- MMLU-Pro acc 80.9
- GPQA Diamond acc 79.6
- AIME 2025 acc 91
- IF-Bench prompt loose acc 70.8
- MultiChallenge acc 76.6
- LongCodeBench 1M match 84
- τ2-bench Telecom only (as benchmarked by Artificial Analysis) 76
- Mean of τ2-bench Retail-Verified 76.5 / Airline-Verified 64.8 (avg@3) 70.7
- BFCL v4 Overall FC 60.3
- MCP Atlas pass rate (blind eval) 24.6
- MMMU Pro accuracy 61.8
- OCRBench-v2 avg accuracy 56.1
- RealKIE-FCC Verified ALNS 62.1
- QVHighlights R1@0.5 77.2
- ScreenSpot point accuracy 83.3
- SWE-Bench Verified 64.5 with inference-time scaling and internal agentic scaffolding (53.6 without) 64.5
- Terminal-Bench 1.0 accuracy 32.5
- LiveCodeBench Code Generation (v5, 2024-07-01 to 2025-01-01 subset) 71
Nova 2 Lite
Nova 2 Lite ranks first on QVHighlights.
Nova 2 Lite
Closed weights Mid-size
- MMMU-Pro 61.8% #65 /90
- IFBench 70.8% #43 /80
- BFCL V4 60.3% #20 /30
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 | |
|---|---|---|---|---|
| MultiChallenge | 76.6% | #2 of 42 | Lab model card | |
| Vectara Hallucination Leaderboard (2025 dataset) | 5.10% | #12 of 104 | Official leaderboard | |
| MMLU-Pro | 80.9% | #72 of 167 | Lab model card | |
| IFBench | 70.8% | #43 of 80 | Lab model card | |
| LMArena (Elo) | 1,335 | #196 of 335 | Official leaderboard | |
| StudyArena Text | 1,191 | #67 of 85 | Official leaderboard | |
| Longform Creative Writing (EQ-Bench) | 38.8 | #101 of 119 | Official leaderboard | |
| LongCodeBench | 84% | #2 of 2 | Lab model card |
Math and science
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| AIME 2025 | 91% | #45 of 143 | Lab model card | |
| GPQA Diamond | 79.6% | #121 of 302 | Lab model card |
Coding
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| LiveCodeBench v5 | 71% | #8 of 47 | Lab model card | |
| SWE-bench Verified | 64.5% | #100 of 155 | Lab model card |
Agents and tools
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| tau2-bench | 76% | #48 of 79 | Lab model card | |
| BFCL V4 | 60.3% | #20 of 30 | Lab model card | |
| PinchBench | 63.1% | #37 of 48 | Official leaderboard | |
| Terminal-Bench | 32.5% | #18 of 22 | Lab model card | |
| tau2-bench Verified | 72.4% | #9 of 11 | Official leaderboard | |
| ScreenSpot | 83.3% | #10 of 11 | Lab model card | |
| PinchBench 2.0 | 37.6% | #53 of 57 | Official leaderboard | |
| MCP Atlas | 24.6% | #46 of 46 | Lab model card |
Vision, audio and robotics
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| QVHighlights | 77.2% | #1 of 5 | Lab model card | |
| RealKIE-FCC Verified | 62.1% | #2 of 3 | Lab model card | |
| MMMU-Pro | 61.8% | #65 of 90 | Lab model card | |
| ParseBench | 40.4% | #38 of 44 | Official leaderboard | |
| OCRBench v2 | 56.1% | #19 of 22 | Lab model card |
Safety and security
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| Aegis 2.0 | 85.8% | #1 of 3 | Lab model card | |
| Jigsaw Toxic Comment Classification | 56.5% | #2 of 3 | Lab model card | |
| WildGuardTest | 84.7% | #4 of 5 | Lab model card |
Its lab's numbers put it at 139.1, number 182 of 404
The Self-Reported Index fits one score to the 14 capability results Amazon reported for this model, on the scale of the Epoch Capabilities Index. Labs choose which benchmarks to show and how to run them, so read it as the lab's claim, not an independent measurement. The 90% interval runs from 135.9 to 142.4. How we compute it.
- AIME 2025 91
- ScreenSpot 83.3
- MMLU-Pro 80.9
- GPQA Diamond 79.6
- MultiChallenge 76.6
- tau2-bench 76
- LiveCodeBench v5 71
- IFBench 70.8
- SWE-bench Verified 64.5
- MMMU-Pro 61.8
- BFCL V4 60.3
- OCRBench v2 56.1
- Terminal-Bench 32.5
- MCP Atlas 24.6
Its lab's numbers next to 2 leaderboards
Where the benchmark's own leaderboard, or Epoch AI's run, also has this model. Gaps mostly come from different harnesses, effort levels and task subsets. Every pair.
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. 4 of them aren't in the launch post.
Capabilities
- MMLU-Pro 80.9
- GPQA Diamond 79.6
- AIME 2025 91
- IFBench 70.8
- MultiChallenge 76.6
- LongCodeBench 84
- OpenAI MRCR
- tau2-bench
- tau2-bench Verified
- BFCL V4 60.3
- MCP Atlas 24.6
- MMMU-Pro 61.8
- OCRBench v2 56.1
- RealKIE-FCC Verified 62.1
- QVHighlights 77.2
- ScreenSpot 83.3
- SWE-bench Verified 64.5
- Terminal-Bench 32.5
- LiveCodeBench v5 71
Safety
- Aegis 2.0 85.8
- WildGuardTest 84.7
- Jigsaw Toxic Comment Classification 56.5