AMD Radeon R9 M380 vs NVIDIA Tesla M2090 Comparison

Head-to-Head Benchmarks

The benchmark data shows a narrow but decisive victory for the NVIDIA Tesla M2090 in the only directly comparable test. In the Geekbench OpenCL workload, the Tesla M2090 scores 13,075, while the AMD Radeon R9 M380 scores 12,565. That is a 3.9% deficit for the AMD part, meaning the NVIDIA compute card leads by roughly 4 percentage points in raw OpenCL performance. This is not a commanding margin, but it is consistent and measurable, and it gives the Tesla M2090 the sole win in the head-to-head comparison.

Looking beyond the direct comparison, the two cards sit in different performance tiers relative to the broader GPU landscape. The Radeon R9 M380 posts an average benchmark score of 15,521, which places it at the 58th percentile among all GPUs in the database. The Tesla M2090, by contrast, averages 13,075 and sits at the 53rd percentile. The AMD card is therefore the higher-ranked product overall, even though it loses the specific OpenCL test. Its average score is 18.7% higher than the Tesla's average, a gap driven by the Radeon's additional Metal benchmark result. The R9 M380 scores 18,476 in Geekbench Metal, a workload the Tesla M2090 cannot run, as it has no display outputs and no Metal support in the recorded data.

The nearest rivals further contextualize each card. The R9 M380's average score of 15,521 places it within 0.2% of the NVIDIA GeForce GTX 1080 Ti (15,548), 1% behind the AMD Radeon Pro W5500 (15,679), and 1.5% ahead of the NVIDIA GeForce RTX 2060 (15,290). These are tight margins, indicating the R9 M380 competes in the same performance band as much newer and more expensive desktop parts. The Tesla M2090, meanwhile, sits 0.7% above the GeForce GTX 1660 SUPER (12,986), 0.9% below the GeForce GTX 950 (13,189), 1% above the RTX 3050 Ti Mobile (12,940), and 1.1% above the AMD Radeon RX 580 (12,928). Its performance neighborhood is populated by mainstream and older-generation cards, reinforcing that the Tesla's raw compute output is modest by modern standards but still respectable for its era.

The single head-to-head result is the only direct evidence of relative performance, and it favors the Tesla M2090 by a small margin. However, the broader benchmark picture tells a different story: the Radeon R9 M380 has a higher average score, a higher percentile rank, and a second benchmark result that the Tesla cannot match. The OpenCL loss should not be dismissed, but it does not define the entire relationship between these two GPUs.

Architecture Differences

The two cards come from different architectural generations with fundamentally different design priorities. The AMD Radeon R9 M380 uses the Strato chip, built on GCN 2.0 architecture, and belongs to the Gem System (R9 M300) generation. It is manufactured on a 28 nm process at TSMC, with 2,080 million transistors packed into a 160 mm² die. That yields a transistor density of 13.0 million per square millimeter, a figure that reflects the relatively dense, power-efficient design of the mobile-oriented R9 M300 series.

The NVIDIA Tesla M2090, in contrast, uses the GF110 chip, built on Fermi 2.0 architecture, and belongs to the Tesla Fermi (x20xx) generation. It is manufactured on a 40 nm process, also at TSMC, with 3,000 million transistors spread across a much larger 520 mm² die. Its transistor density is only 5.8 million per square millimeter, less than half that of the AMD chip. This is a direct consequence of the older, less refined process node: the Tesla packs more transistors overall, but into a die more than three times the size, and it does so with far lower density.

The compute resources differ substantially. The R9 M380 has 768 shading units, 48 texture mapping units, and 16 raster output units. The Tesla M2090 has 512 shading units, 64 TMUs, and 48 ROPs. The AMD card has 50% more shading units, while the NVIDIA card has 33% more TMUs and three times the ROP count. These are different balances of compute, texture, and pixel throughput, and they reflect different intended workloads. The R9 M380's higher shading unit count supports its 1.536 TFLOPS of FP32 throughput, while the Tesla M2090's 1,332.2 GFLOPS is lower on paper. Yet the Tesla still wins the OpenCL test, suggesting that memory bandwidth and other factors matter in practice.

Memory configurations are also divergent. The R9 M380 has 4 GB of GDDR5 on a 128-bit bus, yielding 96.00 GB/s of bandwidth. The Tesla M2090 has 6 GB of GDDR5 on a 384-bit bus, yielding 177.4 GB/s, which is 84.8% higher. The Tesla's memory clock is 924 MHz with 3.7 Gbps effective data rate, while the R9 M380's memory runs at 1500 MHz with 6 Gbps effective. The AMD part has a higher clock speed, but the NVIDIA part has a much wider bus, and bandwidth favors the Tesla by a wide margin. This likely explains the OpenCL result, as compute-heavy workloads often depend on memory throughput.

Other architectural features differ as well. The R9 M380 supports PCIe 3.0 x16, while the Tesla M2090 uses PCIe 2.0 x16. The AMD card supports DirectX 12 (12_0), OpenGL 4.6, and Vulkan 1.2.170. The Tesla M2090 supports DirectX 12 (11_0) and OpenGL 4.6, but has no recorded Vulkan support. The Tesla also has no display outputs, making it a pure compute accelerator, while the R9 M380 is a mobile GPU with display capabilities. The Tesla is a dual-slot card with a 250 W TDP, requiring a 1x 6-pin plus 1x 8-pin power connector and a suggested 600 W power supply. The R9 M380 has no recorded TDP, slot width, or power connector information, consistent with its mobile orientation.

FAQ

Q: Which GPU wins in the direct head-to-head benchmark?

A: The NVIDIA Tesla M2090 wins the only comparable test, Geekbench OpenCL, with a score of 13,075 versus the AMD Radeon R9 M380's 12,565, a 3.9% difference.

Q: Does the Radeon R9 M380 have a higher overall benchmark average?

A: Yes. The R9 M380 averages 15,521 across its recorded benchmarks, while the Tesla M2090 averages 13,075. The R9 M380 also ranks at the 58th percentile among all GPUs, versus the Tesla's 53rd.

Q: Why does the Tesla M2090 win OpenCL despite having fewer shading units?

A: The Tesla M2090 has 512 shading units versus 768 on the R9 M380, but it has 177.4 GB/s of memory bandwidth versus 96.00 GB/s. The wider 384-bit bus and larger 6 GB frame buffer likely compensate for the lower compute count in memory-bound workloads.

Q: Can the Tesla M2090 output video?

A: No. The Tesla M2090 has no display outputs, while the Radeon R9 M380 is a mobile GPU with display support. The Tesla is a compute-only accelerator.

Q: Which card has better API support?

A: The R9 M380 supports DirectX 12 (12_0), OpenGL 4.6, and Vulkan 1.2.170. The Tesla M2090 supports DirectX 12 (11_0) and OpenGL 4.6, but has no recorded Vulkan support.

Q: How do the two cards compare in terms of process technology?

A: The R9 M380 is built on a 28 nm process with a 160 mm² die and 2,080 million transistors. The Tesla M2090 is built on a 40 nm process with a 520 mm² die and 3,000 million transistors.

The Verdict

The data is clear: the NVIDIA Tesla M2090 wins the direct OpenCL comparison, but the AMD Radeon R9 M380 is the higher-performing product overall. The Tesla's single win is narrow, just 3.9%, and it comes in a workload where its memory bandwidth advantage matters most. The R9 M380, however, has a higher average benchmark score (15,521 versus 13,075), a higher percentile rank (58th versus 53rd), and an additional Metal benchmark result that the Tesla cannot match. The R9 M380 also has a more modern feature set, including Vulkan support and PCIe 3.0, and it is built on a much denser process node.

For users prioritizing raw OpenCL compute in a single workload, the Tesla M2090 is the safer choice based on the recorded data. For anyone needing a more versatile GPU with higher average performance, display output capability, and modern API support, the Radeon R9 M380 is the stronger pick. The Tesla M2090 is a specialized compute card from an older generation, and its narrow benchmark win does not offset its lower overall standing in the database.

Specification Differences

The two GPUs differ in nearly every major specification category. The R9 M380 uses a 28 nm process, while the Tesla M2090 uses 40 nm. The R9 M380 has a die size of 160 mm² and 2,080 million transistors, while the Tesla M2090 has a die size of 520 mm² and 3,000 million transistors. Transistor density is 13.0M per mm² for the R9 M380 versus 5.8M per mm² for the Tesla. The R9 M380 has a base clock of 900 MHz and a boost clock of 1000 MHz, while the Tesla M2090 has no recorded base or boost clocks. Memory clocks differ as well: 1500 MHz with 6 Gbps effective for the R9 M380, versus 924 MHz with 3.7 Gbps effective for the Tesla.

Memory size, bus width, and bandwidth all favor the Tesla: 6 GB versus 4 GB, 384 bit versus 128 bit, and 177.4 GB/s versus 96.00 GB/s. Shading units favor the R9 M380 (768 versus 512), while TMUs favor the Tesla (64 versus 48) and ROPs favor the Tesla (48 versus 16). Pixel rate is higher on the Tesla at 20.83 GPixel/s versus 16.00 GPixel/s, while texture rate is higher on the R9 M380 at 48.00 GTexel/s versus 41.66 GTexel/s. FP32 compute is higher on the R9 M380 at 1.536 TFLOPS versus 1,332.2 GFLOPS. The Tesla has a 250 W TDP, dual-slot width, and 1x 6-pin plus 1x 8-pin power connectors, while the R9 M380 has no recorded power figures. The bus interface differs: PCIe 3.0 x16 for the R9 M380 versus PCIe 2.0 x16 for the Tesla. The Tesla has no display outputs, while the R9 M380 is a mobile GPU with display capability. The Tesla is 248 mm long, while the R9 M380 has no recorded dimensions.

Where Each One Wins

The AMD Radeon R9 M380 wins in overall performance ranking, average benchmark score, and feature completeness. It has a higher percentile rank (58th versus 53rd), a higher average score (15,521 versus 13,075), and a Metal benchmark result of 18,476 that the Tesla cannot replicate. It also has more shading units (768 versus 512), higher FP32 throughput (1.536 TFLOPS versus 1,332.2 GFLOPS), faster texture rate (48.00 GTexel/s versus 41.66 GTexel/s), and a more modern process node (28 nm versus 40 nm). Its API support is broader, including Vulkan 1.2.170, which the Tesla lacks, and it supports PCIe 3.0 rather than PCIe 2.0.

The NVIDIA Tesla M2090 wins in the direct OpenCL test, memory bandwidth, and memory capacity. Its 13,075 OpenCL score beats the R9 M380's 12,565 by 3.9%. Its 177.4 GB/s of bandwidth is 84.8% higher than the R9 M380's 96.00 GB/s, and its 6 GB frame buffer is 50% larger than the 4 GB on the AMD card. The Tesla also has more TMUs (64 versus 48), more ROPs (48 versus 16), and a higher pixel rate (20.83 GPixel/s versus 16.00 GPixel/s). For compute workloads that depend on memory throughput, the Tesla is the better performer according to the data. For general GPU tasks, gaming, or any workload requiring display output or modern API features, the Radeon R9 M380 is the better choice.