Choosing a model

PRIOR runs one model per container, and you supply the generation model as a GGUF. The file is mounted at runtime, not baked into the image (weights are large and shared). This page covers which models are supported, how to pick one, and the exact command to fetch a recommended quickstart model.

The model registry

PRIOR ships a model registry (baked into the engine) that maps each supported GGUF to its calibrated steering parameters and grades it. The registry spans dense, mixture-of-experts and hybrid-SSM builds up to 31B and grows as models are calibrated, so it is deliberately not enumerated here; the live, machine-readable list is public at eagle-logic.com/models (and at /model-registry.json).

When you mount a GGUF whose filename matches a registry entry, the engine resolves that model's calibration automatically and runs it at its graded tier. Check what resolved:

curl -s http://localhost:8089/admin/model -H "Authorization: Bearer <admin-key>"
# -> model_key, tier: certified | beta

The filename matters. The engine matches the mounted GGUF's name to the registry. Keep the registry filename (e.g. Qwen3-8B-Q4_K_M.gguf); a renamed file or a different quantization falls back to beta defaults rather than the calibrated values.

⚠️ GGUF support is not guaranteed for every model

The gate (policy detection) works on any model you load. Steering is different. It operates on a model's internal geometry, so its quality is model- and architecture-specific and must be validated per model. We grade every model by that validation:

The grade is the honest signal: a certified model steers cleanly, while an unsupported one effectively doesn't (the gate still routes and flags, but forced refusals won't hold). Do not assume an arbitrary GGUF off Hugging Face will steer; start from the certified list below.

Recommended models

Certified picks (4-bit Q4_K_M):

Also certified: Llama-3.2-1B (~0.8 GB) for the smallest footprint, both Mistral-Nemo-12B builds, the Qwen3-Next hybrid class, Phi-4 and Phi-4-mini, Ministral-3, a DeepSeek-R1 14B distill, and both 12B Gemma builds (Gemma-3-12B and Gemma-4-12B). Qwen3-14B, the smaller Gemma-3/4 builds, and SmolLM3 are currently beta for steering; load them for the gate, not for reliable refusals.

Fetch a model (one command)

Use the Hugging Face CLI. The default quickstart (Llama-3.2-3B, ~2 GB):

pip install -U "huggingface_hub[cli]"

huggingface-cli download bartowski/Llama-3.2-3B-Instruct-GGUF \
  Llama-3.2-3B-Instruct-Q4_K_M.gguf --local-dir ./models

Or the more capable Qwen3-8B (~5 GB):

huggingface-cli download Qwen/Qwen3-8B-GGUF \
  Qwen3-8B-Q4_K_M.gguf --local-dir ./models

Repos occasionally move. If a download 404s, search Hugging Face for the model's official GGUF release or a reputable uploader (e.g. bartowski/…-GGUF), and keep the exact filename shown in the recommended table so the registry match holds.

Run it

docker run -d --name prior --gpus all -p 127.0.0.1:8089:8089 \
  -e PRIOR_NATIVE_MODEL=/models/Llama-3.2-3B-Instruct-Q4_K_M.gguf \
  -v "$(pwd)/models:/models:ro" \
  -v "$(pwd)/license.bin:/app/license.bin:ro" \
  ghcr.io/eagle-logic/prior:slim

Then confirm the registry resolved it as certified (GET /admin/model above), and you're done. See Getting Started for the first requests.

Help grow the registry

Bringing a model that isn't certified yet? Calibrate it in the WebUI (Configuration → Steering model → Auto-calibrate). If you opt in, Share calibration sends the result (a small, non-PII payload: the model name and its calibrated steering parameters) to Eagle Logic. After we verify it, the model joins the certified registry for everyone. See the WebUI Operator Guide.