# Is Laghu SOTA?

Pending benchmarks. Announced Oct 22, 2026; no independent results yet.

As of Nov 3, 2026, Laghu is pending benchmarks on isitsota: announced Oct 22, 2026, with no independent results on the boards we track yet.

Udgam Labs' 152M-parameter English chat model with a thinking on/off switch, trained from scratch with a $146 main pretraining run and released fully open: weights, late checkpoints, fine-tuning data, evaluation outputs and code. The 163 MB model runs in the browser. Apache-2.0.

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

## Announced facts

| Fact | Value |
| --- | --- |
| Lab | Udgam Labs |
| Announced | Oct 22, 2026 |
| API | Not yet |
| Open weights | Published |
| Parameters | 152M (151.8M; 28 layers, width 640) |
| Architecture | Gemma 4 text architecture: 10 query and 2 key-value heads; three 512-token sliding-window layers then one global layer, repeated |
| Training | Trained from scratch with Udgam's own 32,768-token tokenizer: about 70B tokens read in pretraining at 2K, a 1B-token stretch at 32K, then fine-tuning on 41,467 conversations |
| Cost | Main pretraining run $146.26 (8× A100 80GB, 13.2 hours); about $194 for the whole project |
| Context | 16K tokens for use (stretched at 32K; recall fails beyond about 16K) |
| Modes | Thinking on or off; Udgam recommends off except for short arithmetic |
| Release | Laghu, Laghu-Base, Laghu-Base-32K, Laghu-Checkpoints (late training states only; earlier checkpoints were lost), GGUF and MLX builds, the laghu-sft and laghu-evals datasets, and code on GitHub (udgamlabs/laghu) |
| License | Apache-2.0 for weights and code; nanochat-derived files keep their MIT notice |

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: level with SmolLM2-135M-Instruct on judged chat quality (51.0% win rate) and multi-turn follow-ups (41.7% vs 37.5%); behind Falcon-H1-Tiny-90M-Instruct on all three of Udgam's pre-registered chat tests, so it missed Udgam's own release bar.
- Lab claim: GSM8K 7.9% with thinking on, IFEval prompt-level strict 26.1.
- Lab claim: Laghu-Base scores 0.919 bits per byte on text published in September–October 2026, against 0.941 for SmolLM2-135M and 0.979 for Falcon-H1-Tiny-90M-Base.

## Sources

- LAB: [Laghu release post (Udgam Labs blog)](https://udgamlabs.com/blog/laghu) (2026-10-22)
- LAB: [Laghu model page (Udgam Labs)](https://udgamlabs.com/models/laghu) (2026-10-22)
- REPO: [udgamlabs/Laghu model card (Hugging Face)](https://huggingface.co/udgamlabs/Laghu)
- REPO: [udgamlabs/laghu (GitHub)](https://github.com/udgamlabs/laghu)
- LAB: [Udgam Labs on X](https://x.com/udgamlabs/status/2113272462062637075) (2026-10-22)

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/laghu