Decision-1.0-Eos-0.8B
Eos — the dawn of a clearer decision.
Open Decision Foundation Models
Turn context into choices, judgments, and scores. Eos reads your questions and candidate descriptions, then returns structured answers with probability distributions. Ask many questions about one context, or apply the same questions across a batch of contexts.
Decision collection · Architecture · Evaluation
Measured decisions
61.89 overall — ahead of all four reference models on the same 54-task benchmark.
| Model | Overall ↑ | Decisions | Composition | Reading | Inference | Transfer |
|---|---|---|---|---|---|---|
| Eos · 0.8B | 61.89 | 65.94 | 46.04 | 70.31 | 81.67 | 52.01 |
| Kev · 0.8B | 58.28 | 60.14 | 42.29 | 67.81 | 68.75 | 61.19 |
| Qwen3.5 · 2B¹ | 57.24 | 57.12 | 39.00 | 73.75 | 72.29 | 56.31 |
| Laya English | 51.03 | 56.54 | 35.33 | 51.41 | 63.75 | 53.06 |
| Laya Multilingual | 47.19 | 47.25 | 38.92 | 50.78 | 57.29 | 47.13 |
3,766 scored questions; fixed task weights and the same requests for every model. Overall weights are 30% / 25% / 15% / 15% / 15%. Both Laya references use their released general weights. ¹Qwen uses the benchmark's fixed decision-letter readout. This is an observed regression benchmark; overall leadership does not imply a win on every task. Full 54-task matrix, intervals, and method.
Your questions define the task
| Decision | What you receive |
|---|---|
| Choice | A distribution over your named actions or categories. |
| Noul | The probability that a condition is true. |
| Score | A distribution over ordered levels and the expected score. |
Use the System One request format: state / model / questions → answers. Candidate descriptions are supplied at runtime. Multiple questions can share a context, and the same questions can be applied to several contexts.
Download and run
Download the complete repository so the backbone, decision head, tokenizer, and configuration files stay together:
hf download llm-semantic-router/Decision-1.0-Eos-0.8B --local-dir Decision-1.0-Eos-0.8B
Serve this checkpoint with the vLLM Semantic Router Decision runtime. This repository contains model artifacts and documentation, with no bundled inference code or service. The root config.json describes the Decision artifact layout; it is not a Transformers AutoModel configuration. The calibrated temperature is recorded in config.json.
Once a compatible endpoint is serving Eos, make a decision with:
DECISION_BASE_URL=http://127.0.0.1:8000
curl -X POST "$DECISION_BASE_URL/v1/systemone" \
-H 'Content-Type: application/json' \
--data '{
"model": "Decision-1.0-Eos-0.8B",
"state": "The parcel arrived damaged. Please send a replacement today.",
"questions": {
"route": {
"type": "choice",
"instructions": "Which team should handle this request?",
"criteria": {
"delivery": "Damaged or missing parcels",
"billing": "Payments and invoices"
}
}
}
}'
Built to decide
A 24-layer hybrid decoder combines gated linear attention and full attention. A shared decision head reads candidate endpoints against a global query representation and scores all candidates in one forward pass per question batch.
The released inference model contains the text backbone and decision head. See the architecture and readout diagrams for the computation graph.
Built on Qwen3.5-0.8B. English and Chinese are represented in the release evaluation. Transfer, candidate-carried evidence, and some rule tasks remain areas for improvement; probabilities can be overconfident. The maximum complete input is 16,384 tokenizer tokens; this capacity does not establish long-context reasoning quality.