AMD ROCm Compatibility — Hardware Planning for Local AI

AMD GPUs offer competitive performance through ROCm (Radeon Open Compute) but require careful compatibility verification.

ROCm-Supported consumer GPUs

GPU	VRAM	ROCm Support	Notes
RX 6600	8GB	ROCm 6.0+	Entry-level
RX 6700 XT	12GB	ROCm 5.7+	Good value
RX 6800	16GB	ROCm 5.4+	FP16 weakness
RX 6900 XT	16GB	ROCm 5.4+	Extreme power
RX 7900 XT	20GB	ROCm 6.0+	RDNA 3
RX 7900 XTX	24GB	ROCm 6.0+	Best consumer

ROCm Installation Complexity

ROCm requires specific driver and library versions:

# Install ROCm on Ubuntu 22.04
sudo apt install rocm-libs rccl amd-opencl

# Verify installation
rocminfo
# Should list available GPUs

# Set GPU visibility
export ROCM_PATH=/opt/rocm
export HSA_OVERRIDE_GFX_VERSION=10.3.0  # For RDNA3 compatibility fix

Performance Comparison: NVIDIA vs AMD

Equivalent tier GPUs comparison:

Task	RTX 4070 12GB	RX 7900 XT 20GB
llama.cpp throughput	100%	85-90%
ROCm supported frameworks	100%	60-70%
Power efficiency	Better	Worse
Software ecosystem	Superior	Adequate

llama.cpp ROCm Build

# Build llama.cpp with ROCm support
make LLAMA_HIPBLAS=1

# Verify ROCm is detected
./llama-bench -m model.gguf -ngl 99
# Should show "Device: AMD Radeon RX..."

Common ROCm Issues

Version mismatch: ROCm 6.0 and ROCm 5.7 have different requirements
Navi driver issues: Some motherboards require PCIe resizing
Memory fragmentation: Different allocation strategy than CUDA
Framework support: Not all inference servers support ROCm