Model comparison
GLM-5 vs o1-pro
GLM-5 is the stronger model overall, scoring 46.1 to 31.5 on the Noometry Index.
Last verified . 1 shared benchmarks.
Summary
- They share 1 benchmark with published results for both. GLM-5 scores higher in 2 categories and o1-pro in 0 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-5 leads 52.3 to 29.7.
- The biggest single-benchmark swing is ARC-AGI-1: 44.7% for GLM-5 and 23.3% for o1-pro.
- GLM-5 is cheaper at $1 / $3.20 per million input/output tokens, against $150 / $600 for o1-pro.
- GLM-5 accepts more context: 205K tokens versus 200K.
- GLM-5 has downloadable open weights; the other is API-only.
Side by side
| GLM-5 | o1-pro | |
|---|---|---|
| Provider | Z.ai (Zhipu) | OpenAI |
| Noometry Index | 46.1 | 31.5 |
| Released | 2026-02-11 | 2025-03-19 |
| Weights | Open | Proprietary |
| Context window | 205K | 200K |
| Max output | 131K | 100K |
| Input $ / M tokens | $1 | $150 |
| Output $ / M tokens | $3.20 | $600 |
| Results tracked | 45 | 3 |
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Category by category
Coding Not comparable
GLM-5: 49.0 (#52), o1-pro: —
| Benchmark | GLM-5 | o1-pro |
|---|---|---|
| SWE-bench Verified | 72.1% | — |
| SWE-bench Verified (bash only) | 72.8% | — |
| LMArena WebDev | 1434 | — |
| SWE-bench Multilingual | 69.7% | — |
| WeirdML | 48.2% | — |
| LMArena Coding | 1461 | — |
| ALE-Bench | 765.62 | — |
Agentic & Tool Use Not comparable
GLM-5: 31.1 (#71), o1-pro: —
| Benchmark | GLM-5 | o1-pro |
|---|---|---|
| Terminal-Bench | 52.4% | — |
| τ²-bench Airline | 82.5% | — |
| τ²-bench Banking | 9.8% | — |
| τ²-bench Retail | 73.7% | — |
| τ²-bench Telecom | 86.8% | — |
| Vending-Bench 2 | 4,432 | — |
Reasoning GLM-5 leads
GLM-5: 27.6 (#116), o1-pro: 20.4 (#239)
| Benchmark | GLM-5 | o1-pro |
|---|---|---|
| ARC-AGI-1 | 44.7% | 23.3% |
| ARC-AGI-2 | 4.9% | — |
| SimpleBench | 53.2% | — |
| Kagi LLM Benchmark | 75% | — |
| NYT Connections (extended) | 74.8% | — |
| Chess Puzzles | 10% | — |
| EnigmaEval | — | 6.1% |
| LMArena Hard Prompts | 1452 | — |
| Epoch Capabilities Index | 145.83 | — |
| ForecastBench | 61 | — |
Math Not comparable
GLM-5: 46.4 (#71), o1-pro: —
| Benchmark | GLM-5 | o1-pro |
|---|---|---|
| MathArena Final-Answer Competitions | 65.7% | — |
| OTIS Mock AIME 2024-2025 | 80% | — |
| LMArena Math | 1440 | — |
| FrontierMath (Feb 2025 set) | 16.4% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge GLM-5 leads
GLM-5: 52.3 (#64), o1-pro: 29.7 (#234)
| Benchmark | GLM-5 | o1-pro |
|---|---|---|
| GPQA Diamond | 87.8% | — |
| Humanity's Last Exam | — | 8.1% |
| Vectara Hallucination Rate | 10.1% | — |
| LMArena Expert | 1454 | — |
Multilingual Not comparable
GLM-5: 53.7 (#58), o1-pro: —
| Benchmark | GLM-5 | o1-pro |
|---|---|---|
| LMArena Non-English | 1430 | — |
| LMArena Chinese | 1511 | — |
| LMArena French | 1455 | — |
| LMArena German | 1445 | — |
| LMArena Japanese | 1416 | — |
| LMArena Korean | 1423 | — |
| LMArena Russian | 1436 | — |
| LMArena Spanish | 1454 | — |
Instruction Following Not comparable
GLM-5: 75.2 (#67), o1-pro: —
| Benchmark | GLM-5 | o1-pro |
|---|---|---|
| LMArena Instruction Following | 1428 | — |
Long Context Not comparable
GLM-5: 44.7 (#60), o1-pro: —
| Benchmark | GLM-5 | o1-pro |
|---|---|---|
| CL-bench | 18.7% | — |
| LMArena Longer Query | 1446 | — |
Writing & Preference Not comparable
GLM-5: 66.0 (#38), o1-pro: —
| Benchmark | GLM-5 | o1-pro |
|---|---|---|
| LMArena Text | 1446 | — |
| LMArena Creative Writing | 1439 | — |
| EQ-Bench Creative Writing | 1601 | — |
| LMArena Multi-Turn | 1456 | — |
Frequently asked questions
Is GLM-5 better than o1-pro?
GLM-5 is the stronger model overall, scoring 46.1 to 31.5 on the Noometry Index.
Which is cheaper, GLM-5 or o1-pro?
GLM-5 is cheaper. It lists at $1 per million input tokens and $3.20 per million output tokens; o1-pro lists at $150 and $600.
Which has the bigger context window?
GLM-5 does, with 205K tokens against 200K.
How many benchmarks do GLM-5 and o1-pro share?
1 benchmark has published results for both models. GLM-5 has 45 scored results on Noometry and o1-pro has 3.