Model card
Qwen2.5-72B-Instruct.
Unknown
Imported from Papers with Code dump
§ 02 · Benchmarks
Every benchmark Qwen2.5-72B-Instruct has a recorded score for.
| # | Benchmark | Area · Task | Metric | Value | Rank | Date | Source |
|---|---|---|---|---|---|---|---|
| 01 | LV-Eval | Natural Language Processing · Language Modeling | Accuracy | 60.4% | #1 | — | source ↗ |
| 02 | LiveCodeBench | General · Coding Agents | Pass@1 | 55.5% | #1 | — | source ↗ |
| 03 | LongBench-Chat | Natural Language Processing · Language Modeling | Score (1-10) | 8.7% | #1 | — | source ↗ |
| 04 | MBPP | General · Coding Agents | Pass@1 | 88.2% | #1 | — | source ↗ |
| 05 | MGS | Natural Language Processing · Language Modeling | Accuracy | 88.2% | #1 | — | source ↗ |
| 06 | MMLU-Redux | Natural Language Processing · Language Modeling | Accuracy | 86.8% | #1 | — | source ↗ |
| 07 | MTbench | Natural Language Processing · Language Modeling | Score (1-10) | 9.3% | #1 | — | source ↗ |
| 08 | RULER | Natural Language Processing · Language Modeling | Accuracy | 95.1% | #1 | — | source ↗ |
| 09 | okapi MMLU (translated) | Natural Language Processing · Language Modeling | Accuracy | 80.0% | #1 | — | source ↗ |
Rank column shows this model’s position vs all other models scored on the same benchmark + metric (competitors after the slash). #1 in red means current SOTA. Sorted by rank, then newest result.
§ 03 · Strengths by area
Where Qwen2.5-72B-Instruct actually performs.
§ 04 · Papers
1 paper with results for Qwen2.5-72B-Instruct.
- 2024-12-19· Natural Language Processing· 9 results
Qwen2.5 Technical Report
Qwen, :, An Yang, Baosong Yang et al.
§ 05 · Related models
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§ 06 · Sources & freshness
Where these numbers come from.
paper
9
results
0 of 9 rows marked verified.