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.

model	based on	one card of	reads
spinf/gemma-4-12b-fp8 (default)	Gemma 4 12B, FP8 with static activation scales	24 GB (RTX 4090 / 5090, L4, L40S, RTX 6000 Ada, H100)	text, images, audio, video frames
spinf/gemma-4-31b-fp8	Gemma 4 31B, FP8 static	48 GB (RTX 6000 Ada, L40S, RTX PRO 6000)	text, images, video frames
spinf/qwen3.8-27b-int4	Qwen3.8-27B, GPTQ int4	24 GB	text, images, video frames
spinf/pplx-decider-v1-27b-int4	pplx-decider-v1-27b, GPTQ int4: a decision model with a readout head	24 GB	text, with its own packs

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.