FLock.io's typed-decision model, fine-tuned from Mapika's decider-2b. Reads one hidden state per question and scores the declared options, so an answer outside the list cannot occur; several questions about one state share a forward pass.
Juspay's open decision model. Qwen3.6-35B-A3B with a merged rank-16 LoRA, shipped with a pinned SGLang serving bundle that answers Choice, Score and Noul questions over text, images or a video through a TypeSafe-compatible /v1/systemone API.
Figures are from each model’s manifest; accuracy and latency are what the publishers report, on their own suites and hardware. Add a third model.
Questions
What is the difference between this-that-model and xor?
this-that-model is from FLock.io and xor from Juspay. Both have open weights you can download and run. Both answer choice, score and noul questions. Only xor answers classify and route. this-that-model is the smaller model, at 1.9B parameters to 35B. this-that-model is licensed mit; xor, apache-2.0.
Which is more accurate, this-that-model or xor?
They report on different suites — this-that-model 87.8% on limberc/this-that-complex-decisions (1,710 questions, FLock's benchmark), xor 90.0% on JevBench public set (231 items), maker's self-run of Xor 1.2 — so the numbers do not rank them. Test both on your own labelled examples.
Which is cheaper, this-that-model or xor?
this-that-model: Free (open weights). xor: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Which is faster, this-that-model or xor?
By their publishers’ figures, this-that-model answers in about 31.4 ms at the median and xor in about 69 ms — measured on different hardware, so treat it as a rough guide.
Can I run this-that-model or xor locally?
Yes, both: systemone pull flock-io/this-that-model and systemone pull juspay/xor download the weights.
JevBench public set (231 items), maker's self-run of Xor 1.2
