NVIDIA RTX A1000 Mobile vs NVIDIA Tesla M40 24 GB Comparison

# Where Each One Wins

The benchmark data splits cleanly between the two NVIDIA offerings, with the RTX A1000 Mobile taking both head-to-head tests. In Geekbench OpenCL, the A1000 Mobile scores 48,703 against the Tesla M40 24 GB's 37,439 — a decisive 30.1% margin. This is the largest performance gap in the dataset and establishes the A1000 Mobile as the clear compute winner for OpenCL workloads. The Vulkan test tells a closer story: the A1000 Mobile posts 46,782 versus the M40's 45,975, a narrow 1.8% edge that still favors the newer architecture.

Context from the nearest-rival data reinforces this split. The A1000 Mobile's average benchmark score of 47,743 places it 1.5% behind the AMD Radeon RX 6800 XT (48,477) but 2.2% ahead of the AMD Radeon RX 6550M (46,702) and 2.4% ahead of the Intel Arc A530M (46,614). It also sits 2.5% above the AMD Radeon RX 5600M (46,601). The Tesla M40 24 GB, with an average of 41,707, sits in a different performance tier — it is 1.3% ahead of the GeForce RTX 3080 Ti (41,187) and 2.0% ahead of the AMD Radeon Pro 5300 (40,870), but trails its own nearest rival, the NVIDIA Tesla M40 (41,897), by 0.5%. The M40's percentile ranking of 83 against all GPUs is close to the A1000 Mobile's 85, but the raw scores show a meaningful gulf in average compute throughput.

Where each card wins depends on workload type. The A1000 Mobile dominates in OpenCL, likely benefiting from its newer instruction set and driver optimizations. The Vulkan results are nearly even, suggesting that the M40's older Maxwell 2.0 architecture can still hold its own in that API when the workload is not compute-bound. For users prioritizing OpenCL performance, the A1000 Mobile is the unambiguous choice. For Vulkan workloads, the difference is minor enough that other factors — memory capacity, power, or form factor — may decide the selection.

# Architecture Differences

The two GPUs come from different architectural generations and manufacturing processes. The RTX A1000 Mobile uses the GA107 chip on the Ampere architecture, built on Samsung's 8 nm process. It packs 8,700 million transistors into a 200 mm² die, yielding a transistor density of 43.5 million per square millimeter. The Tesla M40 24 GB uses the GM200 chip on the older Maxwell 2.0 architecture, fabricated by TSMC on a 28 nm process. It contains 8,000 million transistors spread across a much larger 601 mm² die, resulting in a transistor density of just 13.3 million per square millimeter. The A1000 Mobile's denser design reflects more than six years of process advancement between the two releases.

Core configurations differ substantially. The A1000 Mobile has 2,048 shading units, 64 texture mapping units, 32 ROPs, 16 ray tracing cores, and 64 tensor cores. The Tesla M40 24 GB has more raw shading units (3,072), more TMUs (192), and more ROPs (96), but it lacks both ray tracing cores and tensor cores entirely — features that did not exist in the Maxwell 2.0 era. The M40 compensates with raw throughput: its FP32 performance of 6.832 TFLOPS exceeds the A1000 Mobile's 4.669 TFLOPS. The A1000 Mobile offers FP16 at a 1:1 ratio (4.669 TFLOPS), while the M40 has no FP16 capability listed. The A1000 Mobile's pixel rate of 36.48 GPixel/s and texture rate of 72.96 GTexel/s are both lower than the M40's 106.8 GPixel/s and 213.5 GTexel/s, reflecting the M40's wider memory bus and higher ROP count.

Memory configurations highlight different design goals. The A1000 Mobile uses 4 GB of GDDR6 on a 128-bit bus, delivering 176.0 GB/s of bandwidth. The Tesla M40 24 GB offers 24 GB of GDDR5 on a 384-bit bus, providing 288.4 GB/s. The M40's sixfold memory capacity advantage makes it suited for large datasets, while the A1000 Mobile's lower capacity is typical of a mobile part. Clock speeds also differ: the A1000 Mobile runs at 630 MHz base and 1,140 MHz boost, while the M40 runs at 948 MHz base and 1,112 MHz boost. Memory clocks are 1,375 MHz (11 Gbps effective) for the A1000 Mobile and 1,502 MHz (6 Gbps effective) for the M40.

API support reflects architectural age. The A1000 Mobile supports DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4. The M40 supports DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.4 — notably missing the Ultimate feature set. The A1000 Mobile connects via PCIe 4.0 x8, while the M40 uses PCIe 3.0 x16. Physically, the A1000 Mobile is an integrated graphics processor (IGP) with no power connectors and no display outputs (portable device dependent), while the M40 is a dual-slot card measuring 267 mm (10.5 inches) with an 8-pin EPS power connector and a 600 W suggested PSU, and it has no display outputs either.

# FAQ

Q: Which GPU has higher raw FP32 compute?

A: The Tesla M40 24 GB leads with 6.832 TFLOPS, compared to the RTX A1000 Mobile's 4.669 TFLOPS. This is despite the M40 being based on the older Maxwell 2.0 architecture.

Q: How much memory does each card offer, and what is the bandwidth?

A: The RTX A1000 Mobile has 4 GB of GDDR6 on a 128-bit bus with 176.0 GB/s bandwidth. The Tesla M40 24 GB has 24 GB of GDDR5 on a 384-bit bus with 288.4 GB/s bandwidth.

Q: Which GPU supports ray tracing and tensor cores?

A: Only the RTX A1000 Mobile includes them — 16 ray tracing cores and 64 tensor cores. The Tesla M40 24 GB has neither, as Maxwell 2.0 predates those features.

Q: What are the power requirements for each card?

A: The RTX A1000 Mobile has a 60 W TDP and requires no power connectors. The Tesla M40 24 GB has a 250 W TDP, requires an 8-pin EPS connector, and needs a 600 W suggested PSU.

Q: How do the two compare in Vulkan performance?

A: They are nearly identical. The RTX A1000 Mobile scores 46,782 in Geekbench Vulkan, just 1.8% ahead of the Tesla M40 24 GB's 45,975.

Q: Which card has the higher average benchmark score overall?

A: The RTX A1000 Mobile averages 47,743, which is 14.5% higher than the Tesla M40 24 GB's 41,707. The A1000 Mobile also ranks at the 85th percentile versus the M40's 83rd.

# Specification Differences

| Specification | NVIDIA RTX A1000 Mobile | NVIDIA Tesla M40 24 GB |

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

| Architecture | Ampere | Maxwell 2.0 |

| Process Node | 8 nm (Samsung) | 28 nm (TSMC) |

| Transistors | 8,700 million | 8,000 million |

| Die Size | 200 mm² | 601 mm² |

| Transistor Density | 43.5M / mm² | 13.3M / mm² |

| Base Clock | 630 MHz | 948 MHz |

| Boost Clock | 1140 MHz | 1112 MHz |

| Memory Clock | 1375 MHz (11 Gbps effective) | 1502 MHz (6 Gbps effective) |

| Memory Size | 4 GB | 24 GB |

| Memory Type | GDDR6 | GDDR5 |

| Memory Bus Width | 128 bit | 384 bit |

| Memory Bandwidth | 176.0 GB/s | 288.4 GB/s |

| Shading Units | 2048 | 3072 |

| TMUs | 64 | 192 |

| ROPs | 32 | 96 |

| Ray Tracing Cores | 16 | None |

| Tensor Cores | 64 | None |

| Pixel Rate | 36.48 GPixel/s | 106.8 GPixel/s |

| Texture Rate | 72.96 GTexel/s | 213.5 GTexel/s |

| FP32 Performance | 4.669 TFLOPS | 6.832 TFLOPS |

| FP16 Performance | 4.669 TFLOPS (1:1) | None |

| TDP | 60 W | 250 W |

| Slot Width | IGP | Dual-slot |

| Power Connectors | None | 8-pin EPS |

| Suggested PSU | None | 600 W |

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

| Display Outputs | Portable Device Dependent | No outputs |

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

| Release Date | 2022-03-29 | 2015-11-09 |

| Predecessor | Quadro Turing-M | Tesla Kepler |

| Successor | Ada-MW | Tesla Pascal |

| Length | Not specified | 267 mm (10.5 inches) |

# Head-to-Head Benchmarks

The Geekbench OpenCL test delivers the most dramatic separation. The RTX A1000 Mobile scores 48,703, and the Tesla M40 24 GB scores 37,439. The 30.1% delta is the largest across any metric in this comparison. This result aligns with the A1000 Mobile's average score of 47,743, which is 14.5% above the M40's 41,707 average. The OpenCL result suggests that the A1000 Mobile's newer Ampere architecture, with its dedicated tensor cores and ray tracing hardware, translates into substantially better compute throughput in this API — despite the M40's higher raw FP32 rating.

The Geekbench Vulkan test narrows the gap considerably. The A1000 Mobile scores 46,782, while the M40 scores 45,975 — a 1.8% difference. This near-parity in Vulkan is notable given the architectural disparity. The M40's 3,072 shading units and 192 texture mapping units likely contribute to its competitiveness in this workload, partially offsetting the lack of modern features. The A1000 Mobile still wins, but the margin is small enough to suggest that Vulkan performance is not a differentiator between these two cards.

Looking at the broader benchmark landscape, the A1000 Mobile's nearest rivals include the AMD Radeon RX 6800 XT (48,477, just 1.5% higher) and the AMD Radeon RX 6550M (46,702, 2.2% lower). The Tesla M40 24 GB's nearest rival list includes another Tesla M40 variant (41,897, 0.5% higher) and the GeForce RTX 3080 Ti (41,187, 1.3% lower). These figures contextualize the head-to-head results: the A1000 Mobile competes with mid-range desktop and mobile GPUs, while the M40 sits among older or lower-tier cards. The M40's 83rd percentile ranking is respectable, but the A1000 Mobile's 85th percentile, combined with a higher average score, places it in a better overall position.

# The Verdict

The data points to the RTX A1000 Mobile as the superior overall performer. It wins both head-to-head benchmarks, holds a higher average score (47,743 versus 41,707), and ranks higher in the global percentile distribution (85 versus 83). The 30.1% OpenCL advantage is substantial, and even the narrow 1.8% Vulkan win confirms its edge across APIs. For users prioritizing compute performance in OpenCL workloads, the A1000 Mobile is the clear pick.

The Tesla M40 24 GB, however, retains one decisive advantage: memory. Its 24 GB capacity is six times larger than the A1000 Mobile's 4 GB, and its 288.4 GB/s bandwidth exceeds the A1000 Mobile's 176.0 GB/s by 64%. For workloads that require loading large datasets into VRAM — such as certain scientific computing, rendering, or inference tasks — the M40's capacity may be more important than raw compute speed. Its higher FP32 throughput (6.832 TFLOPS versus 4.669 TFLOPS) and faster pixel/texture rates also make it attractive for specific fill-rate-bound scenarios.

The choice depends on the workload profile. Select the RTX A1000 Mobile for modern API support, ray tracing, tensor cores, and overall compute efficiency in OpenCL and Vulkan. Select the Tesla M40 24 GB when memory capacity is the binding constraint and the workload can tolerate its older Maxwell 2.0 feature set and higher power draw. The M40's 250 W TDP and 600 W suggested PSU requirement also factor into deployment decisions, whereas the A1000 Mobile's 60 W TDP and IGP form factor enable integration into portable systems. Both cards are end-of-life, but the A1000 Mobile's 2022 release date makes it the more contemporary choice for new designs.