← Back to GPUs
AMD · Radeon PRO
AMD Radeon PRO W7900
$3600$3999 MSRP
The AMD Radeon PRO W7900 offers 48GB of GDDR6 ECC memory at significantly lower cost than NVIDIA's equivalent RTX 6000 Ada. For workloads that run on ROCm (AMD's CUDA alternative), it provides excellent value. However, the AI software ecosystem heavily favors NVIDIA's CUDA, so compatibility should be verified before purchasing. Best suited for OpenCL workloads, professional visualization, and ROCm-compatible AI frameworks.
Best ForBudget 48GB workstation builds and ROCm-compatible AI workloads
VerdictHalf the price of NVIDIA's 48GB card — but verify your AI stack supports ROCm first.
AI
6/10
Gaming
4/10
Specifications
VRAM48GB GDDR6 ECC
Memory Bandwidth864 GB/s
Stream Processors6,144
Boost Clock2500 MHz
TDP295W
Power Connector2x 8-pin
Length267mm
Form FactorDual Slot
Release Year2023
AI Capabilities
Unrivaled48GB VRAM
Run 70B+ models, no compromises. The AI power user's dream.
No CUDA — most AI frameworks run best on NVIDIA. ROCm support is improving but not all models/tools work.
Can run (Q4 quantized)
Llama 3.1 70BLlama 3.1 8BQwen 2.5 72BQwen 2.5 32BQwen 2.5 14BMistral 7BDeepSeek R1 70BFLUX.1 DevStable Diffusion XLStable Diffusion 3.5 LargeHunyuanVideoCogVideoX-5BMochi 1LTX VideoStable Video DiffusionWan Video 14BCodestral 22BQwen 2.5 Coder 32BLLaVA 1.6 34BAlphaFold 2ESMFold (ESM-2 15B)ESM-2 3BscGPTRFdiffusionFine-tune Llama 8BFine-tune Llama 70BTrain SDXL LoRATrain FLUX LoRA
Recommended system RAM for AI: 96GB+ (2x GPU VRAM for model overflow)
Performance Estimates
Estimated tokens/sec for LLM inference based on 864 GB/s memory bandwidth — not hardware benchmarks. Methodology · What is Q4/Q8?
Llama 3.1 70B70B
Q4~9-11 tok/sSlowLlama 3.1 8B8B
FP16~21-26 tok/sUsableQwen 2.5 72B72B
Q4~9-11 tok/sSlowQwen 2.5 32B32B
Q8~11-13 tok/sSlowQwen 2.5 14B14B
FP16~12-15 tok/sSlowMistral 7B7B
FP16~24-29 tok/sUsableDeepSeek R1 70B70B
Q4~9-11 tok/sSlowCodestral 22B22B
FP16~8-9 tok/sSlowQwen 2.5 Coder 32B32B
Q8~11-13 tok/sSlowPros
- +48GB VRAM at lower cost than NVIDIA pro cards
- +Good for ROCm-supported workloads
- +Blower cooler for multi-GPU
Cons
- -No CUDA — limited AI framework support
- -ROCm still maturing
- -Not for gaming
aiworkstation