Images are for reference only. Refer to the linked store for actual product images.A micro-ATX starting point built around an LGA1700 processor and DDR4 memory. The compact enclosure needs its own clearance checks. 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 worksAMD support varies by GPU, operating system and runtime. Check that application’s current ROCm or Vulkan matrix.
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 | Not enough for weights alone |
| 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 · 2026-09-09
AI documentation checked: 2026-09-19A micro-ATX LGA1700 configuration with an RX 7600, useful for comparing a compact DDR4 build and potentially reused older-platform parts.
The Core i5-12400F needs a discrete graphics card for output. The PRIME B660M-A D4 requires DDR4, so the 32 GB LPX kit is part of that platform choice.
The RX 7600 8 GB is an exact graphics selection rather than a guarantee for all games at a particular resolution. The 1 TB 980 PRO provides one initial storage device.
The AK400 and Q300L use air cooling in a smaller enclosure. Check the actual board, GPU, PSU and cable layout together before assuming the listed limits settle the fit.
When starting from scratch, compare the total with a newer platform. If reusing the board or RAM, include those savings, then verify whether a targeted GPU or storage upgrade actually meets the intended 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.