NVIDIA A10M vs NVIDIA GB10 Comparison

NVIDIA A10M and NVIDIA GB10 are both server-class accelerators, but benchmark results place them in different tiers. In the only shared benchmark test, the A10M is the clear victor: it scores 135,230 in Geekbench OpenCL against the GB10’s 120,137, a 12.6% advantage. However, the GB10 counters with a substantially larger memory pool and a far more modern GPU architecture, making the choice between them heavily dependent on workload priorities. The data shows the A10M is the stronger raw compute performer in OpenCL, placing in the 96th percentile of all GPUs, while the GB10 sits just behind in the 95th percentile.

Head-to-Head Benchmarks

The head-to-head comparison is limited to a single Geekbench OpenCL run, and the results are decisive. The NVIDIA A10M achieves a score of 135,230, outpacing the NVIDIA GB10’s 120,137 by 12.6%. This is not a marginal difference; it represents a significant performance gap in compute-heavy OpenCL workloads. The A10M’s win is consistent with its higher average benchmark score of 135,230, whereas the GB10’s average across its two benchmark entries (OpenCL and Vulkan) is 117,393.

Looking at the nearest rivals provides context for these scores. The A10M’s 135,230 score puts it in a tight cluster with the NVIDIA RTX 4000 Ada Generation (135,218, a 0% delta) and the AMD Radeon PRO W6800 (135,396, a -0.1% delta). This means the A10M is effectively tied with these cards in OpenCL performance, differing by less than 1%. The GB10’s OpenCL score of 120,137, meanwhile, is bracketed by the NVIDIA RTX 4000 SFF Ada Generation (117,088, a 0.3% delta in favor of the GB10) and the AMD Radeon PRO W7700 (118,976, a -1.3% delta for the GB10). Notably, the GB10 also outperforms the NVIDIA Tesla V100 SXM2 16 GB by 2.6% and the NVIDIA RTX A5500 Mobile by 3% in its average score.

The GB10 also has a separate Vulkan benchmark result of 114,648, which is not present for the A10M. This score is lower than its OpenCL result, suggesting the GB10’s performance can vary by API. However, without a comparable Vulkan score for the A10M, a direct cross-API comparison is not possible from the data. The single shared benchmark clearly favors the A10M, but the GB10’s architectural advantages may shift the balance in other scenarios.

FAQ

Q: Which GPU has the higher Geekbench OpenCL score?

A: The NVIDIA A10M scores 135,230, which is 12.6% higher than the NVIDIA GB10’s score of 120,137.

Q: How does the GB10 compare to its nearest rivals in average benchmark score?

A: The GB10’s average score of 117,393 is 0.3% higher than the NVIDIA RTX 4000 SFF Ada Generation’s 117,088, but it is 1.3% lower than the AMD Radeon PRO W7700’s 118,976. It also leads the Tesla V100 SXM2 16 GB by 2.6% and the RTX A5500 Mobile by 3%.

Q: What is the memory capacity difference between the two cards?

A: The GB10 has 128 GB of LPDDR5X memory, which is vastly larger than the A10M’s 20 GB of GDDR6 memory. This is a 108 GB difference in favor of the GB10.

Q: Are there any benchmark tests where the GB10 wins?

A: The head-to-head data only includes one Geekbench OpenCL test, which the A10M wins. The GB10 does have a Vulkan score of 114,648, but no corresponding A10M Vulkan score exists for comparison.

Q: Which card has a higher boost clock speed?

A: The GB10 has a boost clock of 2418 MHz, which is significantly higher than the A10M’s boost clock of 1635 MHz. The GB10 also has a higher base clock at 1665 MHz versus 975 MHz.

Q: What is the production status of each card?

A: The NVIDIA A10M is listed as end-of-life, while the NVIDIA GB10 is listed as active and was released on 2025-10-14.

Architecture Differences

The architectural gap between these two GPUs is substantial. The A10M is built on the Ampere architecture using the GA102 chip, manufactured on an 8 nm process at Samsung. It packs 28,300 million transistors onto a 628 mm² die, resulting in a transistor density of 45.1M per mm². In contrast, the GB10 uses the newer Blackwell 2.0 architecture with the GB20B chip, fabricated by TSMC on a more advanced 5 nm node. The GB10’s die size is 382 mm², and while its transistor count is listed as unknown, the smaller die on a denser process node suggests a different design philosophy focused on efficiency and integration.

Core configurations also diverge significantly. The A10M has 7,168 shading units, 224 TMUs, and 80 ROPs, while the GB10 has fewer shading units at 6,144 but more TMUs at 384 and fewer ROPs at 48. The A10M features 56 ray tracing cores and 224 tensor cores, whereas the GB10 has 48 RT cores and 384 tensor cores. This means the GB10 has 71% more tensor cores than the A10M, pointing to a stronger emphasis on AI and matrix operations. The GB10’s texture rate of 928.5 GTexel/s is more than double the A10M’s 366.2 GTexel/s, highlighting its superior texture processing capability.

Memory architecture differs fundamentally. The A10M uses 20 GB of GDDR6 on a 320-bit bus, delivering 500.2 GB/s of bandwidth. The GB10 uses 128 GB of LPDDR5X on a 256-bit bus, but its bandwidth is lower at 273.2 GB/s. The GB10’s memory is slower per-pin but offers six times the capacity. The API support also differs: the A10M supports DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4, while the GB10 lists N/A for all three, indicating it is not designed for traditional graphics APIs.

The Verdict

The data points to a clear split: the NVIDIA A10M is the superior choice for raw OpenCL compute performance, while the NVIDIA GB10 is the better option for memory-intensive and AI-focused tasks. The A10M wins the only direct benchmark, posting a 12.6% higher Geekbench OpenCL score. Its 96th percentile ranking versus the GB10’s 95th percentile confirms its edge in general compute. If a workload is dominated by OpenCL execution, the A10M is the data-backed winner.

However, the GB10 is not a weak card. Its 128 GB memory capacity dwarfs the A10M’s 20 GB, making it the only option for datasets that exceed 20 GB. Its 384 tensor cores, compared to the A10M’s 224, suggest better performance in tensor-based operations, even if no direct benchmark confirms this. The GB10’s higher boost clock of 2418 MHz versus 1635 MHz also indicates potential for higher burst performance in clock-sensitive tasks. For users prioritizing memory capacity and modern tensor hardware, the GB10 is the logical pick, despite losing the OpenCL test.

The A10M’s end-of-life status is a critical factor. It is a mature product with proven drivers, but it is no longer actively produced. The GB10, released on 2025-10-14, is active and has a known launch MSRP of 3,999 USD. The A10M has no launch MSRP listed. The choice ultimately depends on whether the user needs the A10M’s compute lead or the GB10’s massive memory and newer architecture.

Specification Differences

The specification sheet reveals several key differences between the two cards. The most striking gap is memory size: the GB10 offers 128 GB of LPDDR5X, while the A10M has only 20 GB of GDDR6. This is a 108 GB difference. The memory type, bus width, and bandwidth also differ: the A10M uses a 320-bit bus for 500.2 GB/s, whereas the GB10 uses a 256-bit bus for 273.2 GB/s.

Clock speeds favor the GB10. Its base clock is 1665 MHz and boost is 2418 MHz, compared to the A10M’s 975 MHz base and 1635 MHz boost. The memory clock is also higher on the A10M at 1563 MHz (12.5 Gbps effective) versus the GB10’s 1067 MHz (8.5 Gbps effective). The A10M has more shading units (7,168 vs 6,144) and more ROPs (80 vs 48), but the GB10 has more TMUs (384 vs 224) and tensor cores (384 vs 224). Pixel rates are close: 130.8 GPixel/s for the A10M and 116.1 GPixel/s for the GB10, while texture rates strongly favor the GB10 at 928.5 GTexel/s versus 366.2 GTexel/s.

Physical and power characteristics differ as well. The A10M is a single-slot card measuring 267 mm in length and 112 mm in height, with an 8-pin EPS power connector and a 150 W TDP. The GB10 is an IGP (integrated graphics processor) with no power connectors, a 140 W TDP, and much smaller dimensions at 150 mm by 51 mm by 150 mm. The GB10 also has a display output (1x HDMI), while the A10M has none. Bus interfaces are PCIe 4.0 x16 for the A10M and PCIe 5.0 x16 for the GB10. The A10M is built on an 8 nm process with a 628 mm² die, while the GB10 uses 5 nm and a 382 mm² die.

Where Each One Wins

The NVIDIA A10M wins in scenarios that demand maximum OpenCL throughput. Its 12.6% lead over the GB10 in Geekbench OpenCL is the headline figure, and its higher memory bandwidth of 500.2 GB/s means it can feed its 7,168 shading units faster than the GB10 can feed its 6,144. The A10M is also the only card with full graphics API support (DirectX 12 Ultimate, OpenGL 4.6, Vulkan 1.4), making it suitable for compute tasks that also require a display or graphics rendering. Its 96th percentile ranking places it above the GB10’s 95th, making it the safer bet for pure performance metrics.

The NVIDIA GB10 wins in memory capacity and tensor processing. The 128 GB memory pool is unmatched by the A10M, enabling workloads that involve massive datasets, large language models, or high-resolution simulations that would not fit in 20 GB. Its 384 tensor cores are 71% more than the A10M’s 224, suggesting a clear advantage in AI inference and training tasks that leverage tensor operations. The GB10’s higher boost clock (2418 MHz vs 1635 MHz) and faster texture rate (928.5 GTexel/s vs 366.2 GTexel/s) also make it more responsive in texture-heavy or clock-sensitive workloads. The GB10 is the newer, active product with a longer production runway, making it the more future-proof investment for ongoing deployments.