Images are for reference only. Refer to the linked store for actual product images.A 24-core Core Ultra 7 system with 64 GB DDR5 and a 16 GB GeForce card. This CPU can draw substantially more power under sustained workloads; review cooling and board limits. 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 creator-focused Intel platform with a Core Ultra 7 270K Plus, 64 GB RAM and RTX 5070 Ti. The list is a starting point for software-specific validation, not a certified workstation.
The CPU and Z890 board provide the processor platform; the 16 GB GPU should be checked against the actual renderer, editor and codec requirements.
The two-module 64 GB kit raises system-memory capacity independently of graphics memory. The 2 TB SSD remains a single storage device, so plan project, cache and backup capacity explicitly.
The NAUTILUS 360 RS and H7 Flow introduce a radiator, pump and fan-control layout. The RM1000e selection does not remove the need to check exact power connections.
Measure a representative project before deciding between more RAM, graphics memory, CPU capacity or an additional scratch drive. Document the software version and workload so an upgrade can be evaluated against the same task.
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.