# GLM-4.5V vs GLM-4.6

> GLM-4.6 is the stronger model overall, scoring 40.9 to 39.2 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-4-5v-vs-glm-4-6
- Last updated: 2026-10-10
- Shared benchmarks: 14

## Summary

- They share 14 benchmarks with published results for both. GLM-4.5V scores higher in 1 category and GLM-4.6 in 7 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in multilingual, where GLM-4.6 leads 53.6 to 44.9.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 59.8% for GLM-4.5V and 47.4% for GLM-4.6.
- GLM-4.5V is cheaper at $0.60 / $1.80 per million input/output tokens, against $0.60 / $2.20 for GLM-4.6.
- GLM-4.6 accepts more context: 205K tokens versus 64K.

## Snapshot

| | GLM-4.5V | GLM-4.6 |
|---|---|---|
| Provider | Z.ai (Zhipu) | Z.ai (Zhipu) |
| Noometry Index | 39.2 | 40.9 |
| Rank | 158 | 132 |
| Context | 64K | 205K |
| Input $/M | $0.60 | $0.60 |
| Output $/M | $1.80 | $2.20 |
| Weights | Open | Open |

## Coding

- GLM-4.5V: 38.9 (#152)
- GLM-4.6: 39.9 (#137)

| Benchmark | GLM-4.5V | GLM-4.6 |
|---|---|---|
| LMArena Coding | 1347 | 1449 |
| SWE-bench Verified (bash only) | — | 55.4% |
| LMArena WebDev | — | 1339 |
| SciCode | — | 38.4% |
| ALE-Bench | — | 340.82 |

## Agentic & Tool Use

- GLM-4.5V: —
- GLM-4.6: 32.1 (#60)

| Benchmark | GLM-4.5V | GLM-4.6 |
|---|---|---|
| Terminal-Bench | — | 24.5% |
| Berkeley Function Calling Leaderboard | — | 72.4% |

## Reasoning

- GLM-4.5V: 26.5 (#118)
- GLM-4.6: 23.1 (#168)

| Benchmark | GLM-4.5V | GLM-4.6 |
|---|---|---|
| Kagi LLM Benchmark | 59.8% | 47.4% |
| LMArena Hard Prompts | 1335 | 1440 |
| CritPt | — | 1.1% |

## Math

- GLM-4.5V: 34.7 (#157)
- GLM-4.6: 36.4 (#115)

| Benchmark | GLM-4.5V | GLM-4.6 |
|---|---|---|
| LMArena Math | 1353 | 1431 |
| FrontierMath (Feb 2025 set) | — | 3.8% |
| FrontierMath Tier 4 (v1) | — | 2.1% |

## Knowledge

- GLM-4.5V: 36.8 (#155)
- GLM-4.6: 39.6 (#118)

| Benchmark | GLM-4.5V | GLM-4.6 |
|---|---|---|
| LMArena Expert | 1353 | 1432 |
| Vectara Hallucination Rate | — | 9.5% |

## Multimodal

- GLM-4.5V: 33.6 (#86)
- GLM-4.6: —

| Benchmark | GLM-4.5V | GLM-4.6 |
|---|---|---|
| LMArena Vision | 1154 | — |

## Multilingual

- GLM-4.5V: 44.9 (#172)
- GLM-4.6: 53.6 (#62)

| Benchmark | GLM-4.5V | GLM-4.6 |
|---|---|---|
| LMArena Non-English | 1304 | 1426 |
| LMArena Chinese | 1338 | 1500 |
| LMArena Russian | 1299 | 1418 |
| LMArena Spanish | 1335 | 1436 |
| LMArena French | — | 1459 |
| LMArena German | — | 1447 |
| LMArena Japanese | — | 1394 |
| LMArena Korean | — | 1401 |

## Instruction Following

- GLM-4.5V: 69.4 (#170)
- GLM-4.6: 74.5 (#93)

| Benchmark | GLM-4.5V | GLM-4.6 |
|---|---|---|
| LMArena Instruction Following | 1311 | 1410 |

## Long Context

- GLM-4.5V: 39.6 (#166)
- GLM-4.6: 43.4 (#91)

| Benchmark | GLM-4.5V | GLM-4.6 |
|---|---|---|
| LMArena Longer Query | 1305 | 1423 |

## Writing & Preference

- GLM-4.5V: 52.7 (#162)
- GLM-4.6: 61.3 (#86)

| Benchmark | GLM-4.5V | GLM-4.6 |
|---|---|---|
| LMArena Text | 1333 | 1440 |
| LMArena Creative Writing | 1295 | 1411 |
| LMArena Multi-Turn | 1333 | 1427 |
| EQ-Bench Creative Writing | — | 1411 |

## FAQ

### Is GLM-4.5V better than GLM-4.6?

GLM-4.6 is the stronger model overall, scoring 40.9 to 39.2 on the Noometry Index.

### Which is cheaper, GLM-4.5V or GLM-4.6?

GLM-4.5V is cheaper. It lists at $0.60 per million input tokens and $1.80 per million output tokens; GLM-4.6 lists at $0.60 and $2.20.

### Is GLM-4.5V or GLM-4.6 better for coding?

GLM-4.6 scores higher on coding benchmarks: 39.9 versus 38.9 in the Noometry coding category.

### Which has the bigger context window?

GLM-4.6 does, with 205K tokens against 64K.

### How many benchmarks do GLM-4.5V and GLM-4.6 share?

14 benchmarks have published results for both models. GLM-4.5V has 15 scored results on Noometry and GLM-4.6 has 29.