# Is Chitra Tiny SOTA?

Pending benchmarks. Announced Oct 12, 2026; no independent results yet.

As of Nov 3, 2026, Chitra Tiny is pending benchmarks on isitsota: announced Oct 12, 2026, with no independent results on the boards we track yet.

Udgam Labs' 212M-parameter English text-to-image model that makes 256×256 pictures from a sentence. The diffusion transformer was trained from scratch on about 4.7 million public-domain and CC0 images; it uses Flan-T5-Base and Stability AI's sd-vae-ft-mse unchanged. Apache-2.0.

Canonical: https://isitsota.com/m/chitra-tiny
Last updated: 2026-10-24
Tracking since: 2026-10-24

## Announced facts

| Fact | Value |
| --- | --- |
| Lab | Udgam Labs |
| Announced | Oct 12, 2026 |
| API | Not yet |
| Open weights | Published · Hugging Face (udgamlabs/Chitra-Tiny, about 0.85 GB) and code on GitHub (udgamlabs/chitra-tiny) |
| Parameters | 212M (diffusion transformer, 16 layers, width 768) |
| Method | Latent rectified-flow diffusion transformer with classifier-free guidance; 50 steps by default |
| Training | Transformer trained from scratch (random weights) on about 4.7 million public-domain and CC0 images with automatically generated captions |
| Frozen components | google/flan-t5-base text encoder (Apache-2.0) and stabilityai/sd-vae-ft-mse decoder (MIT), used unchanged |
| Output | 256×256 images from English prompts; no built-in safety filter |
| License | Apache-2.0 (weights and code) |

Tags marked unsure are not stated on the lab's own pages.

## What would let us call it

Verdicts use only independent boards we already track. Two consecutive snapshots are required before any crown.

- [x] Publicly announced with a source
- [x] Usable by the public (API or weights)
- [ ] Listed on an independent board we track
- [ ] Enough results for a rank in a category
- [ ] Holds across two snapshots (crowns only)

## What the lab claims

Self-reported. Shown for context; not used in any verdict.

- Lab claim: GenEval overall 0.219 with the official code, against 0.426 for Stable Diffusion 1.5 in the same harness.
- Lab claim: FID 22.1 on 5,000 held-out images like its training data and CLIP score 26.2 (real held-out images: 27.5); Udgam notes both favour the model.
- Lab claim: about three seconds per image on an Apple-silicon Mac.

## Sources

- LAB: [Chitra Tiny, a 212M-parameter text-to-image model trained from scratch (Udgam Labs blog)](https://udgamlabs.com/blog/chitra-tiny) (2026-10-12)
- LAB: [Chitra Tiny model page (Udgam Labs)](https://udgamlabs.com/models/chitra-tiny) (2026-10-12)
- REPO: [udgamlabs/Chitra-Tiny model card (Hugging Face)](https://huggingface.co/udgamlabs/Chitra-Tiny)
- REPO: [udgamlabs/chitra-tiny (GitHub)](https://github.com/udgamlabs/chitra-tiny)

Tracking continues until an independent board lists it.

## Related

- Lab: [Udgam Labs](https://isitsota.com/labs/udgam-labs.md)
- All pending releases: https://isitsota.com/releases.md
- JSON: https://api.isitsota.com/v1/models/chitra-tiny