spinf

Decision models: one input read once, hundreds of questions answered as probabilities.

spinf turns open models into decision models. Instead of generating text, the model scores: a piece of content is read once and every question about it is answered in the same pass with a calibrated, batch-invariant probability. The checkpoints here are the ones spinf-serve, our open-source inference engine, serves: quantized and calibrated by us, with the quantization parameters travelling with the weights, so the same model gives the same score on your GPU and on the hosted API at spinf.com.

pip install "spinf-serve[server]"
spinf-serve serve spinf/gemma-4-12b-fp8     # downloads the checkpoint on first start; an OpenAI-compatible server on port 8000
# or the image: docker run --gpus all -p 8000:8000 -v spinf-cache:/root/.cache ghcr.io/spinfinc/spinf-serve

• spinf-serve: the engine and server (Apache 2.0), the quantization recipes that produced these checkpoints, the parity fixture, the docs.
• spinf-prompts: ready-made, calibrated question sets (content moderation, triage, products, reviews, brand, entertainment) the server preloads; community packs load from any repository, such as thinkingtext's news packs.
• spinf-client: the Python client, for your own server or the hosted API.
• Agent skills for Claude Code and other coding agents.

Each model card carries its recipe and licence: Gemma 4 under Google's terms, Qwen3.8 and pplx-decider under theirs, the quantization and calibration under Apache 2.0.