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What each one decides, how well calibrated it is, how fast it answers and what it costs to pull. Up to 4 at a time; the better value in each row is marked.
| Property | contrastive-lm/clm | tianyu-codings/nanojev |
|---|---|---|
| Summary | Contrastive Language Models score a state against a set of candidate actions with a contrastive objective. Two projection heads on frozen Qwen3-8B embeddings, trained with InfoNCE; clm-serve maps Choice, Score and Noul onto candidate ranking. | A 0.6B replica of the System One idea trained on game environments. A Qwen3-0.6B backbone with an attention-based Choice head that scores a dynamic candidate set for Maze, Snake, ViZDoom and position prediction, shipped with its full training pipeline. |
| Decides | choice, score, noul, rank, classify, route | choice, noul, score |
| Architecture | clm | nanojev |
| Fine-tuned from | qwen/qwen3-8b | qwen/qwen3-0.6b |
| License | apache-2.0 | mit |
| Availability | Open weights | Open weights |
| Hosted by | — | — |
| Input price | — | — |
| Decision accuracy | — | — |
| Calibration error | — | — |
| Valid action rate | — | — |
| Median latency | — | — |
| p95 latency | — | — |
| Evaluation suite | — | — |
| Latest version | 2026.09.25 | 2026.09 |
| Variants | LICENSE | tokenizer |
| Size of latest version | 72.1 MB | 2.2 GB |
| Files | 3 | 2 |
| Downloads | 0 | 0 |
| Stars | 0 | 0 |
| Tags | system-one, contrastive, qwen, ranking, 8b | system-one, games, qwen, research, 0.6b |
| Updated | Sep 26, 2026 | Sep 26, 2026 |