AMD Radeon R9 M380 vs NVIDIA Tesla M4 Comparison

# NVIDIA Tesla M4 vs AMD Radeon R9 M380

The NVIDIA Tesla M4 and AMD Radeon R9 M380 are two end-of-life GPUs from 2015, but they serve fundamentally different design philosophies. The Tesla M4 is a compute-focused accelerator with no display outputs, while the R9 M380 is a mobile graphics solution. The single head-to-head benchmark available shows the Tesla M4 delivering a decisive 34.8% higher OpenCL score (16932 vs 12565), placing it in the 60th percentile of all GPUs compared to the R9 M380's 58th percentile. However, the R9 M380 counters with a strong Metal benchmark score of 18476, suggesting its performance profile varies significantly by API and workload.

The Verdict

The data presents a clear performance hierarchy in compute workloads: the NVIDIA Tesla M4 wins the only direct head-to-head benchmark, scoring 16932 in Geekbench OpenCL against the AMD Radeon R9 M380's 12565 — a 34.8% advantage. This aligns with the Tesla M4's positioning as a datacenter-oriented compute card; its 60th percentile ranking versus 58th for the R9 M380 reflects a modest but real overall performance edge.

For users prioritizing raw OpenCL compute, the Tesla M4 is the data-backed choice. Its FP32 throughput of 2.195 TFLOPS versus 1.536 TFLOPS for the R9 M380, combined with higher pixel and texture rates, makes it the stronger compute engine on paper and in practice. The R9 M380, however, shows a different story in Metal benchmarks — its 18476 score far exceeds the Tesla M4's OpenCL result, though no direct Metal comparison exists for the NVIDIA card in the data.

The R9 M380's lower average benchmark score of 15521 (averaging its two results) still trails the Tesla M4's 16932 average. The R9 M380 sits within 1.5% of the NVIDIA GeForce RTX 2060 (15290) and 1.6% of the GTX 580 (15283), while the Tesla M4 is within 0.8% of the NVIDIA T400 4 GB (16792) and 0.9% of the AMD Radeon RX 7600 XT (17083). These proximity relationships suggest both cards occupy similar performance tiers despite their architectural differences.

Architecture Differences

The two GPUs come from competing architectural lineages. The Tesla M4 uses NVIDIA's Maxwell 2.0 architecture on the GM206 chip, while the R9 M380 employs AMD's GCN 2.0 architecture on the Strato chip. Both are fabricated on the same 28 nm process at TSMC, but the similarities end there.

Transistor counts differ substantially: the Tesla M4 packs 2,940 million transistors on a 228 mm² die, yielding a density of 12.9M per mm². The R9 M380 contains 2,080 million transistors on a smaller 160 mm² die, with a nearly identical density of 13.0M per mm². This means the Tesla M4 uses roughly 41% more silicon area and 41% more transistors to achieve its performance advantage.

The compute configurations diverge significantly. The Tesla M4 features 1024 shading units, 64 texture mapping units, and 32 render output units. The R9 M380 counters with 768 shading units, 48 TMUs, and only 16 ROPs — exactly half the ROP count of the Tesla M4. This ROP disparity directly explains the Tesla M4's 34.30 GPixel/s pixel rate versus the R9 M380's 16.00 GPixel/s, a 114% advantage in pixel throughput.

API support shows generational differences as well. Both support DirectX 12 and OpenGL 4.6, but the Tesla M4 supports DirectX 12_1 while the R9 M380 only reaches 12_0. Vulkan support also differs: the Tesla M4 supports Vulkan 1.4, whereas the R9 M380 is limited to Vulkan 1.2.170.

Head-to-Head Benchmarks

The sole direct comparison in the data is the Geekbench OpenCL test, and it heavily favors the NVIDIA Tesla M4. The Tesla M4 scores 16932 against the R9 M380's 12565, producing a 34.8% delta in NVIDIA's favor. This is a substantial margin — well beyond the noise level suggested by the nearest-rival comparisons.

Contextualizing this result against each card's rivals makes the gap more meaningful. The Tesla M4's 16932 places it just 0.5% below the AMD Radeon HD 7970M (17019) and 0.6% below the NVIDIA GeForce GTX 690 (17037). Meanwhile, the R9 M380's 12565 OpenCL score is significantly lower than its own average of 15521, dragged down by the Metal result being much higher. This suggests the R9 M380's OpenCL drivers or architecture are less optimized for this workload.

The R9 M380's Metal score of 18476 shows the hardware is capable of much higher throughput when the software stack aligns. Had this benchmark been run on the Tesla M4 (which lacks Metal support in the data), the comparison might look very different. The 34.8% OpenCL win for the Tesla M4 therefore represents a floor for its advantage in compute tasks, not a ceiling.

Specification Differences

The clock speeds set the stage for their performance divergence. The Tesla M4 runs at 872 MHz base and boosts to 1072 MHz, while the R9 M380 operates at 900 MHz base and 1000 MHz boost. The R9 M380 has a higher base clock by 28 MHz, but the Tesla M4's boost clock is 72 MHz higher.

Memory configurations are similar but not identical. Both use 4 GB of GDDR5 on a 128-bit bus, yet the R9 M380 achieves higher memory bandwidth: 96.00 GB/s versus 88.00 GB/s for the Tesla M4. The R9 M380's memory runs at 1500 MHz (6 Gbps effective) compared to the Tesla M4's 1375 MHz (5.5 Gbps effective).

The compute throughput differences are stark. The Tesla M4 delivers 2.195 TFLOPS of FP32 performance, 68.61 GTexel/s of texture fill rate, and 34.30 GPixel/s of pixel throughput. The R9 M380 manages only 1.536 TFLOPS, 48.00 GTexel/s, and 16.00 GPixel/s respectively. The Tesla M4 leads by 43% in FP32, 43% in texture rate, and 114% in pixel rate.

Power and physical specifications also differ. The Tesla M4 has a 50 W TDP and requires a 250 W suggested PSU, while the R9 M380's TDP and PSU recommendation are not listed. The Tesla M4 is single-slot with no display outputs, reflecting its server/compute orientation, while the R9 M380's slot width and display outputs are unspecified. Both use PCIe 3.0 x16 interfaces.

Release timing shows a six-month gap: the R9 M380 appeared on May 4, 2015, while the Tesla M4 followed on November 9, 2015. Their generational lineages also differ — the Tesla M4 succeeds Tesla Kepler and precedes Tesla Pascal, while the R9 M380 succeeds the Solar System generation and precedes Polaris Mobile.

FAQ

Q: Which GPU is faster in OpenCL compute?

A: The NVIDIA Tesla M4 wins decisively, scoring 16932 versus the AMD Radeon R9 M380's 12565 in Geekbench OpenCL — a 34.8% advantage.

Q: Does the R9 M380 have any performance advantage?

A: Yes, in Metal benchmarks the R9 M380 scores 18476, which is higher than the Tesla M4's OpenCL score of 16932, though no direct Metal comparison exists for the Tesla M4.

Q: How do these cards compare to modern GPUs?

A: The Tesla M4 sits within 0.9% of the AMD Radeon RX 7600 XT (17083) and 0.8% of the NVIDIA T400 4 GB (16792). The R9 M380 is within 1.5% of the NVIDIA GeForce RTX 2060 (15290) and 1.6% of the GTX 580 (15283).

Q: What explains the Tesla M4's pixel rate advantage?

A: The Tesla M4 has 32 ROPs compared to 16 on the R9 M380, resulting in a 34.30 GPixel/s pixel rate versus 16.00 GPixel/s — a 114% difference.

Q: Are these cards from the same manufacturing process?

A: Both use TSMC's 28 nm process, but the Tesla M4 has 2,940 million transistors on a 228 mm² die, while the R9 M380 has 2,080 million transistors on a 160 mm² die.

Q: Which card has higher memory bandwidth?

A: The R9 M380 achieves 96.00 GB/s versus 88.00 GB/s for the Tesla M4, despite both using 4 GB GDDR5 on 128-bit buses. The R9 M380's memory runs at 1500 MHz (6 Gbps effective) versus 1375 MHz (5.5 Gbps effective).

Where Each One Wins

NVIDIA Tesla M4 wins in every direct compute comparison. The 34.8% OpenCL lead over the R9 M380 is the headline result, supported by a 43% advantage in FP32 throughput (2.195 vs 1.536 TFLOPS) and texture fill rate (68.61 vs 48.00 GTexel/s). The pixel rate advantage is even more pronounced at 114% (34.30 vs 16.00 GPixel/s), driven by double the ROP count. The Tesla M4 also supports newer API versions — DirectX 12_1 versus 12_0, and Vulkan 1.4 versus 1.2.170 — making it the more future-proof choice for compute workloads. Its 50 W TDP and single-slot design with no display outputs positions it clearly for server installations where compute density matters.

AMD Radeon R9 M380 wins in memory bandwidth, delivering 96.00 GB/s versus 88.00 GB/s — a 9% advantage that could help in memory-bound scenarios. Its Metal score of 18476 suggests superior performance in Apple-centric environments, potentially outperforming the Tesla M4's OpenCL result by 9.1% if that comparison were valid. The R9 M380 also has a higher base clock (900 vs 872 MHz), which may benefit lightly-threaded workloads that don't trigger boost behavior. Its unspecified TDP and mobile-oriented generation (Gem System) suggest it was designed for power-constrained laptops rather than datacenter racks.

For users choosing between these end-of-life parts, the data overwhelmingly favors the Tesla M4 for any OpenCL-based compute task. The R9 M380 only makes sense in contexts where Metal API support is required or where its higher memory bandwidth proves critical — scenarios that the available benchmark data cannot directly confirm.