Qwen2.5 72B Instruct — Benchmarks
Benchmark scores for Qwen2.5 72B Instruct aggregated from public leaderboards (12 boards), with how it ranks among open models and how it compares with its nearest neighbours. See hardware requirements for what you need to run it.
- #80 of 100 open models
- 12 boards · updated Oct 2026
- 100 = average open model
- Hardware requirements →
Qwen2.5 72B Instruct reasoning benchmarks
Multi-step logic and problem-solving — can the model think through a hard problem rather than recall an answer.
49.1%
49.1%
median 54.0%open leader 93.1%
Overall best: Gemini 4 Argon (high) 96.4%
45th percentile · #54 of 98 open · #226 of 300 all
IndependentEpoch AI ·
16.2%
16.2%
median 16.2%open leader 34.9%
Overall best: GPT 6 Astra Max 68.3%
50th percentile · #8 of 15 open · #32 of 40 all
IndependentEpoch AI ·
62.9%
62.9%
median 67.7%open leader 93.9%
Overall best: Claude Opus 5.5 Max 98.9%
42nd percentile · #40 of 68 open · #156 of 214 all
Lab-reportedEpoch AI ·
57.5
57.5
median 58.1open leader 61.9
Overall best: O3 (Apr 16, 2025, unspecified) 62.5
36th percentile · #18 of 26 open · #66 of 82 all
Lab-reportedEpoch AI ·
13.4%
13.4%
median 24.7%open leader 55.5%
Overall best: Claude Opus 5.5 Max 68.2%
19th percentile · #44 of 54 open · #158 of 176 all
Lab-reportedEpoch AI ·
Qwen2.5 72B Instruct coding benchmarks
Writing, editing, and fixing real code — measured by whether the resulting program actually runs and passes tests.
16.0%
16.0%
median 39.5%open leader 82.6%
Overall best: GPT 6 Astra Promax 93.6%
11th percentile · #41 of 46 open · #151 of 162 all
IndependentEpoch AI ·
Other results (1)· leaderboard-only, not part of the llmrun Score
35.8%
35.8%
median 49.6%open leader 59.2%
Overall best: Claude Mythos Preview Early 85.2%
25th percentile · #7 of 9 open · #36 of 46 all
Lab-reportedEpoch AI ·
Qwen2.5 72B Instruct math benchmarks
Symbolic and quantitative problem-solving, from competition math to multi-step calculation.
8.1%
8.1%
median 52.8%open leader 98.6%
Overall best: Claude Fable 5 (high) 100.0%
30th percentile · #60 of 86 open · #236 of 283 all
IndependentEpoch AI ·
63.2%
63.2%
median 41.6%open leader 96.6%
Overall best: GPT 5 (Aug 07, 2025, high) 98.1%
74th percentile · #11 of 39 open · #52 of 107 all
IndependentEpoch AI ·
Qwen2.5 72B Instruct knowledge benchmarks
Breadth and depth of factual knowledge across many subjects, paired with the reasoning to apply it.
71.6%
71.6%
median 52.1%open leader 88.0%
Overall best: Gemini-3.1-Pro 91.2%
76th percentile · #35 of 145 open · #95 of 257 all
Independent
Qwen2.5 72B Instruct instruction following benchmarks
How precisely a model obeys explicit, verifiable instructions — format, length, and content constraints — and, more broadly, how much people prefer its responses head-to-head in blind human voting.
1302.9
1302.9
median 1321.5open leader 1487.1
Overall best: Gemini 4 Argon (High) 1523.9
44th percentile · #106 of 187 open · #275 of 405 all
ArenaArena ·
Score vs VRAM in the ≤64 GB tier
- Qwen2.5 72B Instruct
- Other models
- Best Score for its VRAM
#30 of 49 that fit ≤64 GB
Each dot is a model at the best quant that fits ≤64 GB. The line joins the models with the best Score for their VRAM; a dot below it is beaten by a model that needs no more memory.
Full ≤64 GB ranking →Qwen2.5 72B Instruct vs its neighbours
Same boards for the nearest open models per llmrun Score. The highest score in each row is marked.
| Board | Qwen2.5 72B Instructthis model | Qwen3.8 27Bbest in classQ4_K_M · 18 GB | Llama 4 Scout 17B 16E Instructnearest by ScoreQ4_K_M · 77 GB | Mistral Large Instruct 2407nearest by ScoreQ4_K_M · 86 GB | C4ai Command A 03 2025nearest by ScoreQ4_K_M · 79 GB |
|---|---|---|---|---|---|
| llmrun Score | 81.7 | 122.1 | 81.8 | 81.1 | 79.8 |
| GPQA Diamond | 49.1% | — | 51.8% | 49.0% | — |
| DTBench | 62.9% | 88.0% | 57.9% | 61.2% | 61.3% |
| ForecastBench | 57.5 | — | 57.5 | 57.1 | — |
| LMCA | 13.4% | 41.4% | 12.0% | — | 10.3% |
| AIME 2024/2025 | 8.1% | — | 7.8% | 8.5% | — |
| MATH Level 5 | 63.2% | — | 62.3% | 44.8% | — |
| MMLU-Pro | 71.6% | — | 74.3% | 65.9% | — |
| LMArena Text | 1302.9 | 1437.8 | 1321.5 | 1314.4 | 1353.7 |
| Compare head to head | Compare | Compare | Compare | Compare |
Scores aggregated from public benchmark sources (Epoch AI: 10 boards, Arena: 1 board, TIGER-Lab: 1 board) — each linked from the benchmark pages. llmrun does not run these benchmarks. Percentiles and ranks are among open models in the llmrun catalogue; the median and leader marks refer to the same field.