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DecisionTune: decisiontune and Bofeng Huang: docto-decision, compared on what they decide, where they run, what they cost and what their publishers report.
| Property | decision-tune/decisiontune | bofeng-huang/docto-decision |
|---|---|---|
| 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. | French medical decision models by Bofeng Huang: pass a patient message or clinical note, a question and candidate answers, and get one probability per answer from a single forward pass. Choice, score and noul. A research model, not a medical device. |
| Decides | choice, noul, route, classify | choice, score, noul |
| Architecture | decisiontune | docto-decision |
| Fine-tuned from | answerdotai/modernbert-large | qwen/qwen3.5-4b |
| License | apache-2.0 | apache-2.0 |
| Availability | Open weights | Open weights |
| Hosted by | — | — |
| Input price | — | — |
| Decision accuracy | — | 88.9% |
| Calibration error | — | 0.079 |
| Valid action rate | — | — |
| Median latency | — | 47 ms |
| p95 latency | — | — |
| Evaluation suite | — | Docto Decision Bench fr v0.1 (12 tasks, mostly silver labels; the maker's own benchmark) |
| Latest version | 1.0.0 | 0.1.0 |
| Variants | onnx | LICENSE, adapters |
| Size of latest version | 2.9 GB | 8.8 GB |
| Files | 8 | 13 |
| Downloads | 0 | 0 |
| Stars | 0 | 0 |
| Tags | system-one, encoder, modernbert, mlx, onnx, mcp, 395m | system-one, french, medical, qwen, lora, 4.66b |
| 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 docto-decision from Bofeng Huang. Both have open weights you can download and run. Both answer choice and noul questions. Only decisiontune answers route and classify. Only docto-decision answers score. decisiontune is the smaller model, at 395M parameters to 4.7B.
Only docto-decision publishes an accuracy figure (88.9% on Docto Decision Bench fr v0.1 (12 tasks, mostly silver labels; the maker's own benchmark)); decisiontune does not, so there is no comparison to make without your own test.
decisiontune: Free (open weights). docto-decision: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Yes, both: systemone pull decision-tune/decisiontune and systemone pull bofeng-huang/docto-decision download the weights.