gpt-oss-20b-tq3
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Explore AI models 8
NVIDIA-Nemotron-3.5-Super-VL-120B-A12B-tq3-g64
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View details ↗opendecider-nano
manjunathshiva**Open, calibrated System 1 decision model.** Give it a **state** (text, email, ticket or JSON) and **typed questions** (`choice`, `score`, `noul`); it returns a calibrated probability for every option in a single forward pass: **17 ms on an NVIDIA L40S, 18 ms on an Apple M4 Max, ~9 ms per question batched**. ~400M parameters, Apache-2.0. It never generates text, so there is nothing to parse and nothing to hallucinate. **Ahead of Laya like for like on typed-decisions: 0.796**, against 0.766 for Laya's typed-decisions checkpoint (+0.030, 95% CI +0.014 to +0.044), both fine-tuned on its train split. TypeSafe Jev scores 0.754 there zero-shot (measured through TypeSafe's own API): a reference, not a head-to-head. **Documentation: manjunathshiva.github.io/opendecider**: getting started, choosing a model, guides for serving, LM Studio, Ollama and vLLM and automating the confident decisions, plus the Python and HTTP API reference.
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View details ↗opendecider-small-GGUF
manjunathshivaGGUF builds of OpenDecider-small, the 4B OpenDecider decision model, for **LM Studio**, **Ollama** and anything else built on llama.cpp. Best for decisions it has never seen: the best general accuracy and calibration of the 4B models (zero-shot on typed-decisions). A decision model answers typed questions (`choice`, `score`, yes/no) about any text or JSON with a probability for every option, instead of generating text. The opendecider package builds the exact prompt the model was trained on and reads the option probabilities from the server's token log-probabilities. On typed-decisions (2,000 questions), the Q8_0 build gives the same top answer as the full-precision model on 1,975 (98.8%), at the same accuracy: Measured through Ollama's llama.cpp engine; LM Studio runs the same engine and returned identical log-probabilities on the same file. **Q8_0 is the recommended file**; Q4_K_M is for machines with little memory.
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View details ↗opendecider-small-td-GGUF
manjunathshiva基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗Qwen3.6-35B-A3B-tq3a-tqTe-g64
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View details ↗Qwen3.8-27B-tq3-mini-g64
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View details ↗Qwen3.8-Flash-Next-tq4a-tq2e-g64
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