# GLM-5.3 vs Grok 4.20 Multi-Agent

> GLM-5.3 is the stronger model overall, scoring 54.6 to 45.5 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-5-3-vs-grok-4-20-multi-agent
- Last updated: 2026-10-10
- Shared benchmarks: 18

## Summary

- They share 18 benchmarks with published results for both. GLM-5.3 scores higher in 8 categories and Grok 4.20 Multi-Agent in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-5.3 leads 62.1 to 36.6.
- The biggest single-benchmark swing is NYT Connections (extended): 74.2% for GLM-5.3 and 89.6% for Grok 4.20 Multi-Agent.
- Grok 4.20 Multi-Agent is cheaper at $1.25 / $2.50 per million input/output tokens, against $1.40 / $4.40 for GLM-5.3.
- GLM-5.3 has downloadable open weights; the other is API-only.

## Snapshot

| | GLM-5.3 | Grok 4.20 Multi-Agent |
|---|---|---|
| Provider | Z.ai (Zhipu) | xAI |
| Noometry Index | 54.6 | 45.5 |
| Rank | 25 | 62 |
| Context | 1M | 1M |
| Input $/M | $1.40 | $1.25 |
| Output $/M | $4.40 | $2.50 |
| Weights | Open | Proprietary |

## Coding

- GLM-5.3: 59.0 (#12)
- Grok 4.20 Multi-Agent: 42.4 (#91)

| Benchmark | GLM-5.3 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Coding | 1499 | 1458 |
| DeepSWE | 69% | — |
| FrontierCode | 40.1% | — |
| LMArena WebDev | 1623 | — |
| FrontierSWE | 30.2% | — |
| SciCode | 59% | — |
| WeirdML | 75.4% | — |
| ALE-Bench | 1,317 | — |

## Agentic & Tool Use

- GLM-5.3: 36.3 (#34)
- Grok 4.20 Multi-Agent: —

| Benchmark | GLM-5.3 | Grok 4.20 Multi-Agent |
|---|---|---|
| APEX-Agents | 56.6% | — |
| LMArena Search | — | 1204 |
| Vending-Bench 2 | 8,164 | — |

## Reasoning

- GLM-5.3: 45.2 (#42)
- Grok 4.20 Multi-Agent: 42.4 (#44)

| Benchmark | GLM-5.3 | Grok 4.20 Multi-Agent |
|---|---|---|
| NYT Connections (extended) | 74.2% | 89.6% |
| LMArena Hard Prompts | 1491 | 1448 |
| CritPt | 19.1% | — |
| Chess Puzzles | 21% | — |
| Mystery Game Puzzles | 33% | — |
| DTBench | 87.7% | — |
| LMCA | 55.5% | — |
| Bench to the Future 3 | 0.15 | — |
| Epoch Capabilities Index | 155.56 | — |

## Math

- GLM-5.3: 62.1 (#27)
- Grok 4.20 Multi-Agent: 36.6 (#106)

| Benchmark | GLM-5.3 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Math | 1493 | 1441 |
| FrontierMath (Tiers 1-3) | 68.8% | — |
| FrontierMath Tier 4 | 29.3% | — |
| OTIS Mock AIME 2024-2025 | 91.1% | — |
| ProofBench | 49% | — |

## Knowledge

- GLM-5.3: 58.3 (#34)
- Grok 4.20 Multi-Agent: 39.7 (#116)

| Benchmark | GLM-5.3 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Expert | 1512 | 1445 |
| GPQA Diamond | 90.9% | — |
| SimpleQA Verified | 41% | — |

## Multimodal

- GLM-5.3: —
- Grok 4.20 Multi-Agent: 39.8 (#44)

| Benchmark | GLM-5.3 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Vision | — | 1259 |

## Multilingual

- GLM-5.3: 55.9 (#27)
- Grok 4.20 Multi-Agent: 54.6 (#40)

| Benchmark | GLM-5.3 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Non-English | 1457 | 1440 |
| LMArena Chinese | 1523 | 1475 |
| LMArena French | 1499 | 1467 |
| LMArena German | 1505 | 1456 |
| LMArena Japanese | 1438 | 1405 |
| LMArena Korean | 1478 | 1416 |
| LMArena Russian | 1460 | 1457 |
| LMArena Spanish | 1444 | 1447 |

## Instruction Following

- GLM-5.3: 77.8 (#15)
- Grok 4.20 Multi-Agent: 75.0 (#80)

| Benchmark | GLM-5.3 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Instruction Following | 1481 | 1420 |

## Long Context

- GLM-5.3: 45.5 (#32)
- Grok 4.20 Multi-Agent: 43.7 (#84)

| Benchmark | GLM-5.3 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Longer Query | 1485 | 1430 |

## Writing & Preference

- GLM-5.3: 75.9 (#6)
- Grok 4.20 Multi-Agent: 64.1 (#57)

| Benchmark | GLM-5.3 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Text | 1473 | 1450 |
| LMArena Creative Writing | 1459 | 1435 |
| LMArena Multi-Turn | 1473 | 1451 |
| EQ-Bench Creative Writing | 2075 | — |

## FAQ

### Is GLM-5.3 better than Grok 4.20 Multi-Agent?

GLM-5.3 is the stronger model overall, scoring 54.6 to 45.5 on the Noometry Index.

### Which is cheaper, GLM-5.3 or Grok 4.20 Multi-Agent?

Grok 4.20 Multi-Agent is cheaper. It lists at $1.25 per million input tokens and $2.50 per million output tokens; GLM-5.3 lists at $1.40 and $4.40.

### Is GLM-5.3 or Grok 4.20 Multi-Agent better for coding?

GLM-5.3 scores higher on coding benchmarks: 59.0 versus 42.4 in the Noometry coding category.

### Which has the bigger context window?

Both accept 1M tokens.

### How many benchmarks do GLM-5.3 and Grok 4.20 Multi-Agent share?

18 benchmarks have published results for both models. GLM-5.3 has 41 scored results on Noometry and Grok 4.20 Multi-Agent has 20.