Model comparison
GLM-4.5 vs o1-pro
GLM-4.5 is the stronger model overall, scoring 42.0 to 31.5 on the Noometry Index.
Last verified . 1 shared benchmarks.
Summary
- They share 1 benchmark with published results for both. GLM-4.5 scores higher in 2 categories and o1-pro in 0 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GLM-4.5 leads 28.6 to 20.4.
- GLM-4.5 is cheaper at $0.60 / $2.20 per million input/output tokens, against $150 / $600 for o1-pro.
- o1-pro accepts more context: 200K tokens versus 131K.
- GLM-4.5 has downloadable open weights; the other is API-only.
Side by side
| GLM-4.5 | o1-pro | |
|---|---|---|
| Provider | Z.ai (Zhipu) | OpenAI |
| Noometry Index | 42.0 | 31.5 |
| Released | 2025-07-27 | 2025-03-19 |
| Weights | Open | Proprietary |
| Context window | 131K | 200K |
| Max output | 98K | 100K |
| Input $ / M tokens | $0.60 | $150 |
| Output $ / M tokens | $2.20 | $600 |
| Results tracked | 27 | 3 |
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Category by category
Coding Not comparable
GLM-4.5: 41.4 (#125), o1-pro: —
| Benchmark | GLM-4.5 | o1-pro |
|---|---|---|
| SWE-bench Verified (bash only) | 54.2% | — |
| WeirdML | 40.6% | — |
| LMArena Coding | 1434 | — |
| ALE-Bench | 344.82 | — |
| AlgoTune | 1.52 | — |
Reasoning GLM-4.5 leads
GLM-4.5: 28.6 (#100), o1-pro: 20.4 (#239)
| Benchmark | GLM-4.5 | o1-pro |
|---|---|---|
| Kagi LLM Benchmark | 57.9% | — |
| ARC-AGI-1 | — | 23.3% |
| EnigmaEval | — | 6.1% |
| LMArena Hard Prompts | 1429 | — |
Math Not comparable
GLM-4.5: 39.0 (#116), o1-pro: —
| Benchmark | GLM-4.5 | o1-pro |
|---|---|---|
| LMArena Math | 1427 | — |
Knowledge GLM-4.5 leads
GLM-4.5: 35.9 (#179), o1-pro: 29.7 (#234)
| Benchmark | GLM-4.5 | o1-pro |
|---|---|---|
| Humanity's Last Exam | 8.3% | 8.1% |
| Confabulations | 11.3% | — |
| LMArena Expert | 1433 | — |
Multilingual Not comparable
GLM-4.5: 52.8 (#77), o1-pro: —
| Benchmark | GLM-4.5 | o1-pro |
|---|---|---|
| LMArena Non-English | 1417 | — |
| LMArena Chinese | 1465 | — |
| LMArena French | 1418 | — |
| LMArena German | 1407 | — |
| LMArena Japanese | 1415 | — |
| LMArena Korean | 1380 | — |
| LMArena Russian | 1414 | — |
| LMArena Spanish | 1454 | — |
Instruction Following Not comparable
GLM-4.5: 74.1 (#104), o1-pro: —
| Benchmark | GLM-4.5 | o1-pro |
|---|---|---|
| LMArena Instruction Following | 1404 | — |
Long Context Not comparable
GLM-4.5: 38.2 (#201), o1-pro: —
| Benchmark | GLM-4.5 | o1-pro |
|---|---|---|
| Fiction.LiveBench | 58.3% | — |
| LMArena Longer Query | 1412 | — |
Writing & Preference Not comparable
GLM-4.5: 57.5 (#127), o1-pro: —
| Benchmark | GLM-4.5 | o1-pro |
|---|---|---|
| LMArena Text | 1430 | — |
| LMArena Creative Writing | 1395 | — |
| Short-Story Creative Writing | 73.4% | — |
| EQ-Bench Creative Writing | 1343 | — |
| LMArena Multi-Turn | 1415 | — |
Frequently asked questions
Is GLM-4.5 better than o1-pro?
GLM-4.5 is the stronger model overall, scoring 42.0 to 31.5 on the Noometry Index.
Which is cheaper, GLM-4.5 or o1-pro?
GLM-4.5 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; o1-pro lists at $150 and $600.
Which has the bigger context window?
o1-pro does, with 200K tokens against 131K.
How many benchmarks do GLM-4.5 and o1-pro share?
1 benchmark has published results for both models. GLM-4.5 has 27 scored results on Noometry and o1-pro has 3.