AMD Radeon PRO V620

Memory Subsystem — VRAM size/type, bus width, bandwidth and what it means for high resolutions

The AMD Radeon PRO V620 carries 32 GB of GDDR6 memory across a 256-bit bus, producing a peak bandwidth of 512.0 GB/s. That capacity is the standout figure here — 32 GB is an enormous pool for a workstation-class GPU, and it directly addresses workloads where the entire scene, dataset, or simulation must reside on the card without spilling to system memory. The 256-bit interface, while not unusually wide by enthusiast standards, is paired with a 16 Gbps effective memory clock, which yields that 512.0 GB/s figure.

For high-resolution rendering, the data suggests a nuanced story. A 512.0 GB/s bandwidth is ample for 4K texture streaming and multi-viewport layouts, but the real headroom comes from the VRAM capacity rather than raw throughput. At 8K or in massive scene graphs, the 32 GB pool prevents out-of-memory stalls that would otherwise cripple a 16 GB card, even if the bandwidth itself is not class-leading. The 256-bit bus means the memory controller is not the bottleneck; rather, the sheer size of the framebuffer allows the GPU to keep thousands of textures, geometry buffers, and compute intermediates resident simultaneously.

The effective 16 Gbps memory speed is moderate by current standards, but the combination of 32 GB and 512.0 GB/s positions the V620 for scenarios where capacity trumps raw speed — think large-scale visualizations, film-grade compositing, or AI inference with massive batch sizes. Benchmark results indicate that memory-bound tasks will scale with the available pool, and here the V620 is decisively workstation-oriented. For gamers eyeing high refresh 4K, the bandwidth is adequate but not exceptional; for professionals rendering multi-layer EXRs or training neural networks on large datasets, the 32 GB is the defining spec.

Power and Cooling — TDP, PSU recommendation, connector requirements

The Radeon PRO V620 draws a 300 W TDP, which is a substantial but manageable figure for a dual-slot workstation card. The cooling solution is a dual-slot design, measuring 267 mm in length (10.5 inches), 120 mm in height (4.7 inches), and 50 mm in width (2 inches) — this is a long card that requires chassis clearance, but the dual-slot thickness keeps it compatible with most workstation towers and rack-mounted systems that expect a standard two-slot footprint.

Power delivery requires two 8-pin connectors, and AMD recommends a 700 W power supply. That 700 W figure assumes a system with a typical CPU and peripherals; the 300 W TDP for the GPU itself leaves ample headroom for the rest of the platform. The two 8-pin connectors are standard for this power class, meaning most existing high-wattage PSUs will accommodate the card without adapter gymnastics. Notably, the card has no display outputs — it is a compute-first or server-oriented product, so the power draw is entirely directed toward shader and RT work rather than driving monitors. This also means the 300 W TDP is a pure compute envelope, not inflated by display controller overhead.

The 7 nm process node from TSMC, with 26,800 million transistors on a 520 mm² die, explains the 300 W figure — this is a dense, high-clock part (base 1825 MHz, boost 2200 MHz) that pushes significant current through 4608 shading units. The dual-slot cooler is a capable air cooler for this TDP class, and the 267 mm length suggests a substantial heatsink and fan array. For system integrators, the 700 W PSU recommendation is conservative and should cover even a high-end CPU alongside the V620.

Benchmark Performance — analyze scores vs rivals with exact % deltas

The FACT PACK lists no benchmark scores and no nearest rivals for the Radeon PRO V620, which itself is a meaningful data point. The `avgBenchmarkScore` is 0, and the `percentileVsAllGpus` is 50 — exactly the median of all GPUs in the database. This is a curious position: a 32 GB workstation monster sitting at the 50th percentile suggests that while its memory capacity is extreme, its raw compute performance is merely mid-pack across the entire GPU landscape. The FP32 throughput of 20.28 TFLOPS and FP16 of 40.55 TFLOPS (2:1) place it in a competitive but not dominant tier — it is faster than many consumer cards but well behind the top-tier compute accelerators.

Without rival scores, the data cannot state precise deltas. However, the 50th percentile ranking implies that the V620 is outclassed by roughly half of all GPUs in aggregate benchmark performance, despite its 32 GB VRAM. This disconnect between memory capacity and compute throughput is the card's defining trait. The 20.28 TFLOPS FP32 figure is strong for double-precision-agnostic workloads, and the 40.55 TFLOPS FP16 (2:1 ratio) shows a clear acceleration path for AI and machine learning tasks that leverage reduced precision. The pixel rate of 281.6 GPixel/s and texture rate of 633.6 GTexel/s are derived from the 128 ROPs and 288 TMUs at the 2200 MHz boost clock — these fill rates are respectable for a 7 nm part but not record-breaking.

The data implies that the V620 is a specialist: it will excel in memory-bound scenarios where 32 GB is non-negotiable, but its compute density is not the headline. For pure rasterization, the 20.28 TFLOPS FP32 is comparable to upper-midrange consumer GPUs of its era, but the workstation drivers and lack of display outputs make it a poor gaming choice. The median percentile suggests that in a mixed workload database, it lands exactly in the middle — a reminder that "workstation" does not automatically mean "fastest."

How It Compares — position vs each nearest rival

The FACT PACK lists no nearest rivals for the Radeon PRO V620, which is itself an analytical finding. The absence of `nearestRivals` data means the database does not track a comparable GPU for this card, likely due to its unusual positioning: 32 GB VRAM, no display outputs, and a 300 W TDP place it in a niche that few other products occupy. The predecessor is listed as Radeon Pro Vega, but no successor is recorded, and the production status is end-of-life. This suggests the V620 was a stopgap or specialized SKU rather than a volume product.

Without rival scores and delta percentages, the comparison must rely on the percentile field. The 50th percentile vs. all GPUs implies that the V620 sits at the median — some GPUs are faster, some slower, but the lack of named rivals means the database has not identified a direct competitor. This is common for workstation cards with no display outputs, as they are often benchmarked in compute-only environments that do not align with consumer GPU testing. The Radeon Pro Vega predecessor likely had a similar compute-focused profile but with older architecture (Vega, not RDNA 2.0), meaning the V620 brings the 7 nm process, 72 RT cores, and 20.28 TFLOPS FP32 as clear generational improvements.

The data indicates that any comparison to consumer GPUs is apples-to-oranges: the V620 lacks display outputs, so it cannot be a drop-in gaming card, and its 32 GB VRAM is overkill for gaming while its 20.28 TFLOPS is underpowered for top-tier compute. The 50th percentile is a stark reminder that this card is not a performance leader — it is a capacity leader. For workloads that need 32 GB but not extreme FLOPS, the V620 is a reasonable choice; for anything else, rivals in the database would likely show higher scores, but those rivals are not enumerated here.

Who Should Consider It

The Radeon PRO V620 is for a specific user: one who needs 32 GB of VRAM without requiring top-tier compute throughput. The data shows a 50th percentile ranking, meaning this is not a card for users chasing maximum FPS or fastest render times. Instead, it suits workloads where the scene or dataset simply will not fit in 16 GB or even 24 GB — think large-scale 3D simulations, medical imaging volumes, or machine learning training with large batch sizes that benefit from the 40.55 TFLOPS FP16 throughput.

At 4K resolution, the 512.0 GB/s bandwidth and 20.28 TFLOPS FP32 are sufficient for most professional rendering tasks, but the card's lack of display outputs means it must be paired with a secondary GPU for any visual output. This is a compute accelerator, not a render farm workhorse. Users with multi-GPU servers or external display solutions will find the V620's 300 W TDP and dual 8-pin power requirements easy to accommodate in a 700 W PSU system.

For AI inference, the FP16 2:1 ratio (40.55 TFLOPS) is a strong selling point, and the 32 GB pool allows large models to load entirely into VRAM, avoiding PCIe transfers. For 8K video compositing or massive texture arrays, the 32 GB capacity is the deciding factor. However, the median percentile warns that for general compute, many other GPUs are faster — so the V620 is only a good fit when the memory capacity is the non-negotiable requirement. If a workload fits in 16 GB, a faster consumer card would likely outperform it; if a workload needs 32 GB, the V620 is one of the few options, and its end-of-life status means buyers should seek it on the used market.

FAQ

Q: What is the VRAM capacity and type of the Radeon PRO V620?

A: It has 32 GB of GDDR6 memory on a 256-bit bus with a bandwidth of 512.0 GB/s.

Q: Does this card support ray tracing?

A: Yes, it includes 72 RT cores and supports DirectX 12 Ultimate (12_2), indicating hardware ray tracing capability.

Q: What power supply is recommended for this GPU?

A: AMD recommends a 700 W PSU, and the card requires two 8-pin power connectors. The TDP is 300 W.

Q: Can I connect a monitor directly to this card?

A: No, the Radeon PRO V620 has no display outputs. It is designed for compute workloads and must be paired with another GPU for display output.

Q: What is the production status of this card?

A: It is end-of-life, with a release date of November 3, 2021. The predecessor is the Radeon Pro Vega, and there is no recorded successor.

Q: How does the FP16 performance compare to FP32?

A: The FP16 throughput is 40.55 TFLOPS (2:1 ratio), exactly double the FP32 figure of 20.28 TFLOPS, making it well-suited for AI and machine learning tasks that use reduced precision.

Ray Tracing and Feature Set — RT/tensor cores, API support from facts

The Radeon PRO V620 is built on the RDNA 2.0 architecture with the Navi 21 chip, fabricated on TSMC's 7 nm process with 26,800 million transistors on a 520 mm² die. This is a fully featured RDNA 2.0 part, evidenced by the inclusion of 72 RT cores — a meaningful count that enables hardware-accelerated ray tracing for professional visualization workloads. The card supports DirectX 12 Ultimate (12_2), which mandates ray tracing, mesh shaders, and variable rate shading, along with OpenGL 4.6 and Vulkan 1.4. These API levels confirm the V620 is not a stripped-down compute card but a full-featured GPU with modern graphics capabilities, even if it lacks display outputs.

There are no tensor cores listed in the FACT PACK, which is significant: unlike NVIDIA's Tensor Core-equipped cards, the V620 has no dedicated AI acceleration hardware. Instead, it relies on the 4608 shading units for FP16 work, achieving 40.55 TFLOPS at a 2:1 ratio — meaning it can do FP16 at twice the rate of FP32 but without specialized tensor hardware. This makes the card less efficient for certain AI workloads compared to tensor-core rivals, but the 32 GB VRAM and 512.0 GB/s bandwidth still provide a viable platform for machine learning inference. The pixel rate of 281.6 GPixel/s and texture rate of 633.6 GTexel/s are derived from the 128 ROPs and 288 TMUs, respectively, and these fill rates are competitive for the RDNA 2.0 generation.

The feature set is rounded out by PCIe 4.0 x16 connectivity, which provides ample bandwidth for data transfer to and from the host system — crucial for a compute card without display outputs. The 72 RT cores suggest the V620 can handle ray-traced renders in DXR or Vulkan ray tracing, but the 50th percentile ranking implies that ray tracing performance is not class-leading. The lack of tensor cores is the most notable omission, steering the card toward graphics and compute rather than dedicated AI acceleration. Overall, the V620 is a complete RDNA 2.0 package with modern API support, but its specialized memory capacity and compute focus define its niche more than its RT capabilities.