AMD FirePro D300 vs NVIDIA Tesla M4 Comparison

# AMD FirePro D300 vs NVIDIA Tesla M4

The AMD FirePro D300 and NVIDIA Tesla M4 serve different segments of the data center market, and the benchmark data reflects that separation. In the only recorded head-to-head benchmark, the FirePro D300 leads by 15.3% in Geekbench OpenCL, scoring 19,515 against the Tesla M4's 16,932. The FirePro D300 also holds a higher overall percentile rank (64th vs 60th among all GPUs) and a higher average benchmark score (19,637 vs 16,932). However, the Tesla M4 counters with a dramatically lower power draw of 50 W versus 150 W, and double the memory capacity at 4 GB versus 2 GB. These are not interchangeable cards; they are optimized for different workloads, and the data makes those priorities clear.

Where Each One Wins

The AMD FirePro D300 wins on raw compute performance. Its Geekbench OpenCL score of 19,515 is 15.3% higher than the Tesla M4's 16,932. This advantage extends to its average benchmark score of 19,637, which places it 0.2% ahead of the NVIDIA Quadro K5200 and 1.2% ahead of the AMD Radeon RX 7900 XTX, according to nearest-rival data. The FirePro D300 also achieves a higher pixel rate of 27.20 GPixel/s and a nearly identical texture rate of 68.00 GTexel/s versus the Tesla M4's 68.61 GTexel/s, but it is the FP32 throughput that matters most for compute tasks. The FirePro D300 delivers 2.176 TFLOPS, close to the Tesla M4's 2.195 TFLOPS, yet the OpenCL result shows a clear performance gap in favor of the AMD card.

The NVIDIA Tesla M4 wins on efficiency and capacity. Its 50 W TDP is one-third of the FirePro D300's 150 W, and its suggested PSU of 250 W is correspondingly lower than the 450 W suggested for the AMD card. The Tesla M4 packs 4 GB of GDDR5 memory, double the FirePro D300's 2 GB, although the AMD card compensates with a wider 256-bit bus and 162.6 GB/s of bandwidth versus the Tesla M4's 128-bit bus and 88.00 GB/s. The Tesla M4 also boosts to 1,072 MHz, higher than the FirePro D300's memory clock of 1,270 MHz (5.1 Gbps effective) versus the Tesla M4's 1,375 MHz (5.5 Gbps effective), but the AMD card's wider bus delivers more total bandwidth. For workloads that prioritize memory capacity or minimal power consumption, the Tesla M4 is the clear choice.

FAQ

Q: Which card has a higher OpenCL benchmark score?

A: The AMD FirePro D300 scores 19,515 in Geekbench OpenCL, which is 15.3% higher than the NVIDIA Tesla M4's 16,932.

Q: How do the two cards compare in power consumption?

A: The NVIDIA Tesla M4 draws 50 W, while the AMD FirePro D300 draws 150 W. The Tesla M4's suggested PSU is 250 W, compared to 450 W for the FirePro D300.

Q: Which card offers more memory capacity?

A: The NVIDIA Tesla M4 has 4 GB of GDDR5 memory, double the AMD FirePro D300's 2 GB. However, the FirePro D300 has a wider 256-bit memory bus and higher bandwidth at 162.6 GB/s versus 88.00 GB/s.

Q: What is the average benchmark score for each card?

A: The AMD FirePro D300 has an average benchmark score of 19,637 across its recorded tests, while the NVIDIA Tesla M4 has an average score of 16,932 from its single recorded test.

Q: Does the Tesla M4 support display outputs?

A: No, the NVIDIA Tesla M4 has no display outputs. The AMD FirePro D300 has 4x DisplayPort 1.2 outputs.

Q: Which card has a higher percentile ranking among all GPUs?

A: The AMD FirePro D300 ranks in the 64th percentile, while the NVIDIA Tesla M4 ranks in the 60th percentile.

Head-to-Head Benchmarks

The only directly comparable benchmark in the database is Geekbench OpenCL, and the AMD FirePro D300 wins decisively. The FirePro D300 scores 19,515 against the Tesla M4's 16,932, a delta of 15.3%. This is a substantial margin for a compute-oriented workload, indicating that the FirePro D300's architecture and memory subsystem deliver better OpenCL performance despite the Tesla M4 having a higher boost clock of 1,072 MHz and slightly higher FP32 output of 2.195 TFLOPS versus 2.176 TFLOPS.

The FirePro D300's advantage is likely tied to its memory configuration. With a 256-bit bus and 162.6 GB/s of bandwidth, the AMD card can feed its 1,280 shading units more efficiently than the Tesla M4's 128-bit bus and 88.00 GB/s can feed its 1,024 shading units. The FirePro D300 also has 80 texture units versus 64 on the Tesla M4, and while the texture rates are nearly identical (68.00 GTexel/s vs 68.61 GTexel/s), the AMD card achieves that throughput with fewer clock cycles per texture operation. The pixel rates differ more significantly: 27.20 GPixel/s for the FirePro D300 versus 34.30 GPixel/s for the Tesla M4, meaning the NVIDIA card is faster at rasterization-heavy tasks, but OpenCL compute clearly favors the AMD architecture.

In terms of nearest rivals, the FirePro D300's average score of 19,637 sits just 0.2% below the NVIDIA Quadro K5200 and 1.2% above the AMD Radeon RX 7900 XTX, showing it is competitive with much newer hardware. The Tesla M4's average score of 16,932 is 0.5% below the AMD Radeon HD 7970M and 0.8% above the NVIDIA T400 4 GB, placing it in a lower performance tier overall.

Specification Differences

The two cards differ across nearly every major specification category. The AMD FirePro D300 uses 2 GB of GDDR5 memory on a 256-bit bus, delivering 162.6 GB/s of bandwidth. The NVIDIA Tesla M4 uses 4 GB of GDDR5 memory on a 128-bit bus, delivering 88.00 GB/s. The FirePro D300 has 1,280 shading units, 80 TMUs, and 32 ROPs, while the Tesla M4 has 1,024 shading units, 64 TMUs, and 32 ROPs. Clock speeds differ as well: the Tesla M4 has a base clock of 872 MHz and a boost clock of 1,072 MHz, while the FirePro D300 has no listed base or boost clock, only a memory clock of 1,270 MHz (5.1 Gbps effective) versus the Tesla M4's 1,375 MHz (5.5 Gbps effective).

Power requirements are starkly different. The FirePro D300 has a TDP of 150 W and a suggested PSU of 450 W, while the Tesla M4 has a TDP of 50 W and a suggested PSU of 250 W. Both are single-slot cards, but the FirePro D300 has a listed length of 242 mm (9.5 inches), while the Tesla M4 has no dimensions listed. The FirePro D300 features 4x DisplayPort 1.2 outputs, whereas the Tesla M4 has no display outputs at all. Both use PCIe 3.0 x16 interfaces. The FirePro D300 was released on January 17, 2014, while the Tesla M4 came later on November 9, 2015.

Architecture Differences

The AMD FirePro D300 is built on the Pitcairn chip using GCN 1.0 architecture, fabricated on a 28 nm process at TSMC. It contains 2,800 million transistors on a 212 mm² die, resulting in a transistor density of 13.2M per mm². The NVIDIA Tesla M4 uses the GM206 chip with Maxwell 2.0 architecture, also on a 28 nm TSMC process, but packs 2,940 million transistors on a slightly larger 228 mm² die, giving a density of 12.9M per mm². The Tesla M4's higher transistor count and die size suggest a more complex design, yet the FirePro D300 achieves higher performance in the recorded benchmark.

The FirePro D300 belongs to the FirePro Data Center (Dx00) generation and supports DirectX 12 (11_1), OpenGL 4.6, and Vulkan 1.2.170. The Tesla M4 is part of the Tesla Maxwell (Mxx) generation and supports DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.4. The newer Vulkan version on the Tesla M4 reflects its later release date. Neither card has RT cores or tensor cores, and neither lists FP16 support. The FirePro D300's predecessor is FirePro Terascale and its successor is Radeon Instinct, while the Tesla M4's predecessor is Tesla Kepler and its successor is Tesla Pascal.

The architectural differences explain the performance split. GCN 1.0 was designed with compute throughput in mind, and the FirePro D300's wider memory bus and higher shading unit count give it an edge in OpenCL workloads. Maxwell 2.0 focuses on efficiency, which shows in the Tesla M4's 50 W TDP and higher clock speeds, but that efficiency comes at the cost of raw compute performance in this comparison.

The Verdict

The data points to a clear split. Choose the AMD FirePro D300 if compute performance is the priority. It leads the Tesla M4 by 15.3% in Geekbench OpenCL, holds a higher average benchmark score of 19,637 versus 16,932, and ranks in the 64th percentile overall versus 60th. Its 162.6 GB/s of memory bandwidth and 1,280 shading units make it better suited for OpenCL-heavy tasks, and its 4x DisplayPort outputs allow for display connectivity where needed.

Choose the NVIDIA Tesla M4 if power efficiency or memory capacity matters more. Its 50 W TDP is a fraction of the FirePro D300's 150 W, making it far easier to cool and power in dense server environments. Its 4 GB of memory doubles the FirePro D300's 2 GB, which is valuable for models or datasets that exceed 2 GB. The Tesla M4 also has a higher boost clock of 1,072 MHz and slightly higher FP32 output at 2.195 TFLOPS, though the benchmark results show this does not translate to OpenCL superiority.

For most compute workloads, the FirePro D300 is the stronger performer. For power-constrained deployments or memory-hungry tasks, the Tesla M4 is the logical pick. The two cards do not compete for the same socket; they serve different priorities, and the recorded data supports each card's respective role.