ASUS
SKU: DUAL-RTX3060-O12G-V2
Overview
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Overview
Questions about this product? Free pre-sales support from a senior specialist — product questions, compatibility checks, BOM quotes, price confirmation — typically answered within one business day. Need camera placement or system design work? Engineering time is $175 per hour (qty 1 = 1 hour). Hardware buyers get up to one hour ($175) credited back on their order.
The ASUS DUAL-RTX4070-12G-WHI is a white-finish dual-fan GeForce RTX 4070 graphics card carrying 12GB of GDDR6X memory across a 192-bit bus — a practical choice for workstations and rendering nodes where you need Ada Lovelace performance without stepping into the power and thermal demands of the RTX 4080 class. The DUAL-RTX4070-12G-WHI (often searched as DUAL RTX4070 12G WHI) slots into any PCIe 4.0 x16 system and connects up to four displays simultaneously via its single HDMI 2.1 and three DisplayPort 1.4a outputs.
The DUAL-RTX4070-12G-WHI installs into any PCIe 4.0 (or backward-compatible PCIe 3.0) x16 slot. Verify your chassis has clearance for a dual-slot, dual-fan cooler before ordering — ASUS does not publish dimensional data in the known spec set for this SKU. Power connector requirements follow RTX 4070 reference spec; confirm your PSU has the appropriate 16-pin (12VHPWR) or adapter cable. No parallel processing technology (NVLink/SLI) is supported on this card — this is a single-GPU solution only.
For graphics cards in the ASUS product line, the DUAL series sits between the entry-level PHoenix and the higher-end TUF/ROG STRIX variants in terms of cooling mass and factory overclock. If you need the full ASUS ASUS GPU catalog for comparison, the TUF RTX 4070 carries a larger heatsink suited to sustained compute workloads in poorly ventilated enclosures.
Integrators deploying this card into a workstation for GPU-accelerated analytics or NVR transcoding offload should confirm CUDA toolkit compatibility with the software stack — the 5,888 CUDA cores are accessible via CUDA, but the evidence does not confirm OpenCL or specific SDK versions. Pair with a managed PoE switch infrastructure when deploying alongside IP camera systems that feed GPU-accelerated analytics engines.
Q: What is the maximum resolution supported by the ASUS DUAL-RTX4070-12G-WHI?
A: The DUAL-RTX4070-12G-WHI supports a maximum resolution of 7680×4320 pixels (8K), output via HDMI 2.1 or DisplayPort 1.4a.
Q: How many monitors can I connect to the DUAL-RTX4070-12G-WHI simultaneously?
A: Up to four displays simultaneously — one via HDMI 2.1 and three via DisplayPort 1.4a. This makes it a practical single-card solution for quad-monitor operator workstations.
Q: Does the DUAL-RTX4070-12G-WHI support SLI or multi-GPU configurations?
A: No. Parallel processing technology (NVLink/SLI) is not supported on this card. It is a single-GPU solution only.
Q: What PCIe interface does the ASUS DUAL-RTX4070-12G-WHI use?
A: The card uses PCI Express 4.0. It is backward compatible with PCIe 3.0 slots at reduced bandwidth — confirm your platform supports the card's power and physical requirements before deploying.
Q: What is the difference between the DUAL-RTX4070-12G-WHI and the standard DUAL-RTX4070-12G?
A: The -WHI suffix denotes the white colorway. Functionally, both cards share the same GPU, memory configuration, cooling design, and clock speeds. The distinction is purely aesthetic.
Q: Does the DUAL-RTX4070-12G-WHI support CUDA?
A: Yes. The card includes 5,888 CUDA cores on NVIDIA's Ada Lovelace architecture, supporting CUDA-based compute workloads including GPU-accelerated inference, transcoding, and rendering pipelines.

The DUAL-RTX4070-12G-WHI hits a useful middle ground for integrators building GPU-accelerated analytics workstations around NVIDIA's Ada Lovelace platform — specifically, the 5,888 CUDA cores and 12GB of GDDR6X memory position it well for multi-stream inference pipelines without the power draw and cost of RTX 4080 or above. Where I've found it relevant is in edge analytics nodes that need to process decoded video frames through a detection model in near-real-time, where 12GB of VRAM keeps model weights resident without constant swapping.
Technical Highlights:
Deployment Considerations:
Best fit for a quad-display analytics workstation or a compact edge server running CUDA-based video analytics where 12GB VRAM is sufficient for the model set and the white finish either doesn't matter or is a deliberate build requirement.
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