Hy-Nomas
Needs 11 GB at FP8 / INT8. The smallest real configuration today is 1× RTX 3060 at Vast.ai, $0.04 per hour, about $26 a month at 730 hours.
- Per hour
- $0.04
- Per month
- $26
- Cheapest at
Vast.ai
What is documented about Hy-Nomas
news checked 2026-10-27Free-form interactive video world model: segment-autoregressive dual-stream MMDiT (54 blocks) with persistent KV cache, text + camera control, 8 denoising steps. Diffusers files: transformer 17.11 GB BF16 (8.55B params per HF metadata), text encoder 14.14 GB (Qwen2.5-VL-7B language model), PixelUMM decoder 13.94 GB. Original repo 196 GB (FP32 base_ar and distilled DiTs 34.2 GB each, INT8 DiT 9.06 GB, PixelUMM FP8 9.14 GB, LoRAs). WanGP, SGLang and ComfyUI support within a week.
- https://huggingface.co/tencent/Hy-Nomas
- https://huggingface.co/api/models/tencent/Hy-Nomas?blobs=true
- https://huggingface.co/api/models/tencent/Hy-Nomas-Diffusers?blobs=true
How much VRAM it needs
Weights plus 20% runtime overhead. For video models, activations also depend on resolution, clip length and batch size; the per-GPU estimates below give the practical configuration.
| Precision | Weights | Weights + headroom |
|---|---|---|
| BF16published checkpoint | 192 GB | 231 GB |
| FP8 / INT8estimated | 9 GB | 11 GB |
| INT4 / MXFP4estimated | 5 GB | 7 GB |
What it costs to run, GPU by GPU
The fewest GPUs of one type whose total memory fits the model at short context, priced from the cheapest eligible on-demand offer for exactly that count (45-day window, newest reading per provider), with the next providers beside it. Monthly = 730 hours.
| GPU | Smallest config | VRAM used | $ / hour | $ / month | Cheapest at |
|---|---|---|---|---|---|
| RTX 3060Best fit | 1× 12 GB12 GB total | 86% | $0.04 | $26 | |
| RTX A2000 | 1× 12 GB12 GB total | 86% | $0.04 | $26 | |
| T4 | 1× 16 GB16 GB total | 64% | $0.04 | $29 | |
| Tesla P40 | 1× 24 GB24 GB total | 43% | $0.04 | $30 | |
| GTX Titan X | 1× 12 GB12 GB total | 86% | $0.04 | $31 | |
| Titan Xp | 1× 12 GB12 GB total | 86% | $0.04 | $31 | |
| Tesla P100 | 1× 16 GB16 GB total | 64% | $0.04 | $33 | |
| GTX 1080 Ti | 1× 11 GB11 GB total | 93% tight | $0.06 | $45 | |
| RTX A4000 | 1× 16 GB16 GB total | 64% | $0.06 | $46 | |
| Tesla V100 16GB | 1× 16 GB16 GB total | 64% | $0.06 | $46 | |
| RTX 2080 Ti | 1× 11 GB11 GB total | 93% tight | $0.07 | $49 | |
| Tesla V100 32GB | 1× 32 GB32 GB total | 32% | $0.07 | $50 | |
| RTX PRO 2000 | 1× 16 GB16 GB total | 64% | $0.07 | $51 | |
| Tesla M40 | 1× 24 GB24 GB total | 43% | $0.07 | $54 | |
| RTX 3080 Ti | 1× 12 GB12 GB total | 86% | $0.08 | $60 | |
| RTX 4070 | 1× 12 GB12 GB total | 86% | $0.08 | $61 | |
| GTX 1660 | 2× 6 GB12 GB total | 86% | $0.09 | $64 | |
| RTX 5060 Ti | 1× 16 GB16 GB total | 64% | $0.09 | $64 | |
| RTX 3090 | 1× 24 GB24 GB total | 43% | $0.09 | $66 | Akash NetworkTrust 53 · read Nov 1 · receipt · also Vast.ai $0.10, Clore.ai $0.11 |
| RTX 4070 Super | 1× 12 GB12 GB total | 86% | $0.10 | $70 | |
| GTX 1070 | 2× 8 GB16 GB total | 64% | $0.10 | $70 | |
| GTX 1070 Ti | 2× 8 GB16 GB total | 64% | $0.10 | $76 | |
| L4 | 1× 24 GB24 GB total | 43% | $0.10 | $76 | |
| GTX 1080 | 2× 8 GB16 GB total | 64% | $0.11 | $79 | |
| The 24 cheapest of 100 GPU types that fit. Every GPU, any precision and context, in the finder | |||||
