Qwen2.5-14B-Instruct-1M
Qwen2.5-14B-Instruct-1M ranks first on LongBench-Chat.
Qwen2.5-14B-Instruct-1M
Open weights Small
- Open Arabic LLM Leaderboard v1 58.8% #3 /55
- MMLU-Pro 63.3% #142 /167
- IFEval 84.3% #87 /135
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 | |
|---|---|---|---|---|
| Open Arabic LLM Leaderboard v1 | 58.8% | #3 of 55 | Official leaderboard | |
| RULER | 95.7% | #4 of 42 | Lab model card | |
| LongBench-Chat | 8.76 | #1 of 6 | Lab model card | |
| MT-Bench | 8.89 | #9 of 23 | Lab model card | |
| MuSR | 41.8% | #44 of 98 | Official leaderboard | |
| Stick to Your Role! | 0.59 | #8 of 15 | Official leaderboard | |
| IFEval | 84.3% | #87 of 135 | Lab model card | |
| Arena-Hard-Auto | 70.2% | #27 of 39 | Lab model card | |
| MMLU-Pro | 63.3% | #142 of 167 | Lab model card | |
| MMLU-Redux | 80.7% | #39 of 45 | Lab model card | |
| Passkey Retrieval | 100% | #2 of 2 | Lab model card | |
| LV-Eval | 49.8% | #1 of 1 | Lab model card |
Math and science
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| GSM8K | 94.8% | #16 of 92 | Lab model card | |
| MATH | 79.5% | #29 of 99 | Lab model card | |
| GPQA Diamond | 39.9% | #275 of 302 | Lab model card |
Coding
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| HumanEval | 88.4% | #23 of 101 | Lab model card | |
| MBPP | 80.2% | #21 of 71 | Lab model card | |
| MultiPL-E | 77.1% | #6 of 18 | Lab model card | |
| LiveCodeBench | 38.6% | #36 of 54 | Lab model card |
Other
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| Open LLM Leaderboard v2 | 41.6 | #4 of 99 | Official leaderboard | |
| LiveBench | 44.6% | #23 of 27 | Lab model card |
Its lab's numbers put it at 124.3, number 317 of 404
The Self-Reported Index fits one score to the 12 capability results Qwen 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 121.8 to 126.9. How we compute it.
- RULER 95.7
- GSM8K 94.8
- HumanEval 88.4
- IFEval 84.3
- MMLU-Redux 80.7
- MBPP 80.2
- MATH 79.5
- MultiPL-E 77.1
- Arena-Hard-Auto 70.2
- MMLU-Pro 63.3
- GPQA Diamond 39.9
- LiveCodeBench 38.6
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.
Its system card
Every result in the longer documents the lab published with it. 13 of them aren't in the launch post.
Capabilities
- RULER 95.7
- LV-Eval
- LongBench-Chat 8.76
- Passkey Retrieval 100
- MMLU-Pro 63.3
- MMLU-Redux 80.7
- LiveBench 44.6
- GPQA Diamond 39.9
- MATH 79.5
- GSM8K 94.8
- HumanEval 88.4
- MBPP 80.2
- MultiPL-E 77.1
- LiveCodeBench 38.6
- IFEval 84.3
- Arena-Hard-Auto 70.2
- MT-Bench 8.89