9300 X2 delivers 7.987 TFLOPS. The GV100 is roughly 2.08 times faster.

Q: Do both cards support the same DirectX version?

A: No. The NVIDIA Quadro GV100 supports DirectX 12 (12_1), while the AMD FirePro S9300 X2 supports DirectX 12 (12_0). The FirePro also has no display outputs, while the GV100 has 4x DisplayPort 1.4a.