GPU memory and RAM
GPU memory usually limits model size; RAM supports apps, data, and model offload.
Component overview
Patriot Viper Venom 64GB (2x32GB) DDR5-6000 CL30 AMD EXPO
Patriot memory kit
CategoryMemory kits
Technical specifications
PVV564G600C30K
64GB (2x32GB)
DDR5
6000 MT/s
CL30-40-40-76
AMD EXPO, Intel XMP 3.0
1.35V
No
No
AM5; starts at JEDEC DDR5-4800 and enables DDR5-6000 only after BIOS/profile validation
70B-class target requires validation
Selected 70B-class Q4 models need high VRAM or Apple unified memory, short-to-moderate context, and runtime validation.
70B-class fit is still context and runtime sensitive; validate the exact model, quantization, backend, and prompt length before relying on it.
AI terms in plain language
CUDA
NVIDIA’s software layer for many AI tools. Macs and AMD GPUs do not run CUDA workflows the same way.
Apple unified memory
Memory shared by the CPU, GPU, macOS, and apps; it is not the same as NVIDIA VRAM.
7B / 8B / 14B / 70B
Approximate model size in billions of parameters; larger models usually need more memory.
Quantized models
Lower-precision models, such as Q4, that use less memory with possible quality or speed tradeoffs.
Context length
How much text the model can keep in mind at once. Longer context uses more memory.
Inference
Running an existing model for chat, coding help, summaries, or document workflows.
Fine-tuning vs adapter tuning
LoRA and QLoRA train small adapters and need fewer resources than full fine-tuning.
Throughput (tokens/s)
Model output speed. Compare the same model, quantization, context, runtime, and user count; prompt processing is a separate measurement.
Price estimate history
Uses market prices where available and reference estimates otherwise.
Low€812High€812Avg€8127 data points
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Pricing and purchase
€980
Estimated total. Final price confirmed before ordering.
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Returns, warranty, and support
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