AMD Radeon RX 570X vs NVIDIA Tesla M2090 Comparison

The AMD Radeon RX 570X and NVIDIA Tesla M2090 represent two distinct eras of GPU design, separated by seven years of architectural evolution. The data shows a decisive performance gap in the single available benchmark, but the comparison extends beyond raw speed into fundamental differences in compute philosophy, power delivery, and intended use cases. The RX 570X delivers a Geekbench OpenCL score of 38,939 against the M2090’s 13,075, a 197.8% advantage that places them in different performance tiers, yet the M2090’s legacy as a compute-oriented Tesla part means its strengths lie in specifications that modern consumer benchmarks do not fully capture.

Head-to-Head Benchmarks

The only directly comparable metric is Geekbench OpenCL, where the AMD Radeon RX 570X achieves 38,939 points against the NVIDIA Tesla M2090’s 13,075 points. This 197.8% delta is not a marginal improvement; it represents nearly triple the compute output in a workload that stresses general-purpose GPU execution. The RX 570X’s average benchmark score of 13,871 across all tests (including Passmark G2D at 750 and G3D at 1,923) further illustrates its versatility, while the M2090’s average score of 13,075 is derived solely from its OpenCL result.

The magnitude of this gap becomes clearer when placed in context of each card’s nearest rivals. The RX 570X sits at the 55th percentile of all GPUs, with its average score of 13,871 placing it just 0.4% ahead of the NVIDIA RTX A2000 Mobile (13,821) and 0.4% ahead of the AMD Radeon 660M (13,812). The M2090, at the 53rd percentile, achieves an average score of 13,075, which is 0.7% behind the NVIDIA GeForce GTX 1660 SUPER (12,986) but 0.9% ahead of the NVIDIA GeForce GTX 950 (13,189). Interestingly, despite the massive OpenCL delta, both cards occupy similar percentile positions relative to the entire GPU landscape, suggesting that the M2090’s single benchmark may underrepresent its broader compute capabilities.

In the head-to-head tally, the RX 570X wins 1 benchmark out of 1, with the M2090 recording no wins. This clean sweep in the available data is expected given the architectural gulf between them, but it does not tell the full story of the M2090’s specialized compute features that are not exercised by OpenCL’s general-purpose workload.

Architecture Differences

The foundational difference lies in the manufacturing process and chip design. The RX 570X uses a 14 nm process at GlobalFoundries, packing 5,700 million transistors into a 232 mm² die, yielding a transistor density of 24.6 million per square millimeter. The M2090 uses a 40 nm TSMC process, fitting 3,000 million transistors into a substantially larger 520 mm² die, with a density of just 5.8 million per square millimeter. This 4.2x density advantage for the RX 570X explains how it achieves higher performance with a smaller physical footprint and lower power consumption.

Architecturally, the RX 570X is built on GCN 4.0 (Polaris 20), while the M2090 uses Fermi 2.0 (GF110). The GCN design emphasizes parallel throughput with 2,048 shading units, 128 texture mapping units, and 32 ROPs, compared to the M2090’s 512 shading units, 64 TMUs, and 48 ROPs. The RX 570X’s 5.095 TFLOPS FP32 performance dwarfs the M2090’s 1,332.2 GFLOPS (1.33 TFLOPS), a 3.8x gap that directly reflects the shading unit count. The RX 570X also supports FP16 at a 1:1 ratio (5.095 TFLOPS), while the M2090 has no FP16 capability listed, a critical differentiator for modern compute workloads that leverage mixed-precision arithmetic.

Memory subsystems also diverge significantly. The RX 570X features 8 GB of GDDR5 on a 256-bit bus, delivering 224.0 GB/s bandwidth at 1,750 MHz (7 Gbps effective). The M2090 has 6 GB of GDDR5 on a wider 384-bit bus, but its slower 924 MHz clock (3.7 Gbps effective) results in just 177.4 GB/s bandwidth. The RX 570X’s higher bandwidth, combined with 42% more memory capacity, provides a clear advantage for texture-heavy workloads and large datasets. Interface support follows a generational split: the RX 570X uses PCIe 3.0 x16, while the M2090 is limited to PCIe 2.0 x16, halving the available host-to-device bandwidth for data transfers.

FAQ

Q: Which card has a higher transistor density?

A: The AMD Radeon RX 570X achieves 24.6 million transistors per square millimeter, while the NVIDIA Tesla M2090 has 5.8 million per square millimeter, a 4.2x difference stemming from the 14 nm versus 40 nm process nodes.

Q: Does the NVIDIA Tesla M2090 support FP16 computation?

A: No, the M2090 has no FP16 listing in its specifications. The RX 570X supports FP16 at 5.095 TFLOPS with a 1:1 ratio to its FP32 performance, making it suitable for mixed-precision workloads.

Q: What is the memory bandwidth difference?

A: The RX 570X provides 224.0 GB/s bandwidth from 8 GB GDDR5 on a 256-bit bus, whereas the M2090 provides 177.4 GB/s from 6 GB GDDR5 on a 384-bit bus. The RX 570X is 26.3% faster in bandwidth despite the narrower bus.

Q: How do their power requirements compare?

A: The RX 570X has a TDP of 150 W and requires a single 6-pin power connector with a 450 W suggested PSU. The M2090 has a TDP of 250 W, requires one 6-pin and one 8-pin connector, and demands a 600 W suggested PSU. The RX 570X draws 40% less power.

Q: Which card has better API support for modern games?

A: The RX 570X supports DirectX 12 (12_0), OpenGL 4.6, and Vulkan 1.3, while the M2090 supports DirectX 12 (11_0) and OpenGL 4.6 but has no Vulkan support. The RX 570X also offers display outputs (1x DVI, 1x HDMI 2.0b, 3x DisplayPort 1.4a), whereas the M2090 has no display outputs, indicating compute-only use.

Q: What is the performance percentile of each card?

A: The RX 570X is at the 55th percentile of all GPUs, while the M2090 is at the 53rd percentile. Despite the 197.8% OpenCL delta, their overall percentile positions are close, reflecting the M2090’s specialized compute design.

The Verdict

The benchmark data unequivocally favors the AMD Radeon RX 570X for general compute tasks. Its 197.8% lead in Geekbench OpenCL, combined with 3.8x higher FP32 throughput and 26.3% more memory bandwidth, makes it the superior choice for any workload that relies on raw parallel processing. The RX 570X also offers modern feature support—Vulkan 1.3, DirectX 12 (12_0), FP16 capabilities—that the M2090 lacks entirely. For users who need display outputs, the RX 570X provides them, while the M2090 offers none, confirming its role as a headless compute accelerator.

However, the M2090 is not without merit in its specific niche. Its 520 mm² die and 48 ROPs suggest a design optimized for certain double-precision or rasterization-heavy compute tasks that the benchmark data does not cover. Its 384-bit memory bus, despite lower clock speeds, offers a wider path for data-intensive operations. The M2090’s 53rd percentile ranking, just 2 points below the RX 570X, indicates that its compute capabilities remain relevant relative to the broader GPU ecosystem, even if the OpenCL score underperforms.

The production status of both cards is end-of-life, so neither represents a future-proof investment. The RX 570X’s 2018 release date versus the M2090’s 2011 release date explains the architectural gap; seven years of process and design advancement are fully reflected in the performance delta. The data supports choosing the RX 570X for virtually any modern compute or graphics workload, while the M2090 should only be considered for legacy systems that specifically require its Fermi-based compute features.

Specification Differences

The two cards differ in nearly every measurable specification. Process node: 14 nm (RX 570X) versus 40 nm (M2090). Transistor count: 5,700 million versus 3,000 million. Die size: 232 mm² versus 520 mm². Memory size: 8 GB versus 6 GB. Memory bus width: 256-bit versus 384-bit. Memory clock: 1,750 MHz (7 Gbps) versus 924 MHz (3.7 Gbps). Bandwidth: 224.0 GB/s versus 177.4 GB/s. Shading units: 2,048 versus 512. TMUs: 128 versus 64. ROPs: 32 versus 48. Pixel rate: 39.81 GPixel/s versus 20.83 GPixel/s. Texture rate: 159.2 GTexel/s versus 41.66 GTexel/s. FP32: 5.095 TFLOPS versus 1,332.2 GFLOPS. FP16: 5.095 TFLOPS versus none. TDP: 150 W versus 250 W. Power connectors: 1x 6-pin versus 1x 6-pin + 1x 8-pin. Suggested PSU: 450 W versus 600 W. Bus interface: PCIe 3.0 x16 versus PCIe 2.0 x16. Display outputs: 1x DVI, 1x HDMI 2.0b, 3x DisplayPort 1.4a versus none. DirectX support: 12 (12_0) versus 12 (11_0). Vulkan support: 1.3 versus none. Physical length: 241 mm versus 248 mm. Both are dual-slot cards.

Where Each One Wins

The AMD Radeon RX 570X wins decisively in OpenCL compute performance, FP32 throughput, memory capacity, bandwidth, and modern API support. Its 224.0 GB/s bandwidth and 5.095 TFLOPS FP32 make it the clear pick for general-purpose GPU computing, machine learning inference with FP16 support, and any workload requiring display output or Vulkan acceleration. The RX 570X’s lower TDP of 150 W and single 6-pin connector also make it easier to integrate into existing systems without PSU upgrades.

The NVIDIA Tesla M2090 wins in raw memory bus width (384-bit versus 256-bit), which can benefit certain memory-access patterns that favor wide buses over high clocks. Its higher ROP count (48 versus 32) suggests potential advantages in pixel-heavy compute operations, though its lower pixel rate of 20.83 GPixel/s versus 39.81 GPixel/s indicates the RX 570X still outperforms in practice. The M2090 also has a longer physical length (248 mm versus 241 mm), which is irrelevant to performance but may matter for chassis compatibility. Its only realistic win is in legacy compute environments that require Fermi-specific CUDA features, a scenario not covered by the benchmark data but implied by its Tesla lineage and lack of display outputs. For all measured metrics, the RX 570X is the superior performer.