# GLM-4.5V vs GPT-4.1

> GLM-4.5V is the stronger model overall, scoring 39.2 to 35.7 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-4-5v-vs-gpt-4-1
- Last updated: 2026-10-10
- Shared benchmarks: 15

## Summary

- They share 15 benchmarks with published results for both. GLM-4.5V scores higher in 3 categories and GPT-4.1 in 6 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GLM-4.5V leads 26.5 to 11.7.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 59.8% for GLM-4.5V and 52.3% for GPT-4.1.
- GLM-4.5V is cheaper at $0.60 / $1.80 per million input/output tokens, against $2 / $8 for GPT-4.1.
- GPT-4.1 accepts more context: 1.05M tokens versus 64K.
- GLM-4.5V has downloadable open weights; the other is API-only.

## Snapshot

| | GLM-4.5V | GPT-4.1 |
|---|---|---|
| Provider | Z.ai (Zhipu) | OpenAI |
| Noometry Index | 39.2 | 35.7 |
| Rank | 158 | 215 |
| Context | 64K | 1.05M |
| Input $/M | $0.60 | $2 |
| Output $/M | $1.80 | $8 |
| Weights | Open | Proprietary |

## Coding

- GLM-4.5V: 38.9 (#152)
- GPT-4.1: 34.2 (#228)

| Benchmark | GLM-4.5V | GPT-4.1 |
|---|---|---|
| LMArena Coding | 1347 | 1391 |
| SWE-bench Verified | — | 48.5% |
| SWE-bench Verified (bash only) | — | 39.6% |
| Aider Polyglot | — | 52.4% |
| WeirdML | — | 39% |
| CadEval | — | 42% |
| ALE-Bench | — | 558.1 |

## Agentic & Tool Use

- GLM-4.5V: —
- GPT-4.1: 34.4 (#40)

| Benchmark | GLM-4.5V | GPT-4.1 |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 54% |

## Reasoning

- GLM-4.5V: 26.5 (#118)
- GPT-4.1: 11.7 (#334)

| Benchmark | GLM-4.5V | GPT-4.1 |
|---|---|---|
| Kagi LLM Benchmark | 59.8% | 52.3% |
| LMArena Hard Prompts | 1335 | 1384 |
| ARC-AGI-2 | — | 0.4% |
| SimpleBench | — | 27% |
| ARC-AGI-1 | — | 5.5% |
| Chess Puzzles | — | 6% |
| EnigmaEval | — | 2.2% |
| DTBench | — | 68.3% |
| LMCA | — | 25.6% |
| Epoch Capabilities Index | — | 136.79 |
| ForecastBench | — | 61.5 |

## Math

- GLM-4.5V: 34.7 (#157)
- GPT-4.1: 21.4 (#269)

| Benchmark | GLM-4.5V | GPT-4.1 |
|---|---|---|
| LMArena Math | 1353 | 1369 |
| FrontierMath (Tiers 1-3) | — | 6% |
| OTIS Mock AIME 2024-2025 | — | 38.3% |
| Omni-MATH | — | 47.1% |
| MATH Level 5 | — | 83% |
| FrontierMath (Feb 2025 set) | — | 5.5% |
| FrontierMath Tier 4 (v1) | — | 0% |

## Knowledge

- GLM-4.5V: 36.8 (#155)
- GPT-4.1: 37.0 (#152)

| Benchmark | GLM-4.5V | GPT-4.1 |
|---|---|---|
| LMArena Expert | 1353 | 1364 |
| GPQA Diamond | — | 66.9% |
| Humanity's Last Exam | — | 5.4% |
| SimpleQA Verified | — | 31.1% |
| MMLU-Pro | — | 81.1% |
| Vectara Hallucination Rate | — | 5.6% |
| GPQA (HELM) | — | 65.9% |

## Multimodal

- GLM-4.5V: 33.6 (#86)
- GPT-4.1: 37.5 (#66)

| Benchmark | GLM-4.5V | GPT-4.1 |
|---|---|---|
| LMArena Vision | 1154 | 1210 |
| GeoBench | — | 72% |

## Multilingual

- GLM-4.5V: 44.9 (#172)
- GPT-4.1: 49.6 (#128)

| Benchmark | GLM-4.5V | GPT-4.1 |
|---|---|---|
| LMArena Non-English | 1304 | 1370 |
| LMArena Chinese | 1338 | 1382 |
| LMArena Russian | 1299 | 1377 |
| LMArena Spanish | 1335 | 1375 |
| LMArena French | — | 1383 |
| LMArena German | — | 1380 |
| LMArena Japanese | — | 1320 |
| LMArena Korean | — | 1339 |

## Instruction Following

- GLM-4.5V: 69.4 (#170)
- GPT-4.1: 71.5 (#148)

| Benchmark | GLM-4.5V | GPT-4.1 |
|---|---|---|
| LMArena Instruction Following | 1311 | 1367 |
| IFEval | — | 83.8% |

## Long Context

- GLM-4.5V: 39.6 (#166)
- GPT-4.1: 40.0 (#158)

| Benchmark | GLM-4.5V | GPT-4.1 |
|---|---|---|
| LMArena Longer Query | 1305 | 1385 |
| Fiction.LiveBench | — | 63.9% |

## Writing & Preference

- GLM-4.5V: 52.7 (#162)
- GPT-4.1: 57.8 (#120)

| Benchmark | GLM-4.5V | GPT-4.1 |
|---|---|---|
| LMArena Text | 1333 | 1383 |
| LMArena Creative Writing | 1295 | 1363 |
| LMArena Multi-Turn | 1333 | 1398 |
| EQ-Bench Creative Writing | — | 1420 |
| WildBench | — | 85.4% |

## FAQ

### Is GLM-4.5V better than GPT-4.1?

GLM-4.5V is the stronger model overall, scoring 39.2 to 35.7 on the Noometry Index.

### Which is cheaper, GLM-4.5V or GPT-4.1?

GLM-4.5V is cheaper. It lists at $0.60 per million input tokens and $1.80 per million output tokens; GPT-4.1 lists at $2 and $8.

### Is GLM-4.5V or GPT-4.1 better for coding?

GLM-4.5V scores higher on coding benchmarks: 38.9 versus 34.2 in the Noometry coding category.

### Which has the bigger context window?

GPT-4.1 does, with 1.05M tokens against 64K.

### How many benchmarks do GLM-4.5V and GPT-4.1 share?

15 benchmarks have published results for both models. GLM-4.5V has 15 scored results on Noometry and GPT-4.1 has 52.