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DecisionTune: decisiontune and Rizzo AI Academy: rizzo-flow, compared on what they decide, where they run, what they cost and what their publishers report.
| Property | decision-tune/decisiontune | rizzo-ai-academy/rizzo-flow |
|---|---|---|
| Summary | DecisionTune's 395M decision model: ModernBERT-large fine-tuned with a 4 KB scoring head that scores a marker per option, answering a choice or yes/no question in one encoder pass with a probability for every option. Runs locally on CPU or GPU via PyTorch, MLX or ONNX. | A local, Jev-compatible decision model from Rizzo AI Academy. XHToken's Spark-X2.5-4B with a merged typed-decisions LoRA, run on llama.cpp; yes/no, choice and score questions share one prefill of the state and are read from the answer-letter logits. No text is generated. |
| Decides | choice, noul, route, classify | choice, score, noul, classify, route |
| Architecture | decisiontune | rizzo-flow |
| Fine-tuned from | answerdotai/modernbert-large | xhtoken/spark-x2.5-4b |
| License | apache-2.0 | apache-2.0 |
| Availability | Open weights | Open weights |
| Hosted by | — | — |
| Input price | — | — |
| Decision accuracy | — | 64.8% |
| Calibration error | — | 0.112 |
| Valid action rate | — | — |
| Median latency | — | 195 ms |
| p95 latency | — | — |
| Evaluation suite | — | LocalLLaMA/typed-decisions test split (400 cases, 2,000 decisions), Q8_0 |
| Latest version | 1.0.0 | 2026.09 |
| Variants | onnx | lora, LICENSE |
| Size of latest version | 2.9 GB | 22.0 GB |
| Files | 8 | 17 |
| Downloads | 0 | 2 |
| Stars | 0 | 0 |
| Tags | system-one, encoder, modernbert, mlx, onnx, mcp, 395m | system-one, spark, lora, gguf, llama-cpp, 4b |
| Updated | Oct 7, 2026 | Oct 7, 2026 |
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.
decisiontune is from DecisionTune and rizzo-flow from Rizzo AI Academy. Both have open weights you can download and run. Both answer choice, noul, route and classify questions. Only rizzo-flow answers score. decisiontune is the smaller model, at 395M parameters to 4.0B.
Only rizzo-flow publishes an accuracy figure (64.8% on LocalLLaMA/typed-decisions test split (400 cases, 2,000 decisions), Q8_0); decisiontune does not, so there is no comparison to make without your own test.
decisiontune: Free (open weights). rizzo-flow: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Yes, both: systemone pull decision-tune/decisiontune and systemone pull rizzo-ai-academy/rizzo-flow download the weights.