Model comparison
GLM-4.5 vs Qwen2-72B
GLM-4.5 is the stronger model overall, scoring 42.0 to 30.0 on the Noometry Index.
Last verified . 18 shared benchmarks.
Alibaba (Qwen)Summary
- They share 18 benchmarks with published results for both. GLM-4.5 scores higher in 8 categories and Qwen2-72B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in multilingual, where GLM-4.5 leads 52.8 to 35.9.
- The biggest single-benchmark swing is WeirdML: 40.6% for GLM-4.5 and 11.3% for Qwen2-72B.
Side by side
| GLM-4.5 | Qwen2-72B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 42.0 | 30.0 |
| Released | 2025-07-27 | 2024-06-07 |
| Weights | Open | Open |
| Context window | 131K | — |
| Max output | 98K | — |
| Input $ / M tokens | $0.60 | — |
| Output $ / M tokens | $2.20 | — |
| Results tracked | 27 | 26 |
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Category by category
Coding GLM-4.5 leads
GLM-4.5: 41.4 (#125), Qwen2-72B: 29.1 (#310)
| Benchmark | GLM-4.5 | Qwen2-72B |
|---|---|---|
| WeirdML | 40.6% | 11.3% |
| LMArena Coding | 1434 | 1196 |
| SWE-bench Verified (bash only) | 54.2% | — |
| BigCodeBench Instruct | — | 38.5% |
| BigCodeBench Complete | — | 54% |
| ALE-Bench | 344.82 | — |
| AlgoTune | 1.52 | — |
Agentic & Tool Use Not comparable
GLM-4.5: —, Qwen2-72B: 17.0 (#146)
| Benchmark | GLM-4.5 | Qwen2-72B |
|---|---|---|
| TheAgentCompany | — | 1.1% |
| METR Time Horizons | — | 29.9% |
Reasoning GLM-4.5 leads
GLM-4.5: 28.6 (#100), Qwen2-72B: 23.2 (#181)
| Benchmark | GLM-4.5 | Qwen2-72B |
|---|---|---|
| LMArena Hard Prompts | 1429 | 1191 |
| Kagi LLM Benchmark | 57.9% | — |
| Epoch Capabilities Index | — | 125.28 |
Math GLM-4.5 leads
GLM-4.5: 39.0 (#116), Qwen2-72B: 30.2 (#236)
| Benchmark | GLM-4.5 | Qwen2-72B |
|---|---|---|
| LMArena Math | 1427 | 1235 |
| MATH Level 5 | — | 39.1% |
Knowledge GLM-4.5 leads
GLM-4.5: 35.9 (#179), Qwen2-72B: 21.2 (#275)
| Benchmark | GLM-4.5 | Qwen2-72B |
|---|---|---|
| LMArena Expert | 1433 | 1171 |
| GPQA Diamond | — | 40.8% |
| Humanity's Last Exam | 8.3% | — |
| Confabulations | 11.3% | — |
| MMLU | — | 82.4% |
Multilingual GLM-4.5 leads
GLM-4.5: 52.8 (#77), Qwen2-72B: 35.9 (#244)
| Benchmark | GLM-4.5 | Qwen2-72B |
|---|---|---|
| LMArena Non-English | 1417 | 1176 |
| LMArena Chinese | 1465 | 1240 |
| LMArena French | 1418 | 1170 |
| LMArena German | 1407 | 1151 |
| LMArena Japanese | 1415 | 1111 |
| LMArena Korean | 1380 | 1083 |
| LMArena Russian | 1414 | 1169 |
| LMArena Spanish | 1454 | 1169 |
Instruction Following GLM-4.5 leads
GLM-4.5: 74.1 (#104), Qwen2-72B: 61.7 (#241)
| Benchmark | GLM-4.5 | Qwen2-72B |
|---|---|---|
| LMArena Instruction Following | 1404 | 1181 |
Long Context GLM-4.5 leads
GLM-4.5: 38.2 (#201), Qwen2-72B: 36.1 (#235)
| Benchmark | GLM-4.5 | Qwen2-72B |
|---|---|---|
| LMArena Longer Query | 1412 | 1192 |
| Fiction.LiveBench | 58.3% | — |
Writing & Preference GLM-4.5 leads
GLM-4.5: 57.5 (#127), Qwen2-72B: 40.8 (#241)
| Benchmark | GLM-4.5 | Qwen2-72B |
|---|---|---|
| LMArena Text | 1430 | 1203 |
| LMArena Creative Writing | 1395 | 1181 |
| LMArena Multi-Turn | 1415 | 1196 |
| Short-Story Creative Writing | 73.4% | — |
| EQ-Bench Creative Writing | 1343 | — |
Frequently asked questions
Is GLM-4.5 better than Qwen2-72B?
GLM-4.5 is the stronger model overall, scoring 42.0 to 30.0 on the Noometry Index.
Is GLM-4.5 or Qwen2-72B better for coding?
GLM-4.5 scores higher on coding benchmarks: 41.4 versus 29.1 in the Noometry coding category.
How many benchmarks do GLM-4.5 and Qwen2-72B share?
18 benchmarks have published results for both models. GLM-4.5 has 27 scored results on Noometry and Qwen2-72B has 26.