AMD Radeon Instinct MI60 vs NVIDIA RTX 4000 SFF Ada Generation Comparison

The NVIDIA RTX 4000 SFF Ada Generation and the AMD Radeon Instinct MI60 represent two very different philosophies in professional computing, divided by nearly five years of architectural evolution. The data shows a clear performance leader, but the MI60’s massive memory pool and compute-oriented design still hold relevance for specific workloads. Benchmark results indicate the RTX 4000 SFF Ada takes a decisive lead in every measured test, yet the choice between these two cards depends entirely on whether raw compute density or sheer memory capacity matters more for the target application.

Where Each One Wins

The NVIDIA RTX 4000 SFF Ada Generation wins in every benchmark category recorded in the data. It dominates both Geekbench OpenCL and Vulkan tests, with a commanding 34.9% lead in OpenCL and a substantial 18.3% lead in Vulkan. This consistent victory across both APIs suggests the Ada Lovelace architecture delivers superior general-purpose compute performance and graphics throughput compared to the older GCN-based Instinct MI60. The RTX 4000 SFF Ada achieves an average benchmark score of 117,088, placing it in the 95th percentile of all GPUs, while the MI60’s average of 92,466 puts it in the 93rd percentile.

The AMD Radeon Instinct MI60’s only clear advantage lies in memory capacity and bandwidth. It offers 32 GB of HBM2 memory compared to the RTX 4000 SFF Ada’s 20 GB of GDDR6, and its 1.02 TB/s memory bandwidth dwarfs the 280.0 GB/s available on the NVIDIA card. For workloads that are strictly memory-bound — such as large dataset processing or in-memory databases — the MI60’s 4096-bit memory bus and HBM2 technology provide a theoretical advantage that the benchmark scores do not capture. However, the data shows this memory advantage does not translate into compute wins in the tested scenarios.

Architecture Differences

The architectural divide between these two GPUs is stark. The RTX 4000 SFF Ada uses the AD104 chip built on TSMC’s 5 nm process, packing 35,800 million transistors into a 294 mm² die. This yields a transistor density of 121.8 million per square millimeter. The MI60 uses the Vega 20 chip on TSMC’s 7 nm node, with 13,230 million transistors on a larger 331 mm² die, resulting in a much lower density of 40.0 million per square millimeter. The newer process node allows the RTX 4000 SFF Ada to achieve higher performance with dramatically lower power consumption — 70 W TDP versus the MI60’s 300 W TDP.

Feature sets diverge significantly. The RTX 4000 SFF Ada includes 48 dedicated ray tracing cores and 192 tensor cores, enabling hardware-accelerated ray tracing and AI workloads. The MI60 has no ray tracing cores and no tensor cores, relying purely on its 4096 shading units for compute. The RTX 4000 SFF Ada features 6144 shading units, 192 texture mapping units, and 64 render output units, while the MI60 offers 4096 shading units, 256 TMUs, and 64 ROPs. The MI60’s higher texture rate of 460.8 GTexel/s and pixel rate of 115.2 GPixel/s reflect its higher boost clock of 1800 MHz, compared to the RTX 4000 SFF Ada’s 1560 MHz boost clock.

Memory architectures could not be more different. The RTX 4000 SFF Ada uses 20 GB of GDDR6 on a 160-bit bus, while the MI60 uses 32 GB of HBM2 on a 4096-bit bus. The MI60’s effective memory clock is just 2 Gbps, but the massive bus width delivers 1.02 TB/s bandwidth. The RTX 4000 SFF Ada runs memory at 14 Gbps effective, yet the narrow bus limits bandwidth to 280.0 GB/s. The MI60 also supports FP16 at a 2:1 ratio, delivering 29.49 TFLOPS versus its 14.75 TFLOPS FP32 rate, while the RTX 4000 SFF Ada offers 19.17 TFLOPS for both FP32 and FP16 at a 1:1 ratio.

Head-to-Head Benchmarks

The Geekbench OpenCL test delivers the most decisive result in this comparison. The RTX 4000 SFF Ada scores 124,812 against the MI60’s 92,488, a difference of 34.9%. This substantial gap reflects the NVIDIA card’s architectural efficiency and higher FP32 throughput of 19.17 TFLOPS versus the MI60’s 14.75 TFLOPS. The RTX 4000 SFF Ada also benefits from newer driver optimizations and the Ada Lovelace architecture’s improved compute unit utilization.

In the Geekbench Vulkan test, the margin narrows but remains firmly in NVIDIA’s favor. The RTX 4000 SFF Ada scores 109,364 while the MI60 achieves 92,444, giving the NVIDIA card an 18.3% advantage. The smaller delta in Vulkan suggests that the MI60’s raw hardware resources — its additional TMUs and higher clock speeds — help it partially close the gap in graphics-oriented workloads. Still, the RTX 4000 SFF Ada’s superior API support, including DirectX 12 Ultimate and Vulkan 1.4, provides better optimization paths than the MI60’s DirectX 12 (12_1) and Vulkan 1.3.

Looking at rival positioning, the RTX 4000 SFF Ada’s average score of 117,088 sits just 0.3% behind the NVIDIA GB10 and 1.6% behind the AMD Radeon PRO W7700, while leading the Tesla V100 SXM2 16 GB by 2.4% and the RTX A5500 Mobile by 2.8%. The MI60’s average of 92,466 is 0.9% ahead of the NVIDIA RTX A4500 and 1.5% ahead of the RTX A4500 Mobile, but trails the AMD Radeon Pro VII by 4.8% and the Radeon RX 7900M by 5.2%. This places the MI60 in a lower performance tier despite its enterprise positioning.

FAQ

Q: Which GPU has better overall benchmark performance?

A: The NVIDIA RTX 4000 SFF Ada Generation wins both head-to-head benchmarks. It scores 124,812 in Geekbench OpenCL versus 92,488 for the MI60, and 109,364 in Geekbench Vulkan versus 92,444, representing leads of 34.9% and 18.3% respectively.

Q: How does memory capacity compare between the two cards?

A: The AMD Radeon Instinct MI60 offers 32 GB of HBM2 memory on a 4096-bit bus with 1.02 TB/s bandwidth. The NVIDIA RTX 4000 SFF Ada provides 20 GB of GDDR6 on a 160-bit bus with 280.0 GB/s bandwidth.

Q: What are the power requirements for each card?

A: The RTX 4000 SFF Ada has a 70 W TDP with no power connectors and a suggested power supply of 250 W. The MI60 has a 300 W TDP, requires one 6-pin and one 8-pin power connector, and needs a 700 W suggested power supply.

Q: Which card supports ray tracing and AI acceleration?

A: Only the NVIDIA RTX 4000 SFF Ada supports these features, with 48 ray tracing cores and 192 tensor cores. The AMD Radeon Instinct MI60 has no ray tracing or tensor cores in its architecture.

Q: How do their production statuses differ?

A: The NVIDIA RTX 4000 SFF Ada is listed as Active, having launched on 2023-03-20. The AMD Radeon Instinct MI60 is marked as End-of-life, with its release date on 2018-11-17.

Q: What is the form factor difference between the two cards?

A: Both are dual-slot cards, but the RTX 4000 SFF Ada is significantly smaller at 168 mm in length and 69 mm in height, compared to the MI60’s 267 mm length and 111 mm height.

The Verdict

The data makes a compelling case for the NVIDIA RTX 4000 SFF Ada Generation as the superior performer in nearly every measurable category. It wins both head-to-head benchmarks with margins of 34.9% and 18.3%, achieves a higher average benchmark score of 117,088 versus 92,466, and does so while consuming only 70 W compared to the MI60’s 300 W. The RTX 4000 SFF Ada also brings modern features like ray tracing cores, tensor cores, and newer API support that the MI60 completely lacks.

For users prioritizing compute performance, energy efficiency, and a compact form factor, the RTX 4000 SFF Ada is the clear choice. Its 5 nm process node, higher transistor density, and superior FP32 throughput of 19.17 TFLOPS versus 14.75 TFLOPS deliver tangible benefits in OpenCL and Vulkan workloads. The card’s 95th percentile ranking among all GPUs, compared to the MI60’s 93rd percentile, reinforces its higher standing in the performance hierarchy.

The AMD Radeon Instinct MI60 retains one distinct advantage: its 32 GB of HBM2 memory with 1.02 TB/s bandwidth. For applications that require loading extremely large models or datasets into GPU memory, the MI60’s 60% larger memory pool could prove decisive, even with lower raw compute scores. Its 29.49 TFLOPS FP16 performance at a 2:1 ratio also offers a compute advantage for mixed-precision workloads that can leverage half-precision arithmetic.

However, the MI60’s end-of-life status, higher power draw, and lack of modern features like ray tracing make it a difficult recommendation for most users. The RTX 4000 SFF Ada delivers better performance per watt, smaller physical footprint, and future-proofing through Ada Lovelace architecture. Unless the specific workload demands more than 20 GB of VRAM or the 1.02 TB/s memory bandwidth, the NVIDIA RTX 4000 SFF Ada Generation is the objectively better choice based on the benchmark data. Those with memory-intensive AI inference or scientific computing needs should evaluate whether the MI60’s memory advantage outweighs its significant compute deficit.