Running H3 on 8-12GB VRAM: Practical Low-End Setups

Updated 2026-09 · Includes real timings on 8GB cards and a list of pitfalls to avoid

Running H3 on low VRAM is entirely feasible, but you need a combination play: a smaller quantization + the right launch flags + enough virtual memory, with resolution kept in the 540p tier. Below is the checklist broken down by VRAM tier.

Choosing an approach: how to pick among three quantizations

Approach	Main model size	Suitable for	Notes
GGUF Q3_K_M (pruned)	8.9 GB	8–10GB VRAM	Smallest footprint; some quality loss, slower than INT8
Pruned INT8 ConvRot	19.5 GB	12GB+ VRAM	Official recommendation; with dynamic offloading it's been measured working on 12GB
W4A8 ConvRot (pruned)	12.5 GB	12GB+ VRAM / ComfyUI ≥0.31	4-bit weights with INT8 compute, weight error ~0.073, quality close to INT8

The text encoder also needs a small option: NVFP4 AWQ (14.6GB) suits most machines (not limited to Blackwell); with especially little memory (16GB) you can switch the encoder to GGUF Q2 (13.1GB) and pair it with --fast-disk.

Launch flags (mandatory on low VRAM)

python main.py --fast-disk --disable-mmap --use-sage-attention

--fast-disk: puts weights in page cache, where the system can reclaim them, cutting memory usage sharply (measured: from the ~45GB range down to the ~13GB range);
--disable-mmap: required on Windows to read model files over 20GB, otherwise it may crash;
--use-sage-attention: 1.3–2× faster sampling (watch for noise risk on long sequences, see below);
--lowvram: add this as well at 8GB VRAM.

Pagefile and memory

The 16GB RAM + 8GB VRAM combination is a case where a large pagefile is mandatory: set virtual memory to 48GB or more, on an NVMe SSD. That way the system can lean on disk when both VRAM and RAM are tight — the cost is speed, but it still produces output. Users with 32GB RAM and a 12GB card can run without a pagefile, but must accept weights being read back from the SSD frequently.

The resolution ladder: from drafts to final renders

Draft tier: 540p (736×416 / 832×480), 4-step acceleration — check composition and motion;
Confirmation tier: 640p class (960×544), 4–8 steps;
Final tier: 768p (1344×768), 8 steps — on low-VRAM cards, reserve this for the final render; don't use it for repeated drafts.

Real timing reference

Configuration	Resolution / duration	Settings	Time
8GB VRAM + 16GB RAM + 46GB pagefile	736×416 / 5 s	4-step distilled + Sage	~5–6.5 minutes
8GB VRAM + 16GB RAM	736×416 / 10 s	4 steps + text encoder acceleration	~13 minutes
8GB VRAM + 16GB RAM	736×416 / 15 s	—	Essentially unusable (give up)
12GB VRAM + 32GB RAM	1280×736 / 5 s	720p accelerated, 4 steps	~7 minutes

Pitfall: 15-second durations are a hard wall for 8–12GB cards — the token growth from longer duration makes render time balloon non-linearly. The right strategy for low-end machines is "short clips + stitching afterward", not forcing a single long clip.

To find out which tier your specific configuration can reach, just click a few options in the calculator; to find the corresponding quantization files, go to the "Quantized / low VRAM" category in the model library.

Related pages: H3 on RTX 4060 8GB · H3 on RTX 3060 12GB · GGUF Q3 — compatible GPUs · GGUF Q2 — compatible GPUs · W4A8 — compatible GPUs