NVIDIA RTX A1000 vs NVIDIA T1000 8 GB Comparison

The NVIDIA T1000 8 GB and NVIDIA RTX A1000 are both single-slot, 50 W workstation cards with 8 GB of GDDR6 memory, yet they belong to different architectural generations and deliver sharply different compute performance. In the single shared benchmark, the RTX A1000 dominates the T1000, but the comparison extends far beyond that one score, touching on transistor budgets, rendering features, and interface technology.

Head-to-Head Benchmarks

The only directly comparable benchmark in the data is Geekbench Vulkan, and it is not close. The NVIDIA RTX A1000 scores 49,574, while the NVIDIA T1000 8 GB scores 34,561. That is a delta of -30.3% for the T1000, meaning the RTX A1000 is roughly 43% faster in raw Vulkan compute throughput. This is a decisive victory for the Ampere-based card, and it aligns with the underlying hardware differences: the RTX A1000 carries 2,304 shading units versus 896 on the T1000, a 2.57x increase in raw shader count.

The RTX A1000 also posts a Geekbench OpenCL score of 52,078, though no comparable OpenCL result exists for the T1000 in this data set. The T1000’s only benchmark is that Vulkan score, so its average benchmark score is 34,561. The RTX A1000’s average across three tests (Vulkan, OpenCL, and 3DMark Steel Nomad DX12) is 34,207, which is actually slightly lower than the T1000’s single-score average. This happens because the 3DMark Steel Nomad DX12 result of 969 drags down the A1000’s average, even though its Vulkan and OpenCL numbers are far superior.

Notably, both cards share the same overall percentile rank of 79 among all GPUs, despite the large Vulkan gap. The nearest rival data reinforces this: the T1000’s closest competitor is the NVIDIA A2 at 34,690 (a -0.4% delta for the T1000), while the RTX A1000 sits near the NVIDIA RTX A2000 12 GB at 34,154 (a 0.2% delta for the A1000). Both cards are within 1% of NVIDIA TITAN V, with the T1000 at +0.6% and the A1000 at -0.4%. The data suggests that in mixed workload averages, these two cards land in a similar performance tier, but in Vulkan specifically, the RTX A1000 is in a different class.

FAQ

Q: Which card is faster in Vulkan?

A: The NVIDIA RTX A1000 is significantly faster, scoring 49,574 in Geekbench Vulkan versus 34,561 for the NVIDIA T1000 8 GB. This represents a -30.3% delta for the T1000, meaning the A1000 is roughly 43% ahead.

Q: Do both cards have the same amount of memory?

A: Yes, both the NVIDIA T1000 8 GB and the NVIDIA RTX A1000 feature 8 GB of GDDR6 memory on a 128-bit bus. However, the memory speed differs: the T1000 runs at 10 Gbps effective (producing 160.0 GB/s bandwidth), while the RTX A1000 runs at 12 Gbps effective (producing 192.0 GB/s bandwidth).

Q: Are these cards comparable in terms of power draw?

A: Yes, both are rated at 50 W TDP and are single-slot designs with no power connectors. Both also suggest a 250 W power supply. This makes them drop-in replacements in terms of power envelope.

Q: What is the architectural generation difference?

A: The NVIDIA T1000 8 GB is based on the Turing architecture (TU117 chip) on a 12 nm TSMC process, while the NVIDIA RTX A1000 uses the Ampere architecture (GA107 chip) on an 8 nm Samsung process. The T1000 is from the Quadro Turing generation, and the A1000 is from the Workstation Ampere generation.

Q: Does the RTX A1000 support ray tracing?

A: Yes, the RTX A1000 includes 18 RT cores and 72 tensor cores. The T1000 has no RT cores or tensor cores listed in its specifications, indicating it lacks dedicated hardware for these features.

Q: Which card has a higher transistor density?

A: The NVIDIA RTX A1000 has a much higher transistor density at 43.5M per mm², compared to 23.5M per mm² for the T1000. Both chips share the same 200 mm² die size, but the A1000 packs 8,700 million transistors versus 4,700 million on the T1000.

Architecture Differences

The architectural gap between these two cards is generational. The NVIDIA T1000 8 GB uses the Turing architecture with the TU117 chip, fabricated on a 12 nm TSMC process. It packs 4,700 million transistors into a 200 mm² die, yielding a transistor density of 23.5M per mm². The T1000 has 896 shading units, 56 texture mapping units, and 32 ROPs. It lacks any dedicated RT cores or tensor cores, meaning it has no hardware acceleration for ray tracing or AI inference tasks.

The NVIDIA RTX A1000, by contrast, is built on the Ampere architecture with the GA107 chip, manufactured on Samsung’s 8 nm process. It contains 8,700 million transistors on the same 200 mm² die, more than doubling the transistor density to 43.5M per mm². The A1000 features 2,304 shading units, 72 TMUs, and 32 ROPs. Critically, it adds 18 RT cores and 72 tensor cores, enabling hardware-accelerated ray tracing and tensor operations that the T1000 cannot perform.

These architectural differences manifest in compute throughput. The T1000 delivers 2.500 TFLOPS of FP32 performance and 5.000 TFLOPS of FP16 (at a 2:1 ratio). The RTX A1000 delivers 6.737 TFLOPS of FP32 and 6.737 TFLOPS of FP16 (at a 1:1 ratio). The A1000’s FP16 throughput is 35% higher than the T1000’s, and its FP32 throughput is 2.7x higher. The texture fill rate also favors the A1000 at 105.3 GTexel/s versus 78.12 GTexel/s for the T1000, while pixel rates are closer: 46.78 GPixel/s versus 44.64 GPixel/s.

Specification Differences

The two cards diverge on several key specifications. The process node differs: 12 nm TSMC for the T1000 versus 8 nm Samsung for the A1000. Transistor count nearly doubles, from 4,700 million to 8,700 million. Base clock speeds are lower on the A1000 (727 MHz versus 1065 MHz), but boost clocks are higher (1462 MHz versus 1395 MHz). Memory speed also differs, with the T1000 at 10 Gbps effective and the A1000 at 12 Gbps effective, resulting in bandwidth of 160.0 GB/s versus 192.0 GB/s.

The shading unit count is the largest gap: 896 versus 2,304. TMUs also differ (56 versus 72), while ROPs are identical at 32. The A1000 adds 18 RT cores and 72 tensor cores, which the T1000 lacks entirely. FP32 compute is 2.500 TFLOPS versus 6.737 TFLOPS, and FP16 is 5.000 TFLOPS (2:1) versus 6.737 TFLOPS (1:1). The bus interface changes from PCIe 3.0 x16 on the T1000 to PCIe 4.0 x8 on the A1000. DirectX support advances from 12 (12_1) to 12 Ultimate (12_2).

Physical dimensions differ slightly: the T1000 is 156 mm long (6.1 inches), while the A1000 is 163 mm long (6.4 inches). Height is identical at 69 mm (2.7 inches). Production status also differs, with the T1000 marked as end-of-life and the A1000 as active. Release dates are separated by nearly three years: May 2021 for the T1000 and April 2024 for the A1000.

Where Each One Wins

The NVIDIA RTX A1000 wins decisively in raw compute workloads. Its Vulkan score of 49,574 is 43% higher than the T1000’s 34,561, and its FP32 throughput of 6.737 TFLOPS is 2.7x greater. The inclusion of RT cores and tensor cores makes the A1000 the clear choice for ray-traced rendering, AI inference, and any workload that can leverage tensor operations. Its higher memory bandwidth (192.0 GB/s versus 160.0 GB/s) also benefits memory-bound tasks. The A1000’s PCIe 4.0 interface, even at x8 width, provides double the per-lane bandwidth of PCIe 3.0, which can reduce data transfer bottlenecks in large dataset workflows.

The NVIDIA T1000 8 GB’s advantages are narrower but real. Its higher base clock (1065 MHz versus 727 MHz) suggests better performance in lightly threaded or latency-sensitive tasks that do not scale with shader count. In the average benchmark score across all tests, the T1000 actually edges out the A1000 (34,561 versus 34,207), driven by the A1000’s relatively weak 3DMark Steel Nomad DX12 score of 969. The T1000 also has a slight edge in nearest-rival comparisons against the NVIDIA TITAN V (+0.6% versus -0.4%), indicating that in mixed workloads, the older card can hold its own.

For users with legacy software that predates Ampere optimizations, the T1000’s Turing architecture may offer more mature driver support. Its shorter length (156 mm versus 163 mm) could also be a factor in compact chassis, though both cards are single-slot. The T1000’s end-of-life status means it may be available at lower prices in the secondary market, but the data does not support a performance argument for choosing it over the A1000 in modern workloads. The RTX A1000 is the superior card for almost every compute scenario, with the T1000 only making sense for legacy compatibility or specific low-power, low-shader-count tasks where its higher base clock provides a marginal advantage.