Amos 1 large

A 27B decision model. Give it a case (text, JSON or a photo) and a schema of typed questions; it answers every question in one forward pass, each with a probability for every answer you allow. It writes no text, so there is nothing to parse and no malformed output. Our most capable model, for the hardest calls: questions that take several steps, long policies and trade-offs, and cases that need broad knowledge.

Part of the Amos 1 family: large · medium · small · mini. Playground · API docs · Model page

Results

Typed decisions, test split: 2,000 decisions from four workflows it never trained on, zero-shot.

Rivals run by us on the same 2,000 decisions, except Decider 1, whose number is its makers' own.

With each question's priors fitted on the benchmark's own train split and applied at answer time (the weights do not change), as Decider 1 also reports: 80.25% (Decider 1: 80.1%).

Decision Bench, all 1,071 real records, images included, run with the benchmark's own harness: 94.9%. The leaderboard lists Perplexity Decider v1.1 at 94.5%, DeepSeek V4.1 Flash and Gemini 3.5 Flash at 94.2%, Jev 1.13 at 93.8%.

Decision Index 0.3, public part, with the board's own kit: 65.11. By area: knowledge 52.6, language 72.3, retrieval 66.2, tools 79.7, arts 50.0. The board's ranking adds private tests that only its maintainers run.

Use

Hosted, no key: POST https://api.amos.scira.ai/v1/systemone with "model": "amos-1-large".

Or run it yourself. The serving package is in serve/ (Python 3.12, PyTorch 2.14; versions pinned to the ones these numbers were measured with):

hf download mukaddamzaid/amos-1-large --local-dir amos-1-large
pip install ./amos-1-large/serve
python -m amos.serve amos-1-large --device cuda --port 8000 --max-len 131072
curl http://127.0.0.1:8000/v1/systemone -H 'Content-Type: application/json' -d '{
  "state": "Invoice INV-2231 for £306.00 was charged to my card twice. Please refund one.",
  "questions": {
    "refund": {"type": "noul", "instructions": "Is the customer asking for a refund?"},
    "team": {"type": "choice", "instructions": "Which team should handle this?",
             "criteria": {"billing": null, "technical": null, "sales": null}}
  }
}'

Question types: yes/no (noul), pick one (choice, up to 255 options), rate (score), pick any (multi), quote (span) and point (region, with a photo in images). It runs on an 80 GB GPU and reads up to 131,072 tokens per request.

Limits

• The slowest of the four.
• Long quotes, such as a whole clause or address, can come back cut short.
• English only.