NVIDIA A2 vs NVIDIA T1000 8 GB Comparison

The NVIDIA A2 and NVIDIA T1000 8 GB are both end-of-life workstation GPUs from NVIDIA, but they target very different workloads. The A2 is an Ampere-generation accelerator built for compute density, while the T1000 is a Turing-generation card focused on traditional graphics output. Benchmark data shows these two are incredibly close in average performance, but their architectural priorities could not be more different.

Head-to-Head Benchmarks

The only direct benchmark comparison available is Geekbench Vulkan, where the NVIDIA T1000 8 GB wins with a score of 34561 against the NVIDIA A2’s 34023. That is a 1.6% delta in favor of the T1000, which is well within typical run-to-run variance. The T1000’s win here is notable because Vulkan is a graphics API, and the T1000 has dedicated display outputs, while the A2 has none. The A2’s Vulkan score of 34023 is still respectable, but it trails its rival in this specific test.

Looking at the broader average benchmark scores, the story tightens considerably. The A2’s average benchmark score is 34690, while the T1000’s is 34561. That puts the A2 ahead by 0.4%, a razor-thin margin that flips the head-to-head result. In the nearest rivals list, the A2 is listed with a 0.4% positive delta against the T1000’s average score, while the T1000 is listed with a -0.4% delta against the A2. Both cards sit at the 79th percentile among all GPUs, meaning they occupy essentially the same performance tier.

The A2 also has a Geekbench OpenCL score of 35357, which is its strongest result. The T1000 has no OpenCL score listed, so the A2 likely holds an advantage in compute-oriented OpenCL workloads, but the data cannot confirm this directly. What the data does show is that the A2’s average score is dragged down by its Vulkan result, while the T1000’s average is based solely on its Vulkan score. If the T1000 had an OpenCL score, its average could shift either way, but as it stands, the A2 edges ahead in the aggregate.

Other rivals in the same performance neighborhood include the AMD Radeon HD 7970 (average score 34541) and the NVIDIA TITAN V (average score 34355). The A2 leads the HD 7970 by 0.4% and the TITAN V by 1%, while the T1000 leads the HD 7970 by 0.1% and the TITAN V by 0.6%. The NVIDIA RTX A1000 sits slightly behind both, with an average score of 34207 — the A2 leads it by 1.4% and the T1000 by 1%. Neither card blows its rivals away; these are tightly clustered results.

Architecture Differences

The A2 uses the GA107 chip on an 8 nm Samsung process, while the T1000 uses the TU117 chip on a 12 nm TSMC process. The A2’s Ampere architecture includes 8,700 million transistors on a 200 mm² die, giving it a transistor density of 43.5 million per mm². The T1000’s Turing architecture packs 4,700 million transistors on the same 200 mm² die, yielding a density of 23.5 million per mm². The A2 is built on a more advanced process that fits nearly twice the transistors into the same physical space.

The compute resources tell a clear story. The A2 has 1280 shading units, 40 texture mapping units, and 32 raster output pipelines. The T1000 has fewer shading units at 896, but more TMUs at 56, with the same 32 ROPs. The A2 also carries 10 RT cores and 40 tensor cores, while the T1000 has none listed for either. This is a major architectural split: the A2 supports hardware ray tracing and tensor operations, while the T1000 does not.

Memory configurations differ as well. The A2 comes with 16 GB of GDDR6 on a 128-bit bus, delivering 200.1 GB/s of bandwidth. The T1000 has 8 GB of GDDR6 on the same 128-bit bus, with 160.0 GB/s of bandwidth. The A2’s memory clock runs at 1563 MHz (12.5 Gbps effective), while the T1000’s runs at 1250 MHz (10 Gbps effective). The A2 offers double the capacity and 25% more bandwidth.

Clock speeds favor the A2 on paper. The A2 has a base clock of 1440 MHz and a boost clock of 1770 MHz, compared to the T1000’s 1065 MHz base and 1395 MHz boost. Despite the higher clocks, the A2’s FP32 throughput is 4.531 TFLOPS, while the T1000 manages only 2.500 TFLOPS. The T1000 does reach 5.000 TFLOPS in FP16 thanks to a 2:1 ratio, while the A2 stays at 4.531 TFLOPS with a 1:1 ratio. Pixel rates favor the A2 at 56.64 GPixel/s versus 44.64 GPixel/s, but the T1000 wins texture rate at 78.12 GTexel/s versus 70.80 GTexel/s.

FAQ

Q: Which GPU has more memory?

A: The NVIDIA A2 has 16 GB of GDDR6, while the NVIDIA T1000 8 GB has 8 GB of GDDR6. The A2 also has higher bandwidth at 200.1 GB/s versus 160.0 GB/s.

Q: Does the T1000 support ray tracing?

A: No. The T1000 has no RT cores or tensor cores listed, while the A2 includes 10 RT cores and 40 tensor cores.

Q: Which GPU is faster in Vulkan benchmarks?

A: The T1000 wins the Geekbench Vulkan test with a score of 34561 against the A2’s 34023, a 1.6% difference.

Q: What is the average benchmark score difference between the two?

A: The A2 has an average benchmark score of 34690, which is 0.4% higher than the T1000’s 34561.

Q: Do both GPUs have display outputs?

A: No. The T1000 has 4x mini-DisplayPort 1.4a outputs, while the A2 has no display outputs at all.

Q: What are the power requirements?

A: The A2 has a TDP of 60 W, and the T1000 has a TDP of 50 W. Both have no power connectors and recommend a 250 W PSU.

The Verdict

The data points to a clear conclusion: pick the NVIDIA A2 if you need compute features, memory capacity, and raw FP32 throughput. Pick the NVIDIA T1000 8 GB if you need display outputs and a slight edge in graphics API benchmarks. The A2 dominates in shading units (1280 vs 896), FP32 performance (4.531 TFLOPS vs 2.500 TFLOPS), memory size (16 GB vs 8 GB), and bandwidth (200.1 GB/s vs 160.0 GB/s). It also brings RT cores and tensor cores that the T1000 lacks entirely.

The T1000’s advantages are narrower but real. It wins the only head-to-head benchmark (Vulkan, 34561 vs 34023), has a higher texture rate (78.12 GTexel/s vs 70.80 GTexel/s), and offers 4x mini-DisplayPort outputs. It also has a lower TDP at 50 W versus 60 W, and a longer physical footprint at 156 mm (6.1 inches) compared to the A2’s unspecified length. The T1000’s FP16 performance of 5.000 TFLOPS exceeds the A2’s 4.531 TFLOPS, but that comes from a 2:1 ratio that is less flexible than the A2’s 1:1 FP16.

For a database-driven decision, the A2 is the more capable compute card. Its average benchmark score is higher, its architecture is newer (Ampere vs Turing), and its feature set is strictly broader. The T1000 is the choice only when display output is mandatory or when the Vulkan benchmark result is the priority.

Specification Differences

| Specification | NVIDIA A2 | NVIDIA T1000 8 GB |

|---|---|---|

| Architecture | Ampere | Turing |

| Process Node | 8 nm | 12 nm |

| Foundry | Samsung | TSMC |

| Transistors | 8,700 million | 4,700 million |

| Die Size | 200 mm² | 200 mm² |

| Transistor Density | 43.5M / mm² | 23.5M / mm² |

| Base Clock | 1440 MHz | 1065 MHz |

| Boost Clock | 1770 MHz | 1395 MHz |

| Memory Clock | 1563 MHz (12.5 Gbps effective) | 1250 MHz (10 Gbps effective) |

| Memory Size | 16 GB | 8 GB |

| Memory Type | GDDR6 | GDDR6 |

| Memory Bus Width | 128 bit | 128 bit |

| Memory Bandwidth | 200.1 GB/s | 160.0 GB/s |

| Shading Units | 1280 | 896 |

| TMUs | 40 | 56 |

| ROPs | 32 | 32 |

| RT Cores | 10 | None |

| Tensor Cores | 40 | None |

| Pixel Rate | 56.64 GPixel/s | 44.64 GPixel/s |

| Texture Rate | 70.80 GTexel/s | 78.12 GTexel/s |

| FP32 Performance | 4.531 TFLOPS | 2.500 TFLOPS |

| FP16 Performance | 4.531 TFLOPS (1:1) | 5.000 TFLOPS (2:1) |

| TDP | 60 W | 50 W |

| Bus Interface | PCIe 4.0 x8 | PCIe 3.0 x16 |

| Display Outputs | No outputs | 4x mini-DisplayPort 1.4a |

| DirectX Version | 12 Ultimate (12_2) | 12 (12_1) |

| Release Date | 2021-11-09 | 2021-05-05 |

Where Each One Wins

The NVIDIA A2 wins in compute-heavy scenarios. Its 1280 shading units and 40 tensor cores make it the pick for machine learning inference or any workload that can leverage tensor operations. The 16 GB memory capacity is double the T1000’s, which matters for large datasets or models that exceed 8 GB. The A2’s 4.531 TFLOPS of FP32 throughput is 81% higher than the T1000’s 2.500 TFLOPS, and its pixel rate of 56.64 GPixel/s beats the T1000’s 44.64 GPixel/s.

The NVIDIA T1000 8 GB wins in graphics output and efficiency-focused tasks. Its 4x mini-DisplayPort 1.4a outputs make it the only option here for driving physical displays. The T1000’s texture rate of 78.12 GTexel/s exceeds the A2’s 70.80 GTexel/s, which can help in texture-bound workloads. Its lower TDP of 50 W versus 60 W gives it a marginal power advantage. The T1000 also wins the Vulkan benchmark outright, suggesting it may have an edge in Vulkan-based applications.

The architecture split is stark: the A2 is a headless compute accelerator with RT and tensor cores, while the T1000 is a traditional workstation GPU with display outputs and no ray tracing or tensor hardware. If the workload is server-side compute, the A2 is the clear choice. If the workload is desktop graphics or requires physical display connectivity, the T1000 is the only option that fits. Both cards sit at the 79th percentile of all GPUs, but they serve different segments of that percentile.