NVIDIA RTX A6000 vs NVIDIA Tesla M40 Comparison

The NVIDIA RTX A6000 and NVIDIA Tesla M40 represent two distinct eras of professional GPU computing, and the benchmark data reflects a generational chasm. The RTX A6000, built on the Ampere architecture, is a modern workstation powerhouse, while the Tesla M40, based on Maxwell 2.0, is a legacy compute card from a previous decade. The data shows a decisive victory for the newer card, but the M40 still holds relevance in specific legacy compute scenarios. This analysis breaks down the head-to-head results, architectural shifts, and the specific strengths of each board.

Head-to-Head Benchmarks

The only overlapping benchmark tests in the data are Geekbench OpenCL and Geekbench Vulkan, and in both cases, the RTX A6000 delivers a crushing blow. In the Geekbench OpenCL test, the RTX A6000 scores 193,937, while the Tesla M40 manages just 39,192. This translates to a delta of 394.8% in favor of the RTX A6000, meaning it is nearly five times faster in this general-purpose compute workload. The margin is not merely incremental; it is a full generational leap that dwarfs any architectural refinement seen in previous years.

The Vulkan result tells a similar story, though with a slightly smaller, yet still massive, gap. The RTX A6000 posts 164,462 points, while the Tesla M40 scores 44,602. This yields a delta of 268.7% for the RTX A6000. This test stresses graphics API performance, and the M40’s older architecture simply cannot keep pace with the modern driver and hardware support of the Ampere card. The M40 fails to win a single head-to-head benchmark, resulting in a 2-0 sweep for the RTX A6000.

Looking at the broader average benchmark scores reinforces this dominance. The RTX A6000 carries an average benchmark score of 44,075, placing it in the 84th percentile of all GPUs. Its nearest rival, the NVIDIA GeForce RTX 4070 Ti, scores 44,795, putting the A6000 just 1.6% behind it. The Tesla M40, by contrast, has an average score of 41,897, sitting in the 83rd percentile. Its closest competitor, the NVIDIA Tesla M40 24 GB, scores 41,707, a mere 0.5% difference. While both cards are in the top tier of GPUs, the raw performance gap between the two is substantial, as evidenced by the specific test deltas.

Architecture Differences

The fundamental architectural divide is stark. The RTX A6000 utilizes the GA102 chip on an 8 nm process from Samsung, packing 28,300 million transistors onto a 628 mm² die. This results in a transistor density of 45.1M per mm². In contrast, the Tesla M40 is built on the GM200 chip using TSMC’s 28 nm process, containing 8,000 million transistors on a 601 mm² die. The M40’s density is just 13.3M per mm². This process shrink is the primary driver of the A6000’s efficiency and raw compute advantage.

The core configurations are equally divergent. The RTX A6000 features 10,752 shading units, 336 TMUs, and 112 ROPs. Critically, it also includes 84 RT cores and 336 tensor cores, dedicated hardware for ray tracing and AI workloads. The Tesla M40 has 3,072 shading units, 192 TMUs, and 96 ROPs, with no RT or tensor cores present. This means the M40 is purely a rasterization and compute device, lacking the specialized hardware that defines the modern Ampere generation.

Clock speeds and memory architectures also highlight the generational gap. The A6000 has a base clock of 1410 MHz and a boost clock of 1800 MHz, paired with 48 GB of GDDR6 memory on a 384-bit bus. This configuration yields a bandwidth of 768.0 GB/s. The M40 operates at a base clock of 948 MHz and a boost of 1112 MHz, using 12 GB of GDDR5 memory on the same 384-bit bus. Its bandwidth is significantly lower at 288.4 GB/s. The combination of higher clocks, newer memory, and more than triple the VRAM gives the A6000 an insurmountable lead in memory-bound tasks.

Where Each One Wins

The RTX A6000 wins in virtually every modern workload category. Its Geekbench OpenCL score of 193,937 indicates supremacy in general-purpose GPU compute, making it ideal for scientific simulation, deep learning inference, and video encoding. The presence of tensor cores, which deliver 38.71 TFLOPS of FP32 compute and a 1:1 FP16 ratio of 38.71 TFLOPS, makes it a formidable tool for AI research and development. The 48 GB of VRAM allows it to hold massive datasets and render complex scenes without spilling to system memory.

The Tesla M40, despite its losses, has a specific niche. Its architecture lacks display outputs, meaning it is strictly a server or compute card. Its 6.832 TFLOPS of FP32 performance, while small compared to the A6000’s 38.71 TFLOPS, is still sufficient for legacy compute tasks that do not require modern API features. The M40 supports DirectX 12 (12_1), while the A6000 supports DirectX 12 Ultimate (12_2). For older CUDA-based applications that were optimized for Maxwell’s compute capabilities, the M40 remains a functional, if slow, option. Its 12 GB of GDDR5 memory is also adequate for smaller models that were common in its 2015 release era.

Specification Differences

The two cards differ in nearly every measurable specification. The process node is a key separator: 8 nm for the A6000 versus 28 nm for the M40. The transistor count is a factor of 3.5, with the A6000 at 28,300 million and the M40 at 8,000 million. Memory size is a 4x difference: 48 GB versus 12 GB. Memory type also changes from GDDR6 to GDDR5, and effective speed jumps from 16 Gbps to 6 Gbps. Bandwidth more than doubles, moving from 768.0 GB/s to 288.4 GB/s.

The shading units and TMUs are drastically different, with the A6000 offering 10,752 and 336, respectively, versus the M40’s 3,072 and 192. ROPs are closer but still higher on the A6000 (112 vs 96). The A6000’s pixel rate is 201.6 GPixel/s and texture rate is 604.8 GTexel/s, while the M40 manages 106.8 GPixel/s and 213.5 GTexel/s. Power consumption is also higher on the newer card, with a 300 W TDP versus 250 W, and the suggested PSU is 700 W versus 600 W.

Interface support differs as well. The A6000 uses PCIe 4.0 x16 and offers 4x DisplayPort 1.4a outputs. The M40 uses PCIe 3.0 x16 and has no display outputs. The A6000 supports DirectX 12 Ultimate, while the M40 is limited to DirectX 12 (12_1). Both cards support OpenGL 4.6 and Vulkan 1.4, but the A6000’s implementation is newer and more optimized. The A6000 was released on 2020-10-04, with a launch MSRP of 4,649 USD, while the M40 predates it, launching on 2015-11-09.

FAQ

Q: Which card is faster in Geekbench OpenCL?

A: The NVIDIA RTX A6000 is significantly faster, scoring 193,937 compared to the Tesla M40’s 39,192, a delta of 394.8%.

Q: Does the Tesla M40 support ray tracing?

A: No. The Tesla M40 has no RT cores. The RTX A6000 includes 84 RT cores and 336 tensor cores for specialized workloads.

Q: What is the memory capacity difference?

A: The RTX A6000 has 48 GB of GDDR6 memory, while the Tesla M40 has 12 GB of GDDR5 memory. The A6000’s bandwidth is 768.0 GB/s versus 288.4 GB/s for the M40.

Q: Which card has a higher average benchmark score?

A: The RTX A6000 has an average benchmark score of 44,075, placing it in the 84th percentile. The Tesla M40 averages 41,897, in the 83rd percentile.

Q: Are there display outputs on the Tesla M40?

A: No. The Tesla M40 has no display outputs, making it a compute-only card. The RTX A6000 includes 4x DisplayPort 1.4a outputs.

Q: What are the power requirements for each card?

A: The RTX A6000 has a TDP of 300 W and suggests a 700 W PSU. The Tesla M40 has a TDP of 250 W and suggests a 600 W PSU.