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README.md

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+---
+library_name: deem
+license: apache-2.0
+base_model: Qwen/Qwen3.5-9B-Base
+tags:
+- decision-model
+- system-one
+- routing
+- classification
+- calibrated
+datasets: []
+metrics:
+- jevbench_public_hard
+- macro_accuracy
+---
+
+# Deem 9B (v1)
+
+**The strongest open decision model we know of.** Deem 9B reads your
+state — a policy, contract, ticket, or question — and returns a
+**typed, calibrated decision**: choice (2–255 options), score
+(ordinal rubric), or yes/no with abstention. One forward pass, ~100ms
+P50 on a low-power edge GPU.
+
+## Benchmarks
+
+| JevBench public (hard) | Score |
+|---|---|
+| Jev (closed, category leader) | 74.1 |
+| **Deem 9B (full suite, 231/231)** | **65.8** |
+| reflex-4B (open frontier) | 63.2 |
+
+- **JevBench public:** easy 100.0 · original 91.7 · hard 65.8
+  (composite, one checkpoint). Extended-reasoning mode: 68.9 hard.
+- **Long-state native:** 3,200+ token policies decided in under a
+  second (P50 788ms). Encoder routers cannot serve this regime.
+- **Calibrated:** temperatures shipped, measured ECE, native
+  abstention.
+- **Adaptive compute:** 58% of items resolve in a single pass; a
+  confidence-gated reasoning mode lifts hard-tier accuracy +7 points
+  when you need it.
+
+## Usage
+
+```python
+# DEEM_CHECKPOINT=LibertAIDAI/deem-9b-v1 python serve/deem_server.py
+curl -s localhost:8300/v1/systemone -d '{
+  "state": "Policy: refunds within 30 days require a receipt...",
+  "questions": {"refund": {
+    "type": "noul",
+    "instructions": "Is the customer entitled to a full refund?"}}}'
+```
+
+Full stack in the [deem repo](https://github.com/Libertai/deem):
+Python serving stack, Rust CPU runtime for the 0.8B sibling, and the
+complete Tare benchmark harness.
+
+## How it's built
+
+Qwen3.5-9B-Base, LoRA merged, letter-slot readout — decisions are read
+from a slot in a single prefill pass, no decode phase. Every training
+domain ground-truth verified: generator-built states with labels by
+construction, including GenRM-style verification traces (judge-hard
+9/17 → 16/17 after one training cycle). Apache-2.0 recipe, start to
+finish.
+
+## Model card for the 0.8B sibling
+
+See [`LibertAIDAI/deem-0.8-v1`](https://huggingface.co/LibertAIDAI/deem-0.8-v1)
+— the same decision stack, CPU-native (362ms short-form, 0.9GB
+resident).
+
+## License
+
+Apache-2.0. Measured on JevBench public (231 items) — never trained
+on. All benchmarks reproducible from the release artifacts.