# GLM-4.5 vs GPT-4.1 mini

> GLM-4.5 is the stronger model overall, scoring 42.0 to 33.6 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-4-5-vs-gpt-4-1-mini
- Last updated: 2026-10-12
- Shared benchmarks: 22

## Summary

- They share 22 benchmarks with published results for both. GLM-4.5 scores higher in 8 categories and GPT-4.1 mini in 0 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GLM-4.5 leads 28.6 to 10.8.
- The biggest single-benchmark swing is SWE-bench Verified (bash only): 54.2% for GLM-4.5 and 23.9% for GPT-4.1 mini.
- GPT-4.1 mini is cheaper at $0.40 / $1.60 per million input/output tokens, against $0.60 / $2.20 for GLM-4.5.
- GPT-4.1 mini accepts more context: 1.05M tokens versus 131K.
- GLM-4.5 has downloadable open weights; the other is API-only.

## Snapshot

| | GLM-4.5 | GPT-4.1 mini |
|---|---|---|
| Provider | Z.ai (Zhipu) | OpenAI |
| Noometry Index | 42.0 | 33.6 |
| Rank | 122 | 240 |
| Context | 131K | 1.05M |
| Input $/M | $0.60 | $0.40 |
| Output $/M | $2.20 | $1.60 |
| Weights | Open | Proprietary |

## Coding

- GLM-4.5: 41.4 (#125)
- GPT-4.1 mini: 30.6 (#293)

| Benchmark | GLM-4.5 | GPT-4.1 mini |
|---|---|---|
| SWE-bench Verified (bash only) | 54.2% | 23.9% |
| WeirdML | 40.6% | 37.6% |
| LMArena Coding | 1434 | 1367 |
| Aider Polyglot | — | 32.4% |
| SciCode | — | 40.4% |
| BigCodeBench Instruct | — | 48.9% |
| CadEval | — | 16% |
| ALE-Bench | 344.82 | — |
| AlgoTune | 1.52 | — |

## Agentic & Tool Use

- GLM-4.5: —
- GPT-4.1 mini: 33.3 (#55)

| Benchmark | GLM-4.5 | GPT-4.1 mini |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 50.5% |

## Reasoning

- GLM-4.5: 28.6 (#100)
- GPT-4.1 mini: 10.8 (#340)

| Benchmark | GLM-4.5 | GPT-4.1 mini |
|---|---|---|
| Kagi LLM Benchmark | 57.9% | 48.6% |
| LMArena Hard Prompts | 1429 | 1349 |
| ARC-AGI-2 | — | 0% |
| ARC-AGI-1 | — | 3.5% |
| CritPt | — | 0% |
| Chess Puzzles | — | 7% |
| Mystery Game Puzzles | — | 7% |
| DTBench | — | 68.8% |
| LMCA | — | 21.1% |
| Epoch Capabilities Index | — | 135.01 |

## Math

- GLM-4.5: 39.0 (#116)
- GPT-4.1 mini: 24.1 (#270)

| Benchmark | GLM-4.5 | GPT-4.1 mini |
|---|---|---|
| LMArena Math | 1427 | 1343 |
| FrontierMath (Tiers 1-3) | — | 6.7% |
| OTIS Mock AIME 2024-2025 | — | 44.7% |
| Omni-MATH | — | 49.1% |
| MATH Level 5 | — | 87.3% |
| FrontierMath (Feb 2025 set) | — | 4.5% |

## Knowledge

- GLM-4.5: 35.9 (#179)
- GPT-4.1 mini: 34.7 (#194)

| Benchmark | GLM-4.5 | GPT-4.1 mini |
|---|---|---|
| LMArena Expert | 1433 | 1338 |
| GPQA Diamond | — | 65.8% |
| Humanity's Last Exam | 8.3% | — |
| SimpleQA Verified | — | 12.7% |
| MMLU-Pro | — | 78.3% |
| Confabulations | 11.3% | — |
| GPQA (HELM) | — | 61.4% |

## Multimodal

- GLM-4.5: —
- GPT-4.1 mini: 35.8 (#82)

| Benchmark | GLM-4.5 | GPT-4.1 mini |
|---|---|---|
| LMArena Vision | — | 1181 |

## Multilingual

- GLM-4.5: 52.8 (#77)
- GPT-4.1 mini: 45.7 (#166)

| Benchmark | GLM-4.5 | GPT-4.1 mini |
|---|---|---|
| LMArena Non-English | 1417 | 1318 |
| LMArena Chinese | 1465 | 1329 |
| LMArena French | 1418 | 1358 |
| LMArena German | 1407 | 1351 |
| LMArena Japanese | 1415 | 1290 |
| LMArena Korean | 1380 | 1298 |
| LMArena Russian | 1414 | 1324 |
| LMArena Spanish | 1454 | 1319 |

## Instruction Following

- GLM-4.5: 74.1 (#104)
- GPT-4.1 mini: 73.7 (#118)

| Benchmark | GLM-4.5 | GPT-4.1 mini |
|---|---|---|
| LMArena Instruction Following | 1404 | 1333 |
| IFEval | — | 90.4% |

## Long Context

- GLM-4.5: 38.2 (#201)
- GPT-4.1 mini: 31.8 (#275)

| Benchmark | GLM-4.5 | GPT-4.1 mini |
|---|---|---|
| Fiction.LiveBench | 58.3% | 44.4% |
| LMArena Longer Query | 1412 | 1344 |

## Writing & Preference

- GLM-4.5: 57.5 (#127)
- GPT-4.1 mini: 48.6 (#199)

| Benchmark | GLM-4.5 | GPT-4.1 mini |
|---|---|---|
| LMArena Text | 1430 | 1340 |
| LMArena Creative Writing | 1395 | 1300 |
| EQ-Bench Creative Writing | 1343 | 1147 |
| LMArena Multi-Turn | 1415 | 1354 |
| Short-Story Creative Writing | 73.4% | — |
| WildBench | — | 83.8% |

## FAQ

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

GLM-4.5 is the stronger model overall, scoring 42.0 to 33.6 on the Noometry Index.

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

GPT-4.1 mini is cheaper. It lists at $0.40 per million input tokens and $1.60 per million output tokens; GLM-4.5 lists at $0.60 and $2.20.

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

GLM-4.5 scores higher on coding benchmarks: 41.4 versus 30.6 in the Noometry coding category.

### Which has the bigger context window?

GPT-4.1 mini does, with 1.05M tokens against 131K.

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

22 benchmarks have published results for both models. GLM-4.5 has 27 scored results on Noometry and GPT-4.1 mini has 47.