# GLM-5.2 vs Grok-2 (Dec 2024)

> GLM-5.2 is the stronger model overall, scoring 50.9 to 33.4 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-5-2-vs-grok-2
- Last updated: 2026-10-10
- Shared benchmarks: 23

## Summary

- They share 23 benchmarks with published results for both. GLM-5.2 scores higher in 8 categories and Grok-2 (Dec 2024) in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-5.2 leads 55.4 to 19.6.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 86.4% for GLM-5.2 and 11.5% for Grok-2 (Dec 2024).
- GLM-5.2 has downloadable open weights; the other is API-only.

## Snapshot

| | GLM-5.2 | Grok-2 (Dec 2024) |
|---|---|---|
| Provider | Z.ai (Zhipu) | xAI |
| Noometry Index | 50.9 | 33.4 |
| Rank | 38 | 233 |
| Context | 1M | — |
| Input $/M | $1.40 | — |
| Output $/M | $4.40 | — |
| Weights | Open | Proprietary |

## Coding

- GLM-5.2: 50.9 (#37)
- Grok-2 (Dec 2024): 32.9 (#254)

| Benchmark | GLM-5.2 | Grok-2 (Dec 2024) |
|---|---|---|
| WeirdML | 70.1% | 22.2% |
| LMArena Coding | 1484 | 1288 |
| SWE-bench Verified | 78.7% | — |
| DeepSWE | 43.8% | — |
| FrontierCode | 24.5% | — |
| LMArena WebDev | 1604 | — |
| SciCode | 50.5% | — |
| LiveBench Coding | — | 46.4% |
| ALE-Bench | 1,047 | — |

## Agentic & Tool Use

- GLM-5.2: 31.6 (#63)
- Grok-2 (Dec 2024): —

| Benchmark | GLM-5.2 | Grok-2 (Dec 2024) |
|---|---|---|
| τ²-bench Banking | 37.1% | — |
| PostTrainBench | 31.7% | — |
| GBAEval | 0% | — |
| Vending-Bench 2 | 8,314 | — |

## Reasoning

- GLM-5.2: 42.1 (#46)
- Grok-2 (Dec 2024): 16.4 (#294)

| Benchmark | GLM-5.2 | Grok-2 (Dec 2024) |
|---|---|---|
| SimpleBench | 58.8% | 22.7% |
| LMArena Hard Prompts | 1480 | 1272 |
| DTBench | 93.6% | 65.2% |
| Epoch Capabilities Index | 151.76 | 130.48 |
| ARC-AGI-2 | 22.8% | — |
| Kagi LLM Benchmark | 62.6% | — |
| NYT Connections (extended) | 74.3% | — |
| ARC-AGI-1 | 77% | — |
| CritPt | 20.9% | — |
| Chess Puzzles | 21% | — |
| EBR-Bench | 9.5% | — |
| LiveBench Reasoning | — | 54.8% |
| Mystery Game Puzzles | 19% | — |
| LiveBench Data Analysis | — | 54.5% |
| LMCA | 45.8% | — |
| Surface Evolver Bench | 55.6% | — |
| LiveBench | — | 54.3% |

## Math

- GLM-5.2: 55.4 (#35)
- Grok-2 (Dec 2024): 19.6 (#278)

| Benchmark | GLM-5.2 | Grok-2 (Dec 2024) |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 86.4% | 11.5% |
| LMArena Math | 1482 | 1283 |
| FrontierMath (Tiers 1-3) | 59.2% | — |
| FrontierMath Tier 4 | 29.3% | — |
| MathArena Final-Answer Competitions | 67.6% | — |
| ProofBench | 35% | — |
| LiveBench Math | — | 54.9% |
| MATH Level 5 | — | 63.5% |
| FrontierMath (Feb 2025 set) | — | 0.7% |

## Knowledge

- GLM-5.2: 57.1 (#36)
- Grok-2 (Dec 2024): 29.8 (#225)

| Benchmark | GLM-5.2 | Grok-2 (Dec 2024) |
|---|---|---|
| GPQA Diamond | 91.9% | 53.8% |
| LMArena Expert | 1484 | 1254 |
| SimpleQA Verified | 34.2% | — |
| Confabulations | — | 20.1% |

## Multilingual

- GLM-5.2: 56.0 (#25)
- Grok-2 (Dec 2024): 43.3 (#183)

| Benchmark | GLM-5.2 | Grok-2 (Dec 2024) |
|---|---|---|
| LMArena Non-English | 1459 | 1282 |
| LMArena Chinese | 1518 | 1289 |
| LMArena French | 1476 | 1317 |
| LMArena German | 1470 | 1287 |
| LMArena Japanese | 1451 | 1244 |
| LMArena Korean | 1445 | 1237 |
| LMArena Russian | 1467 | 1286 |
| LMArena Spanish | 1477 | 1281 |

## Instruction Following

- GLM-5.2: 77.1 (#32)
- Grok-2 (Dec 2024): 67.1 (#197)

| Benchmark | GLM-5.2 | Grok-2 (Dec 2024) |
|---|---|---|
| LMArena Instruction Following | 1465 | 1270 |
| LiveBench Instruction Following | — | 69.6% |

## Long Context

- GLM-5.2: 45.3 (#43)
- Grok-2 (Dec 2024): 38.7 (#186)

| Benchmark | GLM-5.2 | Grok-2 (Dec 2024) |
|---|---|---|
| LMArena Longer Query | 1479 | 1276 |

## Writing & Preference

- GLM-5.2: 70.7 (#20)
- Grok-2 (Dec 2024): 48.8 (#192)

| Benchmark | GLM-5.2 | Grok-2 (Dec 2024) |
|---|---|---|
| LMArena Text | 1470 | 1305 |
| LMArena Creative Writing | 1465 | 1284 |
| LMArena Multi-Turn | 1468 | 1290 |
| Short-Story Creative Writing | — | 63.6% |
| EQ-Bench Creative Writing | 1757 | — |
| EQ-Bench 4 | 1222 | — |
| LiveBench Language | — | 45.6% |

## FAQ

### Is GLM-5.2 better than Grok-2 (Dec 2024)?

GLM-5.2 is the stronger model overall, scoring 50.9 to 33.4 on the Noometry Index.

### Is GLM-5.2 or Grok-2 (Dec 2024) better for coding?

GLM-5.2 scores higher on coding benchmarks: 50.9 versus 32.9 in the Noometry coding category.

### How many benchmarks do GLM-5.2 and Grok-2 (Dec 2024) share?

23 benchmarks have published results for both models. GLM-5.2 has 50 scored results on Noometry and Grok-2 (Dec 2024) has 34.