Model comparison
GLM-4.5-Air vs GPT-4.1 mini
GLM-4.5-Air is the stronger model overall, scoring 38.9 to 33.6 on the Noometry Index.
Last verified . 23 shared benchmarks.
Summary
- They share 23 benchmarks with published results for both. GLM-4.5-Air scores higher in 7 categories and GPT-4.1 mini in 1 category; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GLM-4.5-Air leads 24.1 to 10.8.
- The biggest single-benchmark swing is Omni-MATH: 39.1% for GLM-4.5-Air and 49.1% for GPT-4.1 mini.
- GLM-4.5-Air is cheaper at $0.20 / $1.10 per million input/output tokens, against $0.40 / $1.60 for GPT-4.1 mini.
- GPT-4.1 mini accepts more context: 1.05M tokens versus 131K.
- GLM-4.5-Air has downloadable open weights; the other is API-only.
Side by side
| GLM-4.5-Air | GPT-4.1 mini | |
|---|---|---|
| Provider | Z.ai (Zhipu) | OpenAI |
| Noometry Index | 38.9 | 33.6 |
| Released | 2025-07-20 | 2025-04-14 |
| Weights | Open | Proprietary |
| Context window | 131K | 1.05M |
| Max output | 98K | 33K |
| Input $ / M tokens | $0.20 | $0.40 |
| Output $ / M tokens | $1.10 | $1.60 |
| Results tracked | 27 | 47 |
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Category by category
Coding GLM-4.5-Air leads
GLM-4.5-Air: 33.3 (#259), GPT-4.1 mini: 30.6 (#293)
| Benchmark | GLM-4.5-Air | GPT-4.1 mini |
|---|---|---|
| LMArena Coding | 1397 | 1367 |
| SWE-bench Verified (bash only) | — | 23.9% |
| Aider Polyglot | — | 32.4% |
| SciCode | — | 40.4% |
| GSO | 2.9% | — |
| WeirdML | — | 37.6% |
| BigCodeBench Instruct | — | 48.9% |
| CadEval | — | 16% |
Agentic & Tool Use Not comparable
GLM-4.5-Air: —, GPT-4.1 mini: 33.3 (#55)
| Benchmark | GLM-4.5-Air | GPT-4.1 mini |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 50.5% |
Reasoning GLM-4.5-Air leads
GLM-4.5-Air: 24.1 (#166), GPT-4.1 mini: 10.8 (#340)
| Benchmark | GLM-4.5-Air | GPT-4.1 mini |
|---|---|---|
| Kagi LLM Benchmark | 43% | 48.6% |
| LMArena Hard Prompts | 1379 | 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 |
| ForecastBench | 59.2 | — |
Math GLM-4.5-Air leads
GLM-4.5-Air: 36.2 (#170), GPT-4.1 mini: 24.1 (#270)
| Benchmark | GLM-4.5-Air | GPT-4.1 mini |
|---|---|---|
| Omni-MATH | 39.1% | 49.1% |
| LMArena Math | 1396 | 1343 |
| FrontierMath (Tiers 1-3) | — | 6.7% |
| OTIS Mock AIME 2024-2025 | — | 44.7% |
| MATH Level 5 | — | 87.3% |
| FrontierMath (Feb 2025 set) | — | 4.5% |
Knowledge Too close to call
GLM-4.5-Air: 35.0 (#191), GPT-4.1 mini: 34.7 (#194)
| Benchmark | GLM-4.5-Air | GPT-4.1 mini |
|---|---|---|
| MMLU-Pro | 76.2% | 78.3% |
| GPQA (HELM) | 59.4% | 61.4% |
| LMArena Expert | 1370 | 1338 |
| GPQA Diamond | — | 65.8% |
| Humanity's Last Exam | 8.1% | — |
| SimpleQA Verified | — | 12.7% |
| Vectara Hallucination Rate | 9.3% | — |
Multimodal Not comparable
GLM-4.5-Air: —, GPT-4.1 mini: 35.8 (#82)
| Benchmark | GLM-4.5-Air | GPT-4.1 mini |
|---|---|---|
| LMArena Vision | — | 1181 |
Multilingual GLM-4.5-Air leads
GLM-4.5-Air: 49.1 (#135), GPT-4.1 mini: 45.7 (#166)
| Benchmark | GLM-4.5-Air | GPT-4.1 mini |
|---|---|---|
| LMArena Non-English | 1366 | 1318 |
| LMArena Chinese | 1426 | 1329 |
| LMArena French | 1399 | 1358 |
| LMArena German | 1377 | 1351 |
| LMArena Japanese | 1348 | 1290 |
| LMArena Korean | 1308 | 1298 |
| LMArena Russian | 1373 | 1324 |
| LMArena Spanish | 1386 | 1319 |
Instruction Following GPT-4.1 mini leads
GLM-4.5-Air: 69.6 (#171), GPT-4.1 mini: 73.7 (#118)
| Benchmark | GLM-4.5-Air | GPT-4.1 mini |
|---|---|---|
| IFEval | 81.2% | 90.4% |
| LMArena Instruction Following | 1354 | 1333 |
Long Context GLM-4.5-Air leads
GLM-4.5-Air: 41.6 (#135), GPT-4.1 mini: 31.8 (#275)
| Benchmark | GLM-4.5-Air | GPT-4.1 mini |
|---|---|---|
| LMArena Longer Query | 1366 | 1344 |
| Fiction.LiveBench | — | 44.4% |
Writing & Preference GLM-4.5-Air leads
GLM-4.5-Air: 55.9 (#139), GPT-4.1 mini: 48.6 (#199)
| Benchmark | GLM-4.5-Air | GPT-4.1 mini |
|---|---|---|
| LMArena Text | 1384 | 1340 |
| LMArena Creative Writing | 1343 | 1300 |
| WildBench | 78.9% | 83.8% |
| LMArena Multi-Turn | 1371 | 1354 |
| EQ-Bench Creative Writing | — | 1147 |
Frequently asked questions
Is GLM-4.5-Air better than GPT-4.1 mini?
GLM-4.5-Air is the stronger model overall, scoring 38.9 to 33.6 on the Noometry Index.
Which is cheaper, GLM-4.5-Air or GPT-4.1 mini?
GLM-4.5-Air is cheaper. It lists at $0.20 per million input tokens and $1.10 per million output tokens; GPT-4.1 mini lists at $0.40 and $1.60.
Is GLM-4.5-Air or GPT-4.1 mini better for coding?
GLM-4.5-Air scores higher on coding benchmarks: 33.3 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-Air and GPT-4.1 mini share?
23 benchmarks have published results for both models. GLM-4.5-Air has 27 scored results on Noometry and GPT-4.1 mini has 47.