# GLM-4.7 vs Grok 4.5

> Grok 4.5 is the stronger model overall, scoring 55.0 to 41.7 on the Noometry Index. GLM-4.7 costs 3.0× less per token, which makes it the better buy when Grok 4.5's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/glm-4-7-vs-grok-4-5
- Last updated: 2026-10-10
- Shared benchmarks: 30

## Summary

- They share 30 benchmarks with published results for both. GLM-4.7 scores higher in 0 categories and Grok 4.5 in 9 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Grok 4.5 leads 56.0 to 23.7.
- The biggest single-benchmark swing is Chess Puzzles: 6% for GLM-4.7 and 36% for Grok 4.5.
- GLM-4.7 is cheaper at $0.60 / $2.20 per million input/output tokens, against $2 / $6 for Grok 4.5.
- Grok 4.5 accepts more context: 500K tokens versus 205K.
- GLM-4.7 has downloadable open weights; the other is API-only.

## Snapshot

| | GLM-4.7 | Grok 4.5 |
|---|---|---|
| Provider | Z.ai (Zhipu) | xAI |
| Noometry Index | 41.7 | 55.0 |
| Rank | 117 | 22 |
| Context | 205K | 500K |
| Input $/M | $0.60 | $2 |
| Output $/M | $2.20 | $6 |
| Weights | Open | Proprietary |

## Coding

- GLM-4.7: 43.6 (#74)
- Grok 4.5: 51.7 (#34)

| Benchmark | GLM-4.7 | Grok 4.5 |
|---|---|---|
| LMArena WebDev | 1435 | 1552 |
| SciCode | 45.1% | 54.1% |
| LMArena Coding | 1454 | 1473 |
| ALE-Bench | 399.48 | 1,309 |
| DeepSWE | — | 53.8% |
| FrontierCode | — | 42.4% |
| WeirdML | — | 46.4% |

## Agentic & Tool Use

- GLM-4.7: 26.4 (#96)
- Grok 4.5: 44.4 (#15)

| Benchmark | GLM-4.7 | Grok 4.5 |
|---|---|---|
| Vending-Bench 2 | 2,377 | 3,887 |
| Terminal-Bench | 33.4% | — |
| APEX-Agents | — | 56.2% |
| τ²-bench Banking | — | 47.9% |
| PostTrainBench | — | 23.4% |
| GBAEval | — | 65.4% |
| GDP.pdf | — | 14% |
| LMArena Search | — | 1213 |

## Reasoning

- GLM-4.7: 23.7 (#161)
- Grok 4.5: 56.0 (#23)

| Benchmark | GLM-4.7 | Grok 4.5 |
|---|---|---|
| SimpleBench | 47.7% | 70% |
| CritPt | 1.7% | 15.4% |
| Chess Puzzles | 6% | 36% |
| LMArena Hard Prompts | 1443 | 1462 |
| Epoch Capabilities Index | 143.53 | 154.02 |
| ARC-AGI-2 | — | 52.6% |
| Kagi LLM Benchmark | — | 83.5% |
| NYT Connections (extended) | — | 79.9% |
| ARC-AGI-1 | — | 87.2% |
| DTBench | — | 96.5% |
| LMCA | — | 45.2% |
| Surface Evolver Bench | — | 74.4% |

## Math

- GLM-4.7: 37.7 (#92)
- Grok 4.5: 60.7 (#29)

| Benchmark | GLM-4.7 | Grok 4.5 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 83.3% | 97.8% |
| ProofBench | 6% | 31% |
| LMArena Math | 1423 | 1457 |
| FrontierMath (Tiers 1-3) | — | 57.2% |
| FrontierMath Tier 4 | — | 24.4% |
| FrontierMath (Feb 2025 set) | 2.4% | — |
| FrontierMath Tier 4 (v1) | 0% | — |

## Knowledge

- GLM-4.7: 47.0 (#74)
- Grok 4.5: 62.3 (#21)

| Benchmark | GLM-4.7 | Grok 4.5 |
|---|---|---|
| GPQA Diamond | 83.3% | 93.4% |
| SimpleQA Verified | 32.2% | 48.3% |
| LMArena Expert | 1424 | 1466 |
| Vectara Hallucination Rate | 11.7% | — |

## Multimodal

- GLM-4.7: —
- Grok 4.5: 37.8 (#63)

| Benchmark | GLM-4.7 | Grok 4.5 |
|---|---|---|
| LMArena Vision | — | 1287 |
| Blueprint-Bench 2 | — | 27.3% |
| Furniture Assembly | — | 22.5% |
| LMArena Document | — | 1452 |

## Multilingual

- GLM-4.7: 53.0 (#75)
- Grok 4.5: 54.5 (#43)

| Benchmark | GLM-4.7 | Grok 4.5 |
|---|---|---|
| LMArena Non-English | 1417 | 1439 |
| LMArena Chinese | 1495 | 1497 |
| LMArena French | 1432 | 1458 |
| LMArena German | 1426 | 1448 |
| LMArena Japanese | 1439 | 1425 |
| LMArena Korean | 1401 | 1402 |
| LMArena Russian | 1423 | 1447 |
| LMArena Spanish | 1433 | 1452 |

## Instruction Following

- GLM-4.7: 74.6 (#90)
- Grok 4.5: 76.3 (#45)

| Benchmark | GLM-4.7 | Grok 4.5 |
|---|---|---|
| LMArena Instruction Following | 1411 | 1446 |

## Long Context

- GLM-4.7: 42.8 (#111)
- Grok 4.5: 44.8 (#54)

| Benchmark | GLM-4.7 | Grok 4.5 |
|---|---|---|
| LMArena Longer Query | 1432 | 1463 |
| CL-bench | 15.9% | — |
| CL-bench Life | 10.9% | — |

## Writing & Preference

- GLM-4.7: 61.1 (#89)
- Grok 4.5: 65.9 (#40)

| Benchmark | GLM-4.7 | Grok 4.5 |
|---|---|---|
| LMArena Text | 1436 | 1448 |
| LMArena Creative Writing | 1401 | 1442 |
| EQ-Bench Creative Writing | 1413 | 1579 |
| LMArena Multi-Turn | 1446 | 1457 |

## FAQ

### Is GLM-4.7 better than Grok 4.5?

Grok 4.5 is the stronger model overall, scoring 55.0 to 41.7 on the Noometry Index. GLM-4.7 costs 3.0× less per token, which makes it the better buy when Grok 4.5's lead doesn't matter for your workload.

### Which is cheaper, GLM-4.7 or Grok 4.5?

GLM-4.7 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; Grok 4.5 lists at $2 and $6.

### Is GLM-4.7 or Grok 4.5 better for coding?

Grok 4.5 scores higher on coding benchmarks: 51.7 versus 43.6 in the Noometry coding category.

### Which has the bigger context window?

Grok 4.5 does, with 500K tokens against 205K.

### How many benchmarks do GLM-4.7 and Grok 4.5 share?

30 benchmarks have published results for both models. GLM-4.7 has 36 scored results on Noometry and Grok 4.5 has 52.