- IMO 2025 (35 pts, gold medal level) 35
- IMO AnswerBench 79.3
- IMO ProofBench 72.9
- AIME 2025 (TIR 98.6) 92.4
- AIME 2026 (TIR 95.0) 90.9
- HMMT Feb25 94.6
- IOI 2025 439.3
- ICPC World Finals 2025 (10/12) 10
- LiveCodeBench v6 (2408-2505) (TIR 88.4) 87.2
- LiveCodeBenchPro 25Q2 Med 27.6 (Easy 87.0) 27.6
- SciCode 36.4
- MMLU-Redux 86.3
- MMLU-Pro 79.8
- GPQA-Diamond 76.1
- HLE (no tool) 17.7
- ArenaHard v2 (Avg.); Hard Prompt 88.2, Creative Writing 78.7 83.5
- IFBench (prompt) 82.9
- Scale AI Multi-Challenge 45.3
- AA-LCR 39.1
- LongBench v2 40.3
- NIAH@1M (RULER Subset) 99
- CL-Bench 12.2
- BFCL v4 52.9
- τ²-Bench 58.9
- Terminal Bench 2.0 21.1
- SWE Verified (OpenHands) 50.2
- MMLU-ProX 72.5
- WMT24++ (en -> xx) 84.1
Nemotron-Cascade 2 30B-A3B
Nemotron-Cascade 2 30B-A3B ranks first on 2 of the 26 benchmarks it has scores on.
27
Benchmarks with a score
2
Ranked first, out of five or more models
5
In the top three
Nemotron-Cascade 2 30B-A3B
Open weights Small
No Epoch Capabilities Index score yet
- IFBench 82.9% #1 /70
- SciCode 36.4% #38 /47
- AA-LCR (Artificial Analysis Long Context Reasoning) 39.1% #29 /31
Where it ranks
Its best score on each benchmark, and where that ranks among every model with a score there. We rank each model once, at its best setting.
Knowledge and language
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| IFBench | 82.9% | #1 of 70 | Model card | |
| RULER | 99% | #1 of 38 | Model card | |
| Arena-Hard v2.0 | 83.5% | #3 of 24 | Model card | |
| MMLU-Pro | 79.8% | #78 of 151 | Model card | |
| WMT24++ | 84.1% | #8 of 12 | Model card | |
| Humanity's Last Exam | 17.7% | #110 of 147 | Model card | |
| MMLU-Redux | 86.3% | #29 of 38 | Model card | |
| MMLU-ProX | 72.5% | #13 of 17 | Model card | |
| MultiChallenge | 45.3% | #29 of 36 | Model card | |
| AA-LCR (Artificial Analysis Long Context Reasoning) | 39.1% | #29 of 31 | Model card | |
| LongBench v2 | 40.3% | #26 of 27 | Model card | |
| CL-bench | 12.2% | #6 of 6 | Model card |
Math and science
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| AIME 2025 | 92.4% | #38 of 143 | Model card | |
| HMMT 2025 | 94.6% | #14 of 49 | Model card | |
| IMO-ProofBench | 72.9% | #2 of 5 | Model card | |
| GPQA Diamond | 76.1% | #134 of 284 | Model card | |
| IMO 2025 | 83.3% | #3 of 6 | Model card | |
| IMO-AnswerBench | 79.3% | #25 of 37 | Model card | |
| AIME 2026 | 90.9% | #27 of 34 | Model card |
Coding
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| LiveCodeBench v6 | 87.2% | #14 of 76 | Model card | |
| Codeforces rating | 2,320 | #13 of 41 | Model card | |
| ICPC World Finals 2025 | 10.0 | #2 of 3 | Model card | |
| SciCode | 36.4% | #38 of 47 | Model card | |
| SWE-bench Verified | 50.2% | #125 of 150 | Model card |
Agents and tools
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| tau2-bench | 58.9% | #60 of 69 | Model card | |
| BFCL V4 | 52.9% | #22 of 24 | Model card | |
| Terminal-Bench 2.0 | 21.1% | #60 of 61 | Model card |
Its launch post
The benchmarks the lab chose to headline, with the scores it gave.
Its system card
Every result in the longer documents the lab published with it. 1 of them isn't in the launch post.
Nemotron-Cascade 2: Post-Training LLMs with Cascade RL and Multi-Domain On-Policy Distillation 19 Mar 2026
Capabilities
- IMO 2025 83.3
- IMO-AnswerBench 79.3
- IMO-ProofBench 72.9
- AIME 2025 92.4
- AIME 2026 90.9
- HMMT 2025 94.6
- IOI 2025 439.3
- ICPC World Finals 2025 10
- LiveCodeBench v6 87.2
- LiveCodeBench Pro 27.6
- Codeforces rating 2320
- SciCode 36.4
- MMLU-Redux 86.3
- MMLU-Pro 79.8
- GPQA Diamond 76.1
- Humanity's Last Exam 17.7
- Arena-Hard v2.0 83.5
- IFBench 82.9
- MultiChallenge 45.3
- AA-LCR (Artificial Analysis Long Context Reasoning) 39.1
- LongBench v2 40.3
- RULER 99
- CL-bench 12.2
- BFCL V4 52.9
- tau2-bench 58.9
- Terminal-Bench 2.0 21.1
- SWE-bench Verified 50.2
- MMLU-ProX 72.5
- WMT24++ 84.1