NVIDIA Quadro M6000 24 GB vs NVIDIA Tesla M40 Comparison

# Head-to-Head Benchmarks

The data presents a clear picture: the NVIDIA Quadro M6000 24 GB outperforms the NVIDIA Tesla M40 in both available benchmark tests. In Geekbench OpenCL, the Quadro scores 40,098 against the Tesla’s 39,192, a 2.3% advantage. The gap widens in Geekbench Vulkan, where the Quadro reaches 46,425 while the Tesla trails at 44,602 — a 4.1% lead for the Quadro. These deltas are modest in absolute terms, but they are consistent across both workloads, suggesting a genuine performance edge rather than a measurement anomaly.

The Quadro’s average benchmark score of 43,262 reinforces this narrative, sitting comfortably above the Tesla’s 41,897. When placed against their respective nearest rivals, the two cards occupy different competitive neighborhoods. The Quadro’s closest rival is the NVIDIA GeForce RTX 5050 Mobile with an average score of 43,268 — essentially a dead heat at a 0% delta. The Quadro also edges out the NVIDIA Quadro M6000 (non-24GB variant) by 0.1% and the NVIDIA GeForce RTX 4070 SUPER by 0.1%, while trailing the NVIDIA GeForce RTX 4090 Mobile by 0.9%. The Tesla M40, by contrast, sits 0.5% behind its own 24 GB sibling, but leads the NVIDIA GeForce RTX 3080 Ti by 1.7% and the AMD Radeon Pro 5300 by 2.5%. Notably, the AMD Radeon RX 7650 GRE outpaces the Tesla by 1.9%.

What’s striking is not the margin of victory — 2.3% and 4.1% are hardly landslides — but the consistency. Both cards share the same GM200 chip, the same Maxwell 2.0 architecture, the same 28 nm TSMC process, and the same 8,000 million transistors on a 601 mm² die. The differences in benchmark outcomes must therefore stem from clock speeds and memory configuration rather than fundamental architectural changes. The Quadro’s base clock runs at 988 MHz versus the Tesla’s 948 MHz, and its boost clock of 1114 MHz slightly exceeds the Tesla’s 1112 MHz. These small frequency advantages translate directly into the observed performance deltas.

The Vulkan gap deserves particular attention. A 4.1% difference in Vulkan versus 2.3% in OpenCL hints that the Quadro’s higher memory bandwidth — 317.4 GB/s against 288.4 GB/s — may play a larger role in certain workloads. The Quadro’s memory runs at 1653 MHz (6.6 Gbps effective) versus the Tesla’s 1502 MHz (6 Gbps effective). Both cards use GDDR5 across a 384-bit bus, but the Quadro’s faster memory clock yields that 29 GB/s bandwidth advantage. Vulkan workloads, which often stress memory subsystems more aggressively, would naturally amplify this difference.

# Where Each One Wins

The Quadro M6000 24 GB wins both head-to-head tests, so the use-case split is straightforward: the Quadro is the better performer in OpenCL and Vulkan compute scenarios. Its 24 GB memory capacity doubles the Tesla’s 12 GB, making it the obvious choice for datasets that exceed 12 GB. The Quadro also offers display outputs — 1x DVI and 4x DisplayPort 1.2 — while the Tesla M40 has none. This makes the Quadro suitable for workstation tasks that require visual output, whereas the Tesla is strictly a compute-oriented accelerator.

The Tesla M40, despite losing both benchmarks, still holds relevance in specific contexts. Its 41,897 average score places it in the 83rd percentile of all GPUs, identical to the Quadro’s percentile ranking. For compute tasks that don’t require display output and where 12 GB of memory suffices, the Tesla delivers nearly the same raw throughput at slightly lower clock speeds. The Tesla’s nearest rival data shows it performing competitively against much newer hardware — it leads the NVIDIA GeForce RTX 3080 Ti by 1.7% — which suggests it remains viable for certain workloads despite its age.

The wins break down cleanly: the Quadro wins on raw speed (both benchmarks), memory capacity (24 GB versus 12 GB), and connectivity (display outputs versus none). The Tesla’s only advantages are its earlier release date (November 2015 versus March 2016) and its different power connector (8-pin EPS versus 1x 8-pin). Neither of these constitutes a performance win, but they may factor into deployment decisions in existing infrastructure.

# Architecture Differences

Both cards are built on the same fundamental architecture: Maxwell 2.0, using the GM200 chip fabricated by TSMC on a 28 nm process. Both pack 8,000 million transistors into a 601 mm² die, yielding a transistor density of 13.3M per mm². The shading unit count is identical at 3,072, as are the texture mapping units (192) and render output units (96). Neither card features ray tracing cores or tensor cores — those would come with later architectures.

The differences emerge in clock speeds and memory. The Quadro’s base clock of 988 MHz is 40 MHz higher than the Tesla’s 948 MHz. The boost clocks are nearly identical — 1114 MHz versus 1112 MHz — but the Quadro still holds a slight edge. Memory clocks diverge more significantly: the Quadro runs at 1653 MHz (6.6 Gbps effective) versus the Tesla’s 1502 MHz (6 Gbps effective). Both use GDDR5 on a 384-bit bus, but the Quadro’s faster memory translates to 317.4 GB/s of bandwidth versus 288.4 GB/s.

Memory capacity is the most obvious architectural split: 24 GB on the Quadro versus 12 GB on the Tesla. This doubling of capacity, combined with the bandwidth advantage, gives the Quadro a substantial edge in memory-bound workloads. The pixel rates are nearly identical — 106.9 GPixel/s for the Quadro versus 106.8 GPixel/s for the Tesla — as are the texture rates (213.9 GTexel/s versus 213.5 GTexel/s). FP32 performance is also close: 6.844 TFLOPS for the Quadro versus 6.832 TFLOPS for the Tesla. Neither card supports FP16, a notable limitation for certain AI workloads.

Power characteristics are identical: both consume 250 W TDP and recommend a 600 W power supply. Both are dual-slot cards measuring 267 mm (10.5 inches) in length. The Quadro stands 111 mm (4.4 inches) tall, while the Tesla’s height is not specified. The power connectors differ — the Quadro uses 1x 8-pin while the Tesla uses 8-pin EPS — which may affect compatibility with existing power cabling. Both cards use PCIe 3.0 x16 interfaces and support DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.4.

# FAQ

Q: Which card is faster in the head-to-head benchmarks?

A: The NVIDIA Quadro M6000 24 GB wins both tests. It scores 40,098 versus 39,192 in Geekbench OpenCL (2.3% ahead) and 46,425 versus 44,602 in Geekbench Vulkan (4.1% ahead).

Q: Do the two cards share the same underlying chip?

A: Yes. Both use the GM200 chip with Maxwell 2.0 architecture, built on a 28 nm TSMC process with 8,000 million transistors on a 601 mm² die. They also have identical shading unit (3,072), TMU (192), and ROP (96) counts.

Q: How do their memory configurations differ?

A: The Quadro has 24 GB of GDDR5 on a 384-bit bus with 317.4 GB/s bandwidth. The Tesla has 12 GB of GDDR5 on the same bus width but with 288.4 GB/s bandwidth. The Quadro’s memory clock is 1653 MHz (6.6 Gbps effective) versus 1502 MHz (6 Gbps effective) on the Tesla.

Q: Can the Tesla M40 output video to a display?

A: No. The Tesla M40 has no display outputs, while the Quadro M6000 24 GB offers 1x DVI and 4x DisplayPort 1.2 connections.

Q: How does each card compare to its nearest rivals?

A: The Quadro’s average score of 43,262 is within 0.1% of the NVIDIA GeForce RTX 5050 Mobile (43,268) and the NVIDIA Quadro M6000 (43,301), and 0.1% ahead of the NVIDIA GeForce RTX 4070 SUPER (43,223). The Tesla’s average of 41,897 places it 1.7% ahead of the NVIDIA GeForce RTX 3080 Ti (41,187) and 2.5% ahead of the AMD Radeon Pro 5300 (40,870), but 1.9% behind the AMD Radeon RX 7650 GRE (42,723).

Q: What are the power and physical specifications?

A: Both cards consume 250 W TDP with a 600 W suggested power supply. Both are dual-slot, 267 mm (10.5 inches) long, and use PCIe 3.0 x16. The Quadro uses a 1x 8-pin power connector, while the Tesla uses an 8-pin EPS connector.

# Specification Differences

| Specification | NVIDIA Quadro M6000 24 GB | NVIDIA Tesla M40 |

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

| Base Clock | 988 MHz | 948 MHz |

| Boost Clock | 1114 MHz | 1112 MHz |

| Memory Clock | 1653 MHz (6.6 Gbps effective) | 1502 MHz (6 Gbps effective) |

| Memory Size | 24 GB | 12 GB |

| Memory Bandwidth | 317.4 GB/s | 288.4 GB/s |

| Pixel Rate | 106.9 GPixel/s | 106.8 GPixel/s |

| Texture Rate | 213.9 GTexel/s | 213.5 GTexel/s |

| FP32 Performance | 6.844 TFLOPS | 6.832 TFLOPS |

| Power Connector | 1x 8-pin | 8-pin EPS |

| Display Outputs | 1x DVI, 4x DisplayPort 1.2 | No outputs |

| Height | 111 mm (4.4 inches) | Not specified |

| Release Date | March 4, 2016 | November 9, 2015 |

| Generation | Quadro Maxwell (Mx000) | Tesla Maxwell (Mxx) |

| Launch MSRP | 4,999 USD | Not available |

# The Verdict

The data points to a straightforward conclusion: the NVIDIA Quadro M6000 24 GB is the superior card in every measurable performance category. It wins both head-to-head benchmarks, offers double the memory capacity, provides higher memory bandwidth, and includes display outputs for workstation flexibility. Its average benchmark score of 43,262 versus the Tesla’s 41,897 — a difference of roughly 3.3% — reflects the cumulative effect of higher clock speeds and faster memory.

The Quadro’s benchmark placement among its nearest rivals is telling. It sits within 0.1% of the NVIDIA GeForce RTX 5050 Mobile and the standard Quadro M6000, and only 0.9% behind the NVIDIA GeForce RTX 4090 Mobile. This suggests the 24 GB Quadro punches well above its generational weight, competing with much newer hardware. The Tesla, meanwhile, holds its own against the NVIDIA GeForce RTX 3080 Ti (1.7% ahead) but falls behind the AMD Radeon RX 7650 GRE by 1.9%.

For buyers choosing between these two, the decision hinges on workload requirements. If the task involves datasets larger than 12 GB, requires visual output, or demands maximum compute throughput, the Quadro M6000 24 GB is the clear pick. Its 24 GB memory capacity alone justifies the choice for large-scale visualization or machine learning workloads that exceed the Tesla’s memory ceiling. The display outputs also make it suitable for interactive workstation use, whereas the Tesla’s lack of outputs confines it to headless compute servers.

The Tesla M40, however, remains a viable option for compute-only deployments where 12 GB is sufficient and where the 8-pin EPS power connector matches existing infrastructure. Its 83rd percentile ranking among all GPUs matches the Quadro’s, and its performance against newer rivals — leading the RTX 3080 Ti by 1.7% — demonstrates that Maxwell 2.0 still has meaningful compute headroom. The earlier release date of November 2015 also means the Tesla may be available at lower cost in secondary markets, though pricing data is not available for this comparison.

The architectural similarities between the two cards — identical chip, identical transistor count, identical shading units — make the Quadro’s wins purely a function of clock speeds and memory configuration. The Quadro’s 40 MHz base clock advantage and 151 MHz memory clock advantage translate directly into the observed 2.3% and 4.1% benchmark deltas. For users who need every bit of performance, the Quadro delivers. For those who can tolerate slightly lower throughput in exchange for a compute-only form factor, the Tesla remains a competent choice. The data, however, is unambiguous: the Quadro M6000 24 GB wins on every benchmark where they are compared.