Leaderboard Evaluation on Open LLM Leaderboard 1
69.28Overall ScoreUltraMix-190k
Evaluation Results
| Method | Links | |
|---|---|---|
| UltraMix-190kBase Model=Qwen-2.5-7B-TuluSFT, Training Mixture/Protocol=UM-190k2025.11 | 69.28 | |
| UltraMix-187kBase Model=Qwen-2.5-7B-TuluSFT, Training Mixture/Protocol=UM-187k2025.11 | 68.97 | |
| UltraMix-190kBase Model=Llama-3.1-8B-TuluSFT, Training Mixture/Protocol=UM-190k2025.11 | 68.5 | |
| UltraMix-170kBase Model=Qwen-2.5-7B-TuluSFT, Training Mixture/Protocol=UM-170k2025.11 | 68.29 | |
| UltraMix-187kBase Model=Llama-3.1-8B-TuluSFT, Training Mixture/Protocol=UM-187k2025.11 | 67.95 | |
| UltraMix-170kBase Model=Llama-3.1-8B-TuluSFT, Training Mixture/Protocol=UM-170k2025.11 | 66.79 | |
| TuluDPOBase Model=Qwen-2.5-7B-TuluSFT, Training Mixture/Protocol=TuluDPO2025.11 | 66.73 | |
| TuluDPOBase Model=Llama-3.1-8B-TuluSFT, Training Mixture/Protocol=TuluDPO2025.11 | 66.3 | |
| SFTBase Model=Qwen-2.5-7B-TuluSFT, Training Mixture/Protocol=SFT2025.11 | 64.76 | |
| UM-190kBackbone=Apertus-8B-SFT2025.11 | 63.83 | |
| UM-187kBackbone=Apertus-8B-SFT2025.11 | 63.43 | |
| SFTBase Model=Llama-3.1-8B-TuluSFT, Training Mixture/Protocol=SFT2025.11 | 62.85 | |
| UltraMixTraining Method=DPO, Dataset=UM-190k2025.11 | 62.51 | |
| UltraMixTraining Method=DPO, Dataset=UM-187k2025.11 | 62.29 | |
| UM-170kBackbone=Apertus-8B-SFT2025.11 | 62.26 | |
| Instella-3B-SFT (UM-190k)DPO Training Dataset=UM-190k2025.11 | 62.03 | |
| Instella-3B-SFT (UM-187k)DPO Training Dataset=UM-187k2025.11 | 61.78 | |
| TuluDPOTraining Method=DPO, Dataset=TuluDPO2025.11 | 61.67 | |
| TuluDPOBackbone=Apertus-8B-SFT2025.11 | 61.67 | |
| Instella-3B-SFT (UM-170k)DPO Training Dataset=UM-170k2025.11 | 61.28 | |
| UltraMixTraining Method=DPO, Dataset=UM-170k2025.11 | 61.19 | |
| Instella-3B-SFT (TuluDPO)DPO Training Dataset=TuluDPO2025.11 | 60.96 | |
| UltraFBBackbone=Apertus-8B-SFT2025.11 | 60.94 | |
| ORPOBackbone=Apertus-8B-SFT2025.11 | 60.58 | |
| Instella-3B-SFT (ORPO)DPO Training Dataset=ORPO2025.11 | 60.32 | |
| Instella-3B-SFT (UltraFB)DPO Training Dataset=UltraFB2025.11 | 59.99 | |
| ORPOTraining Method=ORPO, Dataset=ORPO2025.11 | 59.89 | |
| Instella-3B-SFT (HelpSteer)DPO Training Dataset=HelpSteer2025.11 | 59.76 | |
| Instella-3B-SFT (SFT)DPO Training Dataset=None (SFT Baseline)2025.11 | 59.62 | |
| SFTBackbone=Apertus-8B-SFT2025.11 | 59.49 | |
| HelpSteerBackbone=Apertus-8B-SFT2025.11 | 59.44 | |
| Instella-3B-SFT (CodePref)DPO Training Dataset=CodePref2025.11 | 58.39 | |
| SmolLM-3-3B-SFTTraining Method=SFT2025.11 | 57.48 | |
| HelpSteerTraining Method=DPO, Dataset=HelpSteer2025.11 | 57.17 | |
| CodePrefBackbone=Apertus-8B-SFT2025.11 | 56.7 | |
| UltraFBTraining Method=DPO, Dataset=UltraFB2025.11 | 56.5 | |
| CodePrefTraining Method=DPO, Dataset=CodePref2025.11 | 55.33 | |
| UM-190k2025.11 | 53.95 | |
| UM-187k2025.11 | 53.53 | |
| TuluDPO2025.11 | 52.57 | |
| ORPO2025.11 | 52.33 | |
| UM-170k2025.11 | 52 | |
| UltraFB2025.11 | 50.95 | |
| SFT2025.11 | 50.73 | |
| HelpSteer2025.11 | 50.68 | |
| CodePref2025.11 | 49.38 |