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What this is

A single 16 GB GPU running ComfyUI, shared with a research-paper RAG replica. What that buys you and what it costs.

Updated Aug 9, 2026

The short version

One laptop-class GPU generates 2D game art on demand. You bring it up, generate, and hand the card back. Nothing is sent to a third-party service; there is no per-image charge; the weights are all open and stay on local disk.

The machine

GPUNVIDIA RTX 5080 Laptop, 16 GB VRAM, Blackwell (sm_120)
Power budget~90 W measured under load — roughly half a desktop 5080
Host16-core CPU, 62 GB RAM, ~1.9 TB free, headless Linux
StackComfyUI on Python 3.12 with PyTorch 2.11.0+cu130

That “Laptop” suffix is the single most important line in the table. A laptop 5080 is not a desktop 5080 with a smaller case — it is a different, power-limited part. Measured on this box, a warmed fp16 matrix multiply sustains 36.6 TFLOPS at 91 W with the SM clock sitting at 1290 MHz, against a desktop part’s ~2600 MHz boost.

In practice that is better than it sounds. Measured end to end at 1024² and 20 steps:

TimePeak VRAM
SDXL + pixel-art LoRA8 s7.3 GB
FLUX.2 klein-4B (fp8)16 s8.6 GB

Seconds per image, not fractions of a second — which is fine for batching sprites and tedious for turning a dial and waiting.

It is a shared card, not a dedicated one

The same GPU hosts two always-on services:

ResidentVRAMWhat it is
Papers-RAG replica query API~3.4 GBA read-only copy of the lab’s research-paper corpus
Ollama holding a 4B LLM~3.9 GBPinned resident, answers questions against that corpus

Together they hold ~7.3 GB of the 16 GB, leaving ~8.7 GB if you generate alongside them. That is enough for SDXL and comfortable for SD 1.5, but not enough for the larger models.

So the stack evicts them on demand. comfy-up stops both and hands you the full ~15.3 GB; comfy-down puts them back. See Sharing the GPU for why this is safe and what specifically is not stopped.

What it is good at

  • Sprites, item icons, portraits, and other small-canvas art in a consistent style
  • Batch generation — dozens of variations while you do something else
  • Tilesets and seamless textures
  • Iterating on a look without a per-image bill

What it is not good at

  • Interactive fiddling with the biggest models. At ~90 W, a large model at high resolution is a make-a-coffee operation, not a live dial-turning one.
  • Being an art director. It generates candidates; a human still picks, fixes, and assembles.
  • Perfect text. Legible words inside generated images remain unreliable.
  • Editing. This box generates. Cleanup, palette work, and assembly happen on a desktop machine in Aseprite, Krita, or a tilemap editor — the GPU box is headless and has no GUI.

The honest cost

The electricity is negligible and the models are free. The real cost is your time: prompt iteration, culling bad generations, and hand-fixing the survivors. Treat the output as a fast draftsman, not a finished asset pipeline.

Source: content/start/what-this-is.md · maintained in the nuilab-aigaming repository.