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Radeon RX 9060 XT has official 8 GB and 16 GB GDDR6 configurations.
Radeon RX 9060 XT has official 8 GB and 16 GB GDDR6 configurations. Compare them in one guide while preserving their memory and power differences, rather than merging them into an unspecified RX 9060 XT deployment profile.
Official variants and the memory boundary
The table follows AMD materials for this model. It describes dedicated device memory, not system RAM. A “not verified” entry preserves a source gap; a neighboring configuration cannot supply the missing specification.
| AMD variant | Dedicated memory | Board power |
|---|---|---|
| 8 GB | 8 GB GDDR6 | 150 W |
| 16 GB | 16 GB GDDR6 | 160 W |
Establish the LLM software path
The ROCm Core SDK 10.1.0 device list includes Radeon RX 9060 XT. This is an exact hardware entry, not approval for every operating system, PyTorch build, or quantization format. Select the specific GPU and OS in the compatibility matrix, then record the driver, runtime, and framework release. A listed card does not establish that every kernel used by an inference engine works correctly. Establish device detection, loading of a saved model revision, and a reference request before exploring sustained operation or concurrent requests. ROCm names RX 9060 XT in one generic row; this does not separately qualify the 8 GB and 16 GB configurations.
A practical scenario for this model
Imagine a set of workstations containing both 8 GB and 16 GB boards. A hypothetical 14 billion parameter model at 4 bits per weight needs 7 billion bytes for raw weight storage. Packing overhead, additional tensors, and KV cache are excluded from that estimate. The 8 GB configuration may have insufficient margin even when one short request succeeds; the 16 GB configuration needs its own test rather than an automatic doubling of request capacity. Create two named launch profiles sharing a reference fixture but recording independently validated placement limits. Inventory every board capacity separately so a scheduler cannot select a device by the common product name and silently substitute a different operating profile.
Validate Blender Cycles separately
RDNA 4 meets the HIP hardware floor in the Blender Cycles 5.2 LTS manual: RDNA 1 or newer. This renderer requirement is independent of ROCm LLM support; validate the actual driver, build, and scene on the intended machine.
For a working project, preserve the list of large textures and geometry. Complete a frame on both capacities: an identical scene may need different placement despite the matching GPU name.
Preserve a machine-level acceptance record
The table gives AMD board-power specifications, not measured whole-computer consumption. Check the power supply, connectors, card dimensions, and airflow path for the actual system separately. Board power cannot establish inference speed.
The acceptance table needs separate 8 GB and 16 GB rows with effective settings. Do not transfer the 150 W specification to the 16 GB configuration, which is specified at 160 W.
The acceptance artifact should connect board identity, software versions, model revision, and the workload actually exercised. After any of those changes, the old result describes its original run rather than establishing compatibility of the new configuration.
Related reading
Reconcile llama.cpp unified KV pools and per-slot context limits; RAM and VRAM: which memory matters for an AI server?; NVIDIA and AMD GPU catalogue for LLM inference and server rendering.