AMD FirePro M6100 vs NVIDIA Tesla K10 Comparison

The NVIDIA Tesla K10 and AMD FirePro M6100 are both end-of-life professional GPUs, but they serve entirely different purposes. The benchmark data shows a single decisive win for the Tesla K10 in the Geekbench OpenCL test, yet the specifications reveal why these cards were never direct competitors. The Tesla K10 is a dual-slot, 225 W desktop compute card from 2012, while the FirePro M6100 is a power-efficient MXM module from 2014 designed for mobile workstations. Their performance gap is real but narrow, and the choice between them hinges entirely on form factor and compute workload rather than raw speed.

Where Each One Wins

The NVIDIA Tesla K10 wins the only head-to-head benchmark available, but the victory is modest. In Geekbench OpenCL, the Tesla K10 scores 14029 against the FirePro M6100’s 13354, a 5.1% advantage. This makes the Tesla K10 the clear pick for any compute task that leans on OpenCL performance, especially in a stationary rack or desktop chassis where its dual-slot size and 225 W power draw are acceptable.

The AMD FirePro M6100, despite losing the benchmark, wins in the portability and integration category. As an MXM-B (3.0) module with no power connectors and no display outputs of its own, it is designed to be embedded into a laptop or compact workstation where the Tesla K10 physically cannot fit. The Tesla K10 is 272 mm long (10.7 inches) and requires a 550 W suggested power supply, whereas the FirePro M6100 slots into a proprietary mobile socket. For users needing GPU compute on the move, the FirePro M6100 is the only viable option, regardless of its lower score.

Additionally, the FirePro M6100 wins on API feature level. It supports DirectX 12 (12_0), while the Tesla K10 only reaches DirectX 12 (11_0). In any workload that explicitly requires the higher DirectX feature level, the FirePro M6100 is the functional winner even though it trails in raw OpenCL throughput.

Architecture Differences

The two GPUs come from different architectural generations and design philosophies. The Tesla K10 is built on NVIDIA’s Kepler architecture, using the GK104 chip fabricated on a 28 nm process at TSMC. It packs 3,540 million transistors into a 294 mm² die, yielding a transistor density of 12.0M / mm². The FirePro M6100 uses AMD’s GCN 2.0 architecture with the Emerald chip, also on TSMC’s 28 nm node, but with 2,080 million transistors on a much smaller 160 mm² die, achieving a higher density of 13.0M / mm².

The compute resources differ substantially. The Tesla K10 fields 1,536 shading units, 128 texture mapping units (TMUs), and 32 raster operation pipelines (ROPs). The FirePro M6100 counters with 896 shading units, 56 TMUs, and 16 ROPs. This gives the Tesla K10 a theoretical peak FP32 throughput of 2.289 TFLOPS, while the FirePro M6100 reaches 1.971 TFLOPS. The Tesla K10’s lead is consistent across the board: higher pixel rate (23.84 GPixel/s vs 17.60 GPixel/s) and higher texture rate (95.36 GTexel/s vs 61.60 GTexel/s).

Memory subsystems also diverge sharply. The Tesla K10 has 4 GB of GDDR5 on a 256-bit bus, delivering 160.0 GB/s of bandwidth. The FirePro M6100 has 2 GB of GDDR5 on a 128-bit bus, capped at 96.00 GB/s. However, the FirePro M6100 runs its memory at 1500 MHz (6 Gbps effective), which is faster than the Tesla K10’s 1250 MHz (5 Gbps effective), though the narrower bus negates that clock advantage. The Tesla K10’s larger memory pool and wider bus make it the better choice for large datasets that exceed 2 GB.

Both GPUs support OpenGL 4.6 and Vulkan, but the Vulkan versions differ slightly: the Tesla K10 supports Vulkan 1.2.175, while the FirePro M6100 supports 1.2.170. Neither has dedicated ray tracing or tensor cores, as both predate those features.

Head-to-Head Benchmarks

The only benchmark data available is the Geekbench OpenCL test, and it favors the Tesla K10. The Tesla K10 scores 14029, while the FirePro M6100 scores 13354. The delta is 5.1% in favor of the NVIDIA card. This margin is small but consistent with the theoretical peak FP32 difference, where the Tesla K10 leads by roughly 16% (2.289 TFLOPS vs 1.971 TFLOPS). The fact that the real-world OpenCL gap is smaller than the theoretical peak suggests the FirePro M6100 extracts a higher percentage of its theoretical compute capability in this workload.

Contextualizing the scores against their respective nearest rivals adds perspective. The Tesla K10’s 14029 score sits just 0.9% below the NVIDIA GeForce GTX 680 (14150) and 1.1% above the AMD Radeon RX 570X (13871). It also leads the NVIDIA RTX A2000 Mobile (13821) by 1.5% and the AMD Radeon 660M (13812) by 1.6%. This places the Tesla K10 in the 55th percentile of all GPUs.

The FirePro M6100’s 13354 score is essentially tied with the AMD Radeon RX 5500M (13356, 0% delta) and the AMD Radeon Pro 555X (13321, 0.3% delta). It trails the AMD Radeon HD 8950M (13376) by 0.2% and the AMD Radeon Pro 555 (13407) by 0.4%. Its 54th percentile ranking is just one point below the Tesla K10, confirming that the two cards are in the same performance tier despite their architectural differences.

The decisive factor in the head-to-head is not the 5.1% score difference but the physical and power envelope. The Tesla K10’s 5.1% lead in OpenCL comes at the cost of requiring a desktop slot, external power connectors (1x 6-pin + 1x 8-pin), and a 550 W power supply. The FirePro M6100’s lower score is delivered in an MXM module with no external power connectors, making it the only choice for portable systems.

FAQ

Q: Which GPU is faster in OpenCL compute?

A: The NVIDIA Tesla K10 is faster, scoring 14029 versus the AMD FirePro M6100’s 13354 in Geekbench OpenCL, a 5.1% advantage.

Q: Can the AMD FirePro M6100 be used in a desktop PC?

A: The FirePro M6100 is an MXM-B (3.0) module with no display outputs and no power connectors. It is designed for portable devices and requires a compatible MXM slot, not a standard PCIe desktop slot.

Q: Does the Tesla K10 support the same DirectX feature level as the FirePro M6100?

A: No. The Tesla K10 supports DirectX 12 (11_0), while the FirePro M6100 supports DirectX 12 (12_0). The FirePro M6100 has a higher feature level.

Q: How much memory does each card have?

A: The Tesla K10 has 4 GB of GDDR5 on a 256-bit bus (160.0 GB/s bandwidth). The FirePro M6100 has 2 GB of GDDR5 on a 128-bit bus (96.00 GB/s bandwidth).

Q: What is the transistor count difference between the two?

A: The Tesla K10 has 3,540 million transistors on a 294 mm² die. The FirePro M6100 has 2,080 million transistors on a 160 mm² die.

Q: Which card has a higher pixel fill rate?

A: The Tesla K10 has a pixel rate of 23.84 GPixel/s, compared to the FirePro M6100’s 17.60 GPixel/s.

The Verdict

The data supports a clear split decision. For stationary compute workloads where power and space are unconstrained, the NVIDIA Tesla K10 is the superior choice. It wins the only benchmark, offers double the memory (4 GB vs 2 GB), has more than double the memory bandwidth (160.0 GB/s vs 96.00 GB/s), and delivers higher theoretical throughput in every category: FP32 (2.289 TFLOPS vs 1.971 TFLOPS), pixel rate, and texture rate. Its 55th percentile ranking versus the FirePro M6100’s 54th percentile reflects this slight overall edge.

For mobile or space-constrained professional systems, the AMD FirePro M6100 is the only realistic option. Its MXM module form factor, lack of external power connectors, and portable-device-dependent display outputs make it the sole choice for laptops. The FirePro M6100 also holds the DirectX 12 (12_0) feature level advantage, which the Tesla K10 cannot match. Its 13354 OpenCL score is only 5.1% behind the Tesla K10, a negligible penalty for the portability gains.

The Tesla K10’s launch MSRP was 5,099 USD, reflecting its enterprise compute positioning. The FirePro M6100 has no listed launch MSRP. Neither card is a current-generation product, and both are end-of-life. Buyers choosing between them today should let the chassis dictate the decision: if the system accepts a dual-slot, 225 W PCIe card, the Tesla K10’s extra compute headroom wins. If the system requires an MXM module, the FirePro M6100 is the only contender.

Specification Differences

| Specification | NVIDIA Tesla K10 | AMD FirePro M6100 |

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

| Architecture | Kepler | GCN 2.0 |

| Chip | GK104 | Emerald |

| Process Node | 28 nm | 28 nm |

| Transistors | 3,540 million | 2,080 million |

| Die Size | 294 mm² | 160 mm² |

| Transistor Density | 12.0M / mm² | 13.0M / mm² |

| Memory Clock | 1250 MHz (5 Gbps effective) | 1500 MHz (6 Gbps effective) |

| Memory Size | 4 GB | 2 GB |

| Memory Bus Width | 256 bit | 128 bit |

| Memory Bandwidth | 160.0 GB/s | 96.00 GB/s |

| Shading Units | 1536 | 896 |

| TMUs | 128 | 56 |

| ROPs | 32 | 16 |

| Pixel Rate | 23.84 GPixel/s | 17.60 GPixel/s |

| Texture Rate | 95.36 GTexel/s | 61.60 GTexel/s |

| FP32 | 2.289 TFLOPS | 1.971 TFLOPS |

| TDP | 225 W | Not specified |

| Slot Width | Dual-slot | MXM Module |

| Power Connectors | 1x 6-pin + 1x 8-pin | None |

| Suggested PSU | 550 W | Not specified |

| Bus Interface | PCIe 3.0 x16 | MXM-B (3.0) |

| Display Outputs | No outputs | Portable Device Dependent |

| DirectX | 12 (11_0) | 12 (12_0) |

| Vulkan | 1.2.175 | 1.2.170 |

| Release Date | 2012-04-30 | 2014-05-26 |

| Geekbench OpenCL | 14029 | 13354 |