OpenDecider
Open, calibrated System One decision models: typed choice/score/yes-no answers. 400M to 80B · PyTorch, MLX, GGUF, ONNX, vLLM · pip install opendecider
Zero-Shot Classification • 0.4B • Updated • 6.23k • 8Note Start here · ~400M, 17 ms per question on a GPU, also fast on CPU · typed-decisions 0.796 (Laya-td 0.766, both fine-tuned) · pip install opendecider
manjunathshiva/opendecider-nano-ONNX
Zero-Shot Classification • Updated • 1Note opendecider-nano in the browser (WebGPU or WebAssembly), Node, Bun and Deno · 8-bit (450 MiB) and fp16 ONNX · 47 ms per question on WebGPU, 40 at once in 1.1 s with fp16 · same answer as PyTorch on 99.5%+ · npm install @opendecider/web
OpenDecider demo
🎯Typed decisions with calibrated probabilities, ~400M model
Note Try it in your browser, no install
manjunathshiva/opendecider-small
Zero-Shot Classification • Updated • 200 • 1Note 4B LoRA on Qwen3-4B for decisions it has never seen: 0.735 zero-shot on general decisions (Jev 0.730), ECE 0.087 · fits a 16 GB Mac
manjunathshiva/opendecider-small-td
Zero-Shot Classification • Updated • 121 • 1Note 4B tuned for business workflows (support, invoices, security alerts, agent traces) · typed-decisions 0.792
manjunathshiva/opendecider-medium-td
Zero-Shot Classification • Updated • 68Note 30B MoE, 3B active · most accurate self-hostable model on general decisions (0.765) · typed-decisions 0.788 · NVIDIA, multi-GPU
manjunathshiva/opendecider-large-td
Zero-Shot Classification • Updated • 43Note 80B MoE, 3B active · best calibration (ECE 0.083) · typed-decisions 0.801 · NVIDIA, multi-GPU
manjunathshiva/opendecider-small-GGUF
Zero-Shot Classification • 4B • Updated • 390Note opendecider-small for LM Studio, Ollama and llama.cpp · Q8_0 gives the full-precision top answer on 98.8% of typed-decisions · Q4_K_M for small machines
manjunathshiva/opendecider-small-td-GGUF
Zero-Shot Classification • 4B • Updated • 398 • 2Note opendecider-small-td for LM Studio, Ollama and llama.cpp · Q8_0 agrees with full precision on 98.6%
manjunathshiva/opendecider-small-mlx-8bit
Zero-Shot Classification • 4B • Updated • 103Note Apple Silicon (MLX) · 4.5 GB · same answer as full precision on 1,955 of 2,000 · 66 ms per question
manjunathshiva/opendecider-small-mlx-4bit
Zero-Shot Classification • 4B • Updated • 83 • 1Note Apple Silicon with little memory · 2.6 GB · typed-decisions 0.651
LocalLLaMA/typed-decisions
Viewer • Updated • 3.2k • 30.7k • 116Note The typed-decisions benchmark: nano and the -td models were fine-tuned on its train split only; the test split was never seen