Images are for reference only. Refer to the linked store for actual product images.A 16-core workstation starting point with 64 GB RAM, a 4 TB SSD and 16 GB GeForce graphics. Choose memory capacity and GPU software support for your actual production applications. This USD budget is an illustrative planning target, not a verified parts total or a retailer quote. Check current local prices, BIOS support and mounting clearances. Images are for reference only. Refer to the linked store for actual product images.
Explore cloud use, local language models and image generation with the parts you selected. Memory estimates are not speed benchmarks.
A larger local GPU is not required just to chat with a cloud model or request cloud-generated images. Check the service account, availability in your region, internet connection and supported browser or client.
Local editing, 3D work and running several apps still use your PC’s resources. This does not guarantee a service’s response time.
How cloud inference worksCheck the exact GPU, driver and CUDA support in your chosen application.
Image size, batch size, model components and extra nodes change memory use. CPU offloading can reduce VRAM demand but may be slow. Video generation, training and fine-tuning require separate assessments.
ComfyUI hardware requirementsModel memory and offloadingChange the assumptions to explore the memory tradeoff. These are model sizes, not recommendations for a specific model.
Theoretical weight storage only: 3.7 GiB · 8B / 4-bit
Actual use is higher: quantization metadata, unquantized tensors, KV cache, compute buffers and the runtime also need memory. Total installed memory is not the same as free memory.
| Parameters | Weight lower bound | Compared with selected VRAM |
|---|---|---|
| 3B | 1.4 GiB | Weights only; overhead not included |
| 8B | 3.7 GiB | Weights only; overhead not included |
| 14B | 6.5 GiB | Weights only; overhead not included |
| 32B | 14.9 GiB | Weights only; overhead not included |
| 70B | 32.6 GiB | Not enough for weights alone |
Weight lower bound = total parameters × bits ÷ 8. B means one billion parameters; GiB means 2³⁰ bytes. All parameters are counted, including inactive experts in a mixture-of-experts model. Nominal catalog RAM and VRAM capacities are used as GiB for this planning comparison.
Shared system memory is not added to dedicated VRAM. RAM kit capacity is counted once. Already-owned parts still count as installed hardware. No throughput or “smooth performance” claim is made.
After assembly, use the actual model file and context setting with the runtime’s resource estimator, then measure response speed and memory use in your workload.
LM Studio resource estimationWeight estimates · Context and memory · GPU runtime support · Application requirements
Selected GPU manufacturer specifications · 2026-09-10
AI documentation checked: 2026-09-19A 16-core Ryzen 9 9950X parts list with 64 GB system memory and an RTX 5080 for evaluating substantial CPU and GPU creative workloads.
The CPU's core count is a capacity choice for workloads that can use it; it is not proof that every editor or export is faster. The 16 GB GPU has its own software and memory requirements.
The 4 TB 990 PRO expands local storage while the 64 GB DDR5 kit expands working memory. Keep project size, caches and a separate backup plan visible in the decision.
The X870 board, 360 mm NAUTILUS and H7 Flow create a full-size liquid-cooled installation whose exact mounting and fan control should be planned before assembly.
Use a representative project to identify whether CPU time, GPU work, RAM or storage is limiting you. Avoid moving to a more expensive CPU if the actual task is limited by GPU memory or project storage.
This is an editorial parts-list explanation. The planning target is not a current retailer total, and this configuration has not been benchmarked by RigAtlas.