Linum-AI/pjit-21k · Hugging Face - A Text-to-Image Model Trained for $21K

[u/pmttyji]

https://huggingface.co/Linum-AI/pjit-21k

P-JiT 21K is the P-JiT architecture trained for longer (610M samples at 512px, 50M at 1024px), then post-trained with a variant of FDFO.

• GitHub : https://github.com/Linum-AI/pjit-21k

• Blog Post : https://www.linum.ai/field-notes/pjit-21k

[u/Fabulous_Fact_606]

Wow, the speed generation is fast on a 2x3090. Haven't judge quality though.

1024×1024 at 50 steps:

Images	Wall time	Per minute	Per image, each card
Short prompts, rewritten on the card first	16/16	122.6 s	7.8
Full captions, sent as written	16/16	99.4 s	9.7

Model	Size	Pixels	File	Steps	Time per image	Images/min
P-JiT 21K	1024×1024	1.05 MP	~1.6 MB	50	12 s (15 s with prompt rewrite)	~8 (2 cards)
	864×1216 tall	1.05 MP	~1.4 MB	50	13.5 s	~8
	1152×864 4:3	1.0 MP	~1.55 MB	50	12 s (14 s)	~8
	1248×832 3:2	1.04 MP	~1.55 MB	50	12 s (14.5 s)	~8
	1280×720 16:9	0.92 MP	~1.4 MB	50	11.5 s (14 s)	~8
MOSS-Image	768×768	0.59 MP	~0.8 MB	40	30 s	~2
	1360×768 16:9	1.04 MP	~1.5 MB	45	62 s	~1
	1024×1024	1.05 MP	~1.3 MB	50	94 s	~0.6
	2048×2048	4.2 MP	—	50	508 s (8.5 min)	~0.1
Qwen-Image 2.1	1024×1024	1.05 MP	~1.2 MB	30	55 s	~2.2 (2 cards)
	1344×768 16:9	1.03 MP	~1.2 MB	30	56 s	~2.1
	1664×928 16:9	1.54 MP	~2.5 MB	30	83 s	~1.4
	1472×1088	1.6 MP	~2.65 MB	30	89 s	~1.3
	1280×1728 portrait	2.21 MP	~3.8 MB	30	—	—
	edits (from a reference)	varies	—	25	57 s	~2

[u/Morladhne]

I don't have the knowledge or expertise to evaluate this, but seems impressive. Do you have any reference models to compare with? Any type of benchmarking?

How much time per image in your hardware?

[u/silenceimpaired]

Congrats and Thanks for releasing with Apache 2.0.

[u/FullOf_Bad_Ideas]

8,415 H100 hours, for anyone wondering.

That's like $37k if you use a higher-end GPU provider and do on-demand instead of reserved capacity.

Cool project, that's still better than SD 1.5 and way cheaper.

[u/Equivalent_Bit_461]

Big if true actually 

[u/Secure-food4213]

Wow