# Gemini 2.5 Pro vs GLM-5.3

> GLM-5.3 is the stronger model overall, scoring 54.6 to 44.9 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gemini-2-5-pro-vs-glm-5-3
- Last updated: 2026-10-10
- Shared benchmarks: 32

## Summary

- They share 32 benchmarks with published results for both. Gemini 2.5 Pro scores higher in 1 category and GLM-5.3 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-5.3 leads 62.1 to 31.9.
- The biggest single-benchmark swing is FrontierMath (Tiers 1-3): 24.6% for Gemini 2.5 Pro and 68.8% for GLM-5.3.
- GLM-5.3 is cheaper at $1.40 / $4.40 per million input/output tokens, against $1.25 / $10 for Gemini 2.5 Pro.
- Gemini 2.5 Pro accepts more context: 1.05M tokens versus 1M.
- GLM-5.3 has downloadable open weights; the other is API-only.

## Snapshot

| | Gemini 2.5 Pro | GLM-5.3 |
|---|---|---|
| Provider | Google | Z.ai (Zhipu) |
| Noometry Index | 44.9 | 54.6 |
| Rank | 67 | 25 |
| Context | 1.05M | 1M |
| Input $/M | $1.25 | $1.40 |
| Output $/M | $10 | $4.40 |
| Weights | Proprietary | Open |

## Coding

- Gemini 2.5 Pro: 42.8 (#86)
- GLM-5.3: 59.0 (#12)

| Benchmark | Gemini 2.5 Pro | GLM-5.3 |
|---|---|---|
| LMArena WebDev | 1227 | 1623 |
| SciCode | 42.8% | 59% |
| WeirdML | 54% | 75.4% |
| LMArena Coding | 1452 | 1499 |
| ALE-Bench | 785.52 | 1,317 |
| SWE-bench Verified | 57.6% | — |
| DeepSWE | — | 69% |
| FrontierCode | — | 40.1% |
| SWE-bench Verified (bash only) | 53.6% | — |
| Aider Polyglot | 83.1% | — |
| FrontierSWE | — | 30.2% |
| GSO | 3.9% | — |
| LiveBench Coding | 85.9% | — |
| CadEval | 64% | — |
| AlgoTune | 1.51 | — |

## Agentic & Tool Use

- Gemini 2.5 Pro: 29.1 (#81)
- GLM-5.3: 36.3 (#34)

| Benchmark | Gemini 2.5 Pro | GLM-5.3 |
|---|---|---|
| Vending-Bench 2 | 573.64 | 8,164 |
| Terminal-Bench | 32.6% | — |
| APEX-Agents | — | 56.6% |
| GDPval | 23.3% | — |
| Remote Labor Index | 0.8% | — |
| TheAgentCompany | 30.3% | — |
| τ²-bench Banking | 13.7% | — |
| DeepResearch Bench | 42.8% | — |
| BALROG | 43.3% | — |
| LMArena Search | 1142 | — |
| METR Time Horizons | 55.4% | — |

## Reasoning

- Gemini 2.5 Pro: 28.8 (#85)
- GLM-5.3: 45.2 (#42)

| Benchmark | Gemini 2.5 Pro | GLM-5.3 |
|---|---|---|
| CritPt | 2% | 19.1% |
| Chess Puzzles | 20% | 21% |
| LMArena Hard Prompts | 1455 | 1491 |
| DTBench | 82.4% | 87.7% |
| LMCA | 34.8% | 55.5% |
| Epoch Capabilities Index | 145.32 | 155.56 |
| ARC-AGI-2 | 4.9% | — |
| SimpleBench | 62.4% | — |
| Kagi LLM Benchmark | 70.3% | — |
| NYT Connections (extended) | — | 74.2% |
| ARC-AGI-1 | 41% | — |
| EnigmaEval | 5.6% | — |
| LiveBench Reasoning | 89.8% | — |
| Mystery Game Puzzles | — | 33% |
| LiveBench Data Analysis | 79.9% | — |
| Bench to the Future 3 | — | 0.15 |
| ForecastBench | 61.3 | — |
| LiveBench | 82.3% | — |

## Math

- Gemini 2.5 Pro: 31.9 (#191)
- GLM-5.3: 62.1 (#27)

| Benchmark | Gemini 2.5 Pro | GLM-5.3 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 24.6% | 68.8% |
| FrontierMath Tier 4 | 0% | 29.3% |
| OTIS Mock AIME 2024-2025 | 84.7% | 91.1% |
| LMArena Math | 1450 | 1493 |
| ProofBench | — | 49% |
| Omni-MATH | 41.6% | — |
| LiveBench Math | 90.2% | — |
| MATH Level 5 | 95.9% | — |
| FrontierMath (Feb 2025 set) | 14.1% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |

## Knowledge

- Gemini 2.5 Pro: 55.8 (#41)
- GLM-5.3: 58.3 (#34)

| Benchmark | Gemini 2.5 Pro | GLM-5.3 |
|---|---|---|
| GPQA Diamond | 85.3% | 90.9% |
| LMArena Expert | 1452 | 1512 |
| Humanity's Last Exam | 21.6% | — |
| SimpleQA Verified | — | 41% |
| MMLU-Pro | 86.3% | — |
| Confabulations | 10.6% | — |
| Vectara Hallucination Rate | 7% | — |
| GPQA (HELM) | 74.9% | — |

## Multimodal

- Gemini 2.5 Pro: 44.5 (#16)
- GLM-5.3: —

| Benchmark | Gemini 2.5 Pro | GLM-5.3 |
|---|---|---|
| LMArena Vision | 1263 | — |
| GeoBench | 86% | — |
| VPCT | 48% | — |
| LMArena Document | 1421 | — |
| SpatialViz-Bench | 44.7% | — |

## Multilingual

- Gemini 2.5 Pro: 55.5 (#30)
- GLM-5.3: 55.9 (#27)

| Benchmark | Gemini 2.5 Pro | GLM-5.3 |
|---|---|---|
| LMArena Non-English | 1452 | 1457 |
| LMArena Chinese | 1507 | 1523 |
| LMArena French | 1473 | 1499 |
| LMArena German | 1487 | 1505 |
| LMArena Japanese | 1462 | 1438 |
| LMArena Korean | 1435 | 1478 |
| LMArena Russian | 1460 | 1460 |
| LMArena Spanish | 1473 | 1444 |

## Instruction Following

- Gemini 2.5 Pro: 75.2 (#71)
- GLM-5.3: 77.8 (#15)

| Benchmark | Gemini 2.5 Pro | GLM-5.3 |
|---|---|---|
| LMArena Instruction Following | 1436 | 1481 |
| LiveBench Instruction Following | 80.6% | — |
| IFEval | 84% | — |

## Long Context

- Gemini 2.5 Pro: 59.7 (#5)
- GLM-5.3: 45.5 (#32)

| Benchmark | Gemini 2.5 Pro | GLM-5.3 |
|---|---|---|
| LMArena Longer Query | 1449 | 1485 |
| Fiction.LiveBench | 91.7% | — |

## Writing & Preference

- Gemini 2.5 Pro: 63.9 (#60)
- GLM-5.3: 75.9 (#6)

| Benchmark | Gemini 2.5 Pro | GLM-5.3 |
|---|---|---|
| LMArena Text | 1458 | 1473 |
| LMArena Creative Writing | 1453 | 1459 |
| EQ-Bench Creative Writing | 1421 | 2075 |
| LMArena Multi-Turn | 1453 | 1473 |
| Short-Story Creative Writing | 83.8% | — |
| WildBench | 85.7% | — |
| LiveBench Language | 67.8% | — |

## FAQ

### Is Gemini 2.5 Pro better than GLM-5.3?

GLM-5.3 is the stronger model overall, scoring 54.6 to 44.9 on the Noometry Index.

### Which is cheaper, Gemini 2.5 Pro or GLM-5.3?

GLM-5.3 is cheaper. It lists at $1.40 per million input tokens and $4.40 per million output tokens; Gemini 2.5 Pro lists at $1.25 and $10.

### Is Gemini 2.5 Pro or GLM-5.3 better for coding?

GLM-5.3 scores higher on coding benchmarks: 59.0 versus 42.8 in the Noometry coding category.

### Which has the bigger context window?

Gemini 2.5 Pro does, with 1.05M tokens against 1M.

### How many benchmarks do Gemini 2.5 Pro and GLM-5.3 share?

32 benchmarks have published results for both models. Gemini 2.5 Pro has 78 scored results on Noometry and GLM-5.3 has 41.