# Models

`GET /v1/models` lists what this gateway offers, whether each engine answers right now, and what is pinned.

| Name | Checkpoint | Window | State read (short question / 10-20 options) | Notes |
|---|---|---|---|---|
| `jers` | chosen by its language router | | | reads the script and language of the state, then picks English or multilingual; typed-decisions only when named |
| `jers-latest` | alias of `jers` | | | pin a checkpoint name before relying on exact behaviour |
| `jers-english` | ModernBERT-large, 421M parameters | 512 tokens | about 475 / 330 tokens | the most measured here; the engine's authors report 0.78 on MASSIVE intent in English (0.86 on English XNLI) |
| `jers-multilingual` | mmBERT-base, 322M, 100+ languages | 1024 tokens | about 990 / 780 tokens | the engine's authors: +21 points over English on non-English XNLI; Swedish 0.57 against English 0.78 |
| `jers-typed-decisions` | ModernBERT-large fine-tuned on four workflows | 1024 tokens | about 990 / 790 tokens | 0.77 on its own workflows (customer service, invoices, security incidents, agent traces), where the base checkpoints score 0.34 to 0.36 against a 0.46 majority baseline; best for multi-question workflow decisions like those |
| `jers-ft-<tenant>-<date>` | fine-tuned on one tenant's golden cases (`jers_finetune.py`) | as its base | as its base | listed by `GET /v1/models` only for that tenant, with `"fine_tuned": true` and its held-out accuracy; registered only when it beat its base on held-out cases |

Window figures measured on 2026-09-23 with this gateway's engine (see State); accuracy figures are the engine's authors' unless marked. The English checkpoint answers a three-question request in 27 ms of engine time on the hosted RTX 4090 GPU (median of 25, 2026-09-24), and in 71 ms end to end through https://api.getjers.com from a server in Boston (median of 50).

`default`, `auto` and `jers-latest` are aliases of `jers`. An unknown name is a 422 that lists these. Every answer carries `model` (the model name with aliases resolved: `jers-latest`, `default` and `auto` come back as `jers`) and `engine` (the engine's name, the checkpoint that answered, and its metadata), so you always know what produced a number. The engine's authors report that the English checkpoint collapses outside English while staying confident, which is why `jers` routes by language before the engine reads anything: name `jers-english` only for English states.

## Versions

`GET /v1/models` reports the runtime library version and the loaded checkpoints; treat `jers-*` names as "the checkpoint Jers runs today", record `engine` from the answer next to any measurement, and run your golden set (Quality) before and after the engine is upgraded.