# Claude Sonnet 4 vs GLM-4.5V

> Claude Sonnet 4 is the stronger model overall, scoring 40.6 to 39.2 on the Noometry Index. GLM-4.5V costs 6.7× less per token, which makes it the better buy when Claude Sonnet 4's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/claude-sonnet-4-vs-glm-4-5v
- Last updated: 2026-10-10
- Shared benchmarks: 15

## Summary

- They share 15 benchmarks with published results for both. Claude Sonnet 4 scores higher in 6 categories and GLM-4.5V in 3 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in multimodal, where GLM-4.5V leads 33.6 to 25.6.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 73% for Claude Sonnet 4 and 59.8% for GLM-4.5V.
- GLM-4.5V is cheaper at $0.60 / $1.80 per million input/output tokens, against $3 / $15 for Claude Sonnet 4.
- Claude Sonnet 4 accepts more context: 200K tokens versus 64K.
- GLM-4.5V has downloadable open weights; the other is API-only.

## Snapshot

| | Claude Sonnet 4 | GLM-4.5V |
|---|---|---|
| Provider | Anthropic | Z.ai (Zhipu) |
| Noometry Index | 40.6 | 39.2 |
| Rank | 139 | 158 |
| Context | 200K | 64K |
| Input $/M | $3 | $0.60 |
| Output $/M | $15 | $1.80 |
| Weights | Proprietary | Open |

## Coding

- Claude Sonnet 4: 44.0 (#70)
- GLM-4.5V: 38.9 (#152)

| Benchmark | Claude Sonnet 4 | GLM-4.5V |
|---|---|---|
| LMArena Coding | 1414 | 1347 |
| SWE-bench Verified (bash only) | 64.9% | — |
| Aider Polyglot | 61.3% | — |
| SciCode | 40% | — |
| GSO | 4.9% | — |
| WeirdML | 46.1% | — |
| ALE-Bench | 655.35 | — |

## Agentic & Tool Use

- Claude Sonnet 4: 38.3 (#29)
- GLM-4.5V: —

| Benchmark | Claude Sonnet 4 | GLM-4.5V |
|---|---|---|
| TheAgentCompany | 33.1% | — |
| Cybench | 35% | — |
| DeepResearch Bench | 46.6% | — |
| OSWorld | 43.9% | — |
| METR Time Horizons | 62% | — |

## Reasoning

- Claude Sonnet 4: 23.0 (#169)
- GLM-4.5V: 26.5 (#118)

| Benchmark | Claude Sonnet 4 | GLM-4.5V |
|---|---|---|
| Kagi LLM Benchmark | 73% | 59.8% |
| LMArena Hard Prompts | 1372 | 1335 |
| ARC-AGI-2 | 5.9% | — |
| SimpleBench | 45.5% | — |
| ARC-AGI-1 | 40% | — |
| CritPt | 0.3% | — |
| EnigmaEval | 3.1% | — |
| DTBench | 77.1% | — |
| LMCA | 29% | — |
| Epoch Capabilities Index | 141.69 | — |
| ForecastBench | 60.2 | — |

## Math

- Claude Sonnet 4: 41.5 (#71)
- GLM-4.5V: 34.7 (#157)

| Benchmark | Claude Sonnet 4 | GLM-4.5V |
|---|---|---|
| LMArena Math | 1375 | 1353 |
| OTIS Mock AIME 2024-2025 | 71.1% | — |
| Omni-MATH | 60.2% | — |
| MATH Level 5 | 84.4% | — |
| FrontierMath (Feb 2025 set) | 4.1% | — |
| FrontierMath Tier 4 (v1) | 0% | — |

## Knowledge

- Claude Sonnet 4: 41.6 (#99)
- GLM-4.5V: 36.8 (#155)

| Benchmark | Claude Sonnet 4 | GLM-4.5V |
|---|---|---|
| LMArena Expert | 1371 | 1353 |
| GPQA Diamond | 79.2% | — |
| Humanity's Last Exam | 7.8% | — |
| MMLU-Pro | 84.3% | — |
| Confabulations | 13.2% | — |
| Vectara Hallucination Rate | 10.3% | — |
| GPQA (HELM) | 70.6% | — |

## Multimodal

- Claude Sonnet 4: 25.6 (#116)
- GLM-4.5V: 33.6 (#86)

| Benchmark | Claude Sonnet 4 | GLM-4.5V |
|---|---|---|
| LMArena Vision | 1191 | 1154 |
| GeoBench | 37% | — |
| VPCT | 34% | — |
| MindCube | 44.8% | — |

## Multilingual

- Claude Sonnet 4: 46.9 (#151)
- GLM-4.5V: 44.9 (#172)

| Benchmark | Claude Sonnet 4 | GLM-4.5V |
|---|---|---|
| LMArena Non-English | 1333 | 1304 |
| LMArena Chinese | 1351 | 1338 |
| LMArena Russian | 1355 | 1299 |
| LMArena Spanish | 1356 | 1335 |
| LMArena French | 1364 | — |
| LMArena German | 1331 | — |
| LMArena Japanese | 1301 | — |
| LMArena Korean | 1293 | — |

## Instruction Following

- Claude Sonnet 4: 71.8 (#141)
- GLM-4.5V: 69.4 (#170)

| Benchmark | Claude Sonnet 4 | GLM-4.5V |
|---|---|---|
| LMArena Instruction Following | 1375 | 1311 |
| IFEval | 84% | — |

## Long Context

- Claude Sonnet 4: 33.6 (#254)
- GLM-4.5V: 39.6 (#166)

| Benchmark | Claude Sonnet 4 | GLM-4.5V |
|---|---|---|
| LMArena Longer Query | 1398 | 1305 |
| Fiction.LiveBench | 46.9% | — |

## Writing & Preference

- Claude Sonnet 4: 57.3 (#127)
- GLM-4.5V: 52.7 (#162)

| Benchmark | Claude Sonnet 4 | GLM-4.5V |
|---|---|---|
| LMArena Text | 1351 | 1333 |
| LMArena Creative Writing | 1345 | 1295 |
| LMArena Multi-Turn | 1376 | 1333 |
| Short-Story Creative Writing | 81.4% | — |
| EQ-Bench Creative Writing | 1483 | — |
| WildBench | 83.8% | — |

## FAQ

### Is Claude Sonnet 4 better than GLM-4.5V?

Claude Sonnet 4 is the stronger model overall, scoring 40.6 to 39.2 on the Noometry Index. GLM-4.5V costs 6.7× less per token, which makes it the better buy when Claude Sonnet 4's lead doesn't matter for your workload.

### Which is cheaper, Claude Sonnet 4 or GLM-4.5V?

GLM-4.5V is cheaper. It lists at $0.60 per million input tokens and $1.80 per million output tokens; Claude Sonnet 4 lists at $3 and $15.

### Is Claude Sonnet 4 or GLM-4.5V better for coding?

Claude Sonnet 4 scores higher on coding benchmarks: 44.0 versus 38.9 in the Noometry coding category.

### Which has the bigger context window?

Claude Sonnet 4 does, with 200K tokens against 64K.

### How many benchmarks do Claude Sonnet 4 and GLM-4.5V share?

15 benchmarks have published results for both models. Claude Sonnet 4 has 58 scored results on Noometry and GLM-4.5V has 15.