- Arena-Hard (thinking=True) 57.6
- AlpacaEval-2.0 (thinking=True) 62.7
- MMLU 65.5
- PopQA 26.2
- TruthfulQA 66.9
- BigBenchHard 69.1
- DROP 59.4
- GSM8K 80.9
- HumanEval 89.7
- HumanEval+ 86.1
- IFEval 74.8
- AttaQ 88.5
- AIME24 8.12
- MATH-500 69
Granite 3.3 8B Instruct
Granite 3.3 8B Instruct ranks first on AttaQ.
Granite 3.3 8B Instruct
Open weights Flagship
- PopQA 26.2% #6 /7
- GPQA Main 32.5% #54 /60
- QIMMA 46.5% #17 /25
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 | |
|---|---|---|---|---|
| TruthfulQA | 66.9% | #9 of 30 | Lab model card | |
| AlpacaEval 2.0 | 62.7% | #5 of 16 | Lab model card | |
| Vectara Hallucination Leaderboard (2025 dataset) | 10.6% | #66 of 104 | Official leaderboard | |
| BIG-Bench Hard | 69.1% | #49 of 73 | Lab model card | |
| QIMMA | 46.5% | #17 of 25 | Official leaderboard | |
| Arena-Hard-Auto | 57.6% | #31 of 39 | Lab model card | |
| MMLU | 65.5% | #110 of 131 | Lab model card | |
| PopQA | 26.2% | #6 of 7 | Lab model card | |
| IFEval | 74.8% | #119 of 135 | Lab model card | |
| DROP | 59.4% | #38 of 41 | Lab model card |
Math and science
Coding
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| HumanEval | 89.7% | #14 of 101 | Lab model card | |
| HumanEval+ | 86.1% | #13 of 27 | Lab model card |
Professional work
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| AssetOpsBench | 35% | #3 of 3 | Official leaderboard |
Safety and security
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| AttaQ | 88.5% | #1 of 5 | Lab model card | |
| AIR-Bench 2024 | 82.5% | #19 of 82 | Official leaderboard | |
| Anthropic Red Team | 99.1% | #33 of 75 | Official leaderboard | |
| HELM Safety | 90.5 | #45 of 75 | Official leaderboard | |
| SimpleSafetyTests | 97.5% | #51 of 75 | Official leaderboard |
Other
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| HELM Capabilities | 46.3 | #57 of 60 | Official leaderboard |
Its lab's numbers put it at 115.5, number 366 of 404
The Self-Reported Index fits one score to the 12 capability results IBM 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 112.3 to 118.6. How we compute it.
- HumanEval 89.7
- HumanEval+ 86.1
- GSM8K 80.9
- IFEval 74.8
- BIG-Bench Hard 69.1
- MATH-500 69
- TruthfulQA 66.9
- MMLU 65.5
- AlpacaEval 2.0 62.7
- DROP 59.4
- Arena-Hard-Auto 57.6
- AIME 2024 8.12
Its lab's number next to a leaderboard
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.