# GLM-5.3 vs o1

> GLM-5.3 is the stronger model overall, scoring 54.6 to 40.6 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-5-3-vs-o1
- Last updated: 2026-10-10
- Shared benchmarks: 26

## Summary

- They share 26 benchmarks with published results for both. GLM-5.3 scores higher in 8 categories and o1 in 1 category; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-5.3 leads 62.1 to 34.9.
- The biggest single-benchmark swing is FrontierMath (Tiers 1-3): 68.8% for GLM-5.3 and 14.7% for o1.
- GLM-5.3 is cheaper at $1.40 / $4.40 per million input/output tokens, against $15 / $60 for o1.
- GLM-5.3 accepts more context: 1M tokens versus 200K.
- GLM-5.3 has downloadable open weights; the other is API-only.

## Snapshot

| | GLM-5.3 | o1 |
|---|---|---|
| Provider | Z.ai (Zhipu) | OpenAI |
| Noometry Index | 54.6 | 40.6 |
| Rank | 25 | 140 |
| Context | 1M | 200K |
| Input $/M | $1.40 | $15 |
| Output $/M | $4.40 | $60 |
| Weights | Open | Proprietary |

## Coding

- GLM-5.3: 59.0 (#12)
- o1: 45.7 (#64)

| Benchmark | GLM-5.3 | o1 |
|---|---|---|
| WeirdML | 75.4% | 47.6% |
| LMArena Coding | 1499 | 1367 |
| DeepSWE | 69% | — |
| FrontierCode | 40.1% | — |
| Aider Polyglot | — | 61.7% |
| LMArena WebDev | 1623 | — |
| FrontierSWE | 30.2% | — |
| SciCode | 59% | — |
| LiveBench Coding | — | 69.7% |
| CadEval | — | 56% |
| ALE-Bench | 1,317 | — |
| HumanEval+ | — | 89% |
| MBPP+ | — | 80.2% |

## Agentic & Tool Use

- GLM-5.3: 36.3 (#34)
- o1: 24.3 (#111)

| Benchmark | GLM-5.3 | o1 |
|---|---|---|
| APEX-Agents | 56.6% | — |
| Cybench | — | 10% |
| METR Time Horizons | — | 51.1% |
| Vending-Bench 2 | 8,164 | — |

## Reasoning

- GLM-5.3: 45.2 (#42)
- o1: 27.5 (#103)

| Benchmark | GLM-5.3 | o1 |
|---|---|---|
| Chess Puzzles | 21% | 15% |
| LMArena Hard Prompts | 1491 | 1372 |
| DTBench | 87.7% | 74.7% |
| LMCA | 55.5% | 22.3% |
| Epoch Capabilities Index | 155.56 | 141.92 |
| SimpleBench | — | 41.7% |
| NYT Connections (extended) | 74.2% | — |
| ARC-AGI-1 | — | 30.7% |
| CritPt | 19.1% | — |
| EnigmaEval | — | 5.7% |
| LiveBench Reasoning | — | 91.6% |
| Mystery Game Puzzles | 33% | — |
| LiveBench Data Analysis | — | 65.5% |
| Bench to the Future 3 | 0.15 | — |
| LiveBench | — | 75.7% |

## Math

- GLM-5.3: 62.1 (#27)
- o1: 34.9 (#150)

| Benchmark | GLM-5.3 | o1 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 68.8% | 14.7% |
| OTIS Mock AIME 2024-2025 | 91.1% | 73.3% |
| LMArena Math | 1493 | 1388 |
| FrontierMath Tier 4 | 29.3% | — |
| ProofBench | 49% | — |
| LiveBench Math | — | 80.3% |
| MATH Level 5 | — | 94.7% |
| FrontierMath (Feb 2025 set) | — | 9.3% |

## Knowledge

- GLM-5.3: 58.3 (#34)
- o1: 41.5 (#101)

| Benchmark | GLM-5.3 | o1 |
|---|---|---|
| GPQA Diamond | 90.9% | 76.8% |
| SimpleQA Verified | 41% | 41.1% |
| LMArena Expert | 1512 | 1362 |
| Humanity's Last Exam | — | 8% |
| Confabulations | — | 11.7% |

## Multimodal

- GLM-5.3: —
- o1: 33.6 (#87)

| Benchmark | GLM-5.3 | o1 |
|---|---|---|
| LMArena Vision | — | 1168 |
| GeoBench | — | 80% |
| VPCT | — | 37% |
| SpatialViz-Bench | — | 41.4% |

## Multilingual

- GLM-5.3: 55.9 (#27)
- o1: 48.8 (#137)

| Benchmark | GLM-5.3 | o1 |
|---|---|---|
| LMArena Non-English | 1457 | 1359 |
| LMArena Chinese | 1523 | 1394 |
| LMArena French | 1499 | 1343 |
| LMArena German | 1505 | 1337 |
| LMArena Japanese | 1438 | 1346 |
| LMArena Korean | 1478 | 1396 |
| LMArena Russian | 1460 | 1356 |
| LMArena Spanish | 1444 | 1345 |

## Instruction Following

- GLM-5.3: 77.8 (#15)
- o1: 75.0 (#82)

| Benchmark | GLM-5.3 | o1 |
|---|---|---|
| LMArena Instruction Following | 1481 | 1368 |
| LiveBench Instruction Following | — | 81.5% |

## Long Context

- GLM-5.3: 45.5 (#32)
- o1: 50.3 (#9)

| Benchmark | GLM-5.3 | o1 |
|---|---|---|
| LMArena Longer Query | 1485 | 1378 |
| Fiction.LiveBench | — | 83.3% |

## Writing & Preference

- GLM-5.3: 75.9 (#6)
- o1: 55.8 (#139)

| Benchmark | GLM-5.3 | o1 |
|---|---|---|
| LMArena Text | 1473 | 1366 |
| LMArena Creative Writing | 1459 | 1347 |
| LMArena Multi-Turn | 1473 | 1368 |
| Short-Story Creative Writing | — | 70.2% |
| EQ-Bench Creative Writing | 2075 | — |
| LiveBench Language | — | 65.4% |

## FAQ

### Is GLM-5.3 better than o1?

GLM-5.3 is the stronger model overall, scoring 54.6 to 40.6 on the Noometry Index.

### Which is cheaper, GLM-5.3 or o1?

GLM-5.3 is cheaper. It lists at $1.40 per million input tokens and $4.40 per million output tokens; o1 lists at $15 and $60.

### Is GLM-5.3 or o1 better for coding?

GLM-5.3 scores higher on coding benchmarks: 59.0 versus 45.7 in the Noometry coding category.

### Which has the bigger context window?

GLM-5.3 does, with 1M tokens against 200K.

### How many benchmarks do GLM-5.3 and o1 share?

26 benchmarks have published results for both models. GLM-5.3 has 41 scored results on Noometry and o1 has 52.