# GLM-5 vs Grok 4.20 (Non-Reasoning)

> Grok 4.20 (Non-Reasoning) is the stronger model overall, scoring 48.6 to 46.1 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-5-vs-grok-4-20
- Last updated: 2026-10-11
- Shared benchmarks: 34

## Summary

- They share 34 benchmarks with published results for both. GLM-5 scores higher in 3 categories and Grok 4.20 (Non-Reasoning) in 6 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Grok 4.20 (Non-Reasoning) leads 52.3 to 27.6.
- The biggest single-benchmark swing is ARC-AGI-2: 4.9% for GLM-5 and 65.1% for Grok 4.20 (Non-Reasoning).
- Both cost about the same: $1 input and $3.20 output per million tokens.
- Grok 4.20 (Non-Reasoning) accepts more context: 1M tokens versus 205K.
- GLM-5 has downloadable open weights; the other is API-only.

## Snapshot

| | GLM-5 | Grok 4.20 (Non-Reasoning) |
|---|---|---|
| Provider | Z.ai (Zhipu) | xAI |
| Noometry Index | 46.1 | 48.6 |
| Rank | 66 | 54 |
| Context | 205K | 1M |
| Input $/M | $1 | $1.25 |
| Output $/M | $3.20 | $2.50 |
| Weights | Open | Proprietary |

## Coding

- GLM-5: 49.0 (#52)
- Grok 4.20 (Non-Reasoning): 42.1 (#112)

| Benchmark | GLM-5 | Grok 4.20 (Non-Reasoning) |
|---|---|---|
| LMArena WebDev | 1434 | 1375 |
| WeirdML | 48.2% | 52.3% |
| LMArena Coding | 1461 | 1459 |
| ALE-Bench | 765.62 | 1,150 |
| SWE-bench Verified | 72.1% | — |
| SWE-bench Verified (bash only) | 72.8% | — |
| SWE-bench Multilingual | 69.7% | — |

## Agentic & Tool Use

- GLM-5: 31.1 (#71)
- Grok 4.20 (Non-Reasoning): 34.4 (#46)

| Benchmark | GLM-5 | Grok 4.20 (Non-Reasoning) |
|---|---|---|
| Terminal-Bench | 52.4% | 57.3% |
| τ²-bench Banking | 9.8% | 18% |
| Vending-Bench 2 | 4,432 | 4,663 |
| τ²-bench Airline | 82.5% | — |
| τ²-bench Retail | 73.7% | — |
| τ²-bench Telecom | 86.8% | — |
| LMArena Search | — | 1189 |

## Reasoning

- GLM-5: 27.6 (#116)
- Grok 4.20 (Non-Reasoning): 52.3 (#32)

| Benchmark | GLM-5 | Grok 4.20 (Non-Reasoning) |
|---|---|---|
| ARC-AGI-2 | 4.9% | 65.1% |
| Kagi LLM Benchmark | 75% | 75% |
| NYT Connections (extended) | 74.8% | 85.4% |
| ARC-AGI-1 | 44.7% | 89.5% |
| Chess Puzzles | 10% | 24% |
| LMArena Hard Prompts | 1452 | 1451 |
| Epoch Capabilities Index | 145.83 | 151.98 |
| ForecastBench | 61 | 61.4 |
| SimpleBench | 53.2% | — |
| Thematic Generalization | — | 63.8% |
| DTBench | — | 90.1% |
| LMCA | — | 38.7% |

## Math

- GLM-5: 46.4 (#71)
- Grok 4.20 (Non-Reasoning): 48.2 (#65)

| Benchmark | GLM-5 | Grok 4.20 (Non-Reasoning) |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 80% | 92.2% |
| LMArena Math | 1440 | 1455 |
| FrontierMath (Tiers 1-3) | — | 44.9% |
| FrontierMath Tier 4 | — | 17.1% |
| MathArena Final-Answer Competitions | 65.7% | — |
| ProofBench | — | 14% |
| FrontierMath (Feb 2025 set) | 16.4% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |

## Knowledge

- GLM-5: 52.3 (#64)
- Grok 4.20 (Non-Reasoning): 52.8 (#60)

| Benchmark | GLM-5 | Grok 4.20 (Non-Reasoning) |
|---|---|---|
| GPQA Diamond | 87.8% | 89.3% |
| LMArena Expert | 1454 | 1439 |
| SimpleQA Verified | — | 30.2% |
| Vectara Hallucination Rate | 10.1% | — |

## Multimodal

- GLM-5: —
- Grok 4.20 (Non-Reasoning): 33.3 (#98)

| Benchmark | GLM-5 | Grok 4.20 (Non-Reasoning) |
|---|---|---|
| LMArena Vision | — | 1263 |
| Blueprint-Bench 2 | — | 0% |
| LMArena Document | — | 1416 |

## Multilingual

- GLM-5: 53.7 (#58)
- Grok 4.20 (Non-Reasoning): 54.5 (#40)

| Benchmark | GLM-5 | Grok 4.20 (Non-Reasoning) |
|---|---|---|
| LMArena Non-English | 1430 | 1441 |
| LMArena Chinese | 1511 | 1481 |
| LMArena French | 1455 | 1476 |
| LMArena German | 1445 | 1465 |
| LMArena Japanese | 1416 | 1449 |
| LMArena Korean | 1423 | 1417 |
| LMArena Russian | 1436 | 1458 |
| LMArena Spanish | 1454 | 1443 |

## Instruction Following

- GLM-5: 75.2 (#67)
- Grok 4.20 (Non-Reasoning): 74.8 (#83)

| Benchmark | GLM-5 | Grok 4.20 (Non-Reasoning) |
|---|---|---|
| LMArena Instruction Following | 1428 | 1420 |

## Long Context

- GLM-5: 44.7 (#60)
- Grok 4.20 (Non-Reasoning): 45.5 (#34)

| Benchmark | GLM-5 | Grok 4.20 (Non-Reasoning) |
|---|---|---|
| CL-bench | 18.7% | 22.2% |
| LMArena Longer Query | 1446 | 1437 |
| CL-bench Life | — | 11.9% |

## Writing & Preference

- GLM-5: 66.0 (#38)
- Grok 4.20 (Non-Reasoning): 65.7 (#44)

| Benchmark | GLM-5 | Grok 4.20 (Non-Reasoning) |
|---|---|---|
| LMArena Text | 1446 | 1451 |
| LMArena Creative Writing | 1439 | 1438 |
| EQ-Bench Creative Writing | 1601 | 1574 |
| LMArena Multi-Turn | 1456 | 1456 |

## FAQ

### Is GLM-5 better than Grok 4.20 (Non-Reasoning)?

Grok 4.20 (Non-Reasoning) is the stronger model overall, scoring 48.6 to 46.1 on the Noometry Index.

### Which is cheaper, GLM-5 or Grok 4.20 (Non-Reasoning)?

GLM-5 is cheaper. It lists at $1 per million input tokens and $3.20 per million output tokens; Grok 4.20 (Non-Reasoning) lists at $1.25 and $2.50.

### Is GLM-5 or Grok 4.20 (Non-Reasoning) better for coding?

GLM-5 scores higher on coding benchmarks: 49.0 versus 42.1 in the Noometry coding category.

### Which has the bigger context window?

Grok 4.20 (Non-Reasoning) does, with 1M tokens against 205K.

### How many benchmarks do GLM-5 and Grok 4.20 (Non-Reasoning) share?

34 benchmarks have published results for both models. GLM-5 has 45 scored results on Noometry and Grok 4.20 (Non-Reasoning) has 46.