Model comparison
GLM-4.5 vs GPT-4.1 nano
GLM-4.5 is the stronger model overall, scoring 42.0 to 27.9 on the Noometry Index. GPT-4.1 nano costs 5.7× less per token, which makes it the better buy when GLM-4.5's lead doesn't matter for your workload.
Last verified . 18 shared benchmarks.
Summary
- They share 18 benchmarks with published results for both. GLM-4.5 scores higher in 8 categories and GPT-4.1 nano in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GLM-4.5 leads 28.6 to 8.5.
- The biggest single-benchmark swing is Fiction.LiveBench: 58.3% for GLM-4.5 and 25% for GPT-4.1 nano.
- GPT-4.1 nano is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.60 / $2.20 for GLM-4.5.
- GPT-4.1 nano accepts more context: 1.05M tokens versus 131K.
- GLM-4.5 has downloadable open weights; the other is API-only.
Side by side
| GLM-4.5 | GPT-4.1 nano | |
|---|---|---|
| Provider | Z.ai (Zhipu) | OpenAI |
| Noometry Index | 42.0 | 27.9 |
| Released | 2025-07-27 | 2025-04-14 |
| Weights | Open | Proprietary |
| Context window | 131K | 1.05M |
| Max output | 98K | 33K |
| Input $ / M tokens | $0.60 | $0.10 |
| Output $ / M tokens | $2.20 | $0.40 |
| Results tracked | 27 | 38 |
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Category by category
Coding GLM-4.5 leads
GLM-4.5: 41.4 (#125), GPT-4.1 nano: 24.1 (#330)
| Benchmark | GLM-4.5 | GPT-4.1 nano |
|---|---|---|
| WeirdML | 40.6% | 19% |
| LMArena Coding | 1434 | 1306 |
| SWE-bench Verified (bash only) | 54.2% | — |
| Aider Polyglot | — | 8.9% |
| SciCode | — | 25.9% |
| ALE-Bench | 344.82 | — |
| AlgoTune | 1.52 | — |
Agentic & Tool Use Not comparable
GLM-4.5: —, GPT-4.1 nano: 26.5 (#104)
| Benchmark | GLM-4.5 | GPT-4.1 nano |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 33% |
Reasoning GLM-4.5 leads
GLM-4.5: 28.6 (#100), GPT-4.1 nano: 8.5 (#349)
| Benchmark | GLM-4.5 | GPT-4.1 nano |
|---|---|---|
| Kagi LLM Benchmark | 57.9% | 33.3% |
| LMArena Hard Prompts | 1429 | 1286 |
| ARC-AGI-2 | — | 0% |
| ARC-AGI-1 | — | 0% |
| CritPt | — | 0% |
| DTBench | — | 52.5% |
| LMCA | — | 5.5% |
| Epoch Capabilities Index | — | 129.62 |
Math GLM-4.5 leads
GLM-4.5: 39.0 (#116), GPT-4.1 nano: 26.9 (#252)
| Benchmark | GLM-4.5 | GPT-4.1 nano |
|---|---|---|
| LMArena Math | 1427 | 1274 |
| OTIS Mock AIME 2024-2025 | — | 28.9% |
| Omni-MATH | — | 36.7% |
| MATH Level 5 | — | 70% |
| FrontierMath (Feb 2025 set) | — | 1% |
Knowledge GLM-4.5 leads
GLM-4.5: 35.9 (#179), GPT-4.1 nano: 21.8 (#273)
| Benchmark | GLM-4.5 | GPT-4.1 nano |
|---|---|---|
| LMArena Expert | 1433 | 1272 |
| GPQA Diamond | — | 48.9% |
| Humanity's Last Exam | 8.3% | — |
| SimpleQA Verified | — | 6% |
| MMLU-Pro | — | 55% |
| Confabulations | 11.3% | — |
| GPQA (HELM) | — | 50.7% |
Multimodal Not comparable
GLM-4.5: —, GPT-4.1 nano: 29.2 (#113)
| Benchmark | GLM-4.5 | GPT-4.1 nano |
|---|---|---|
| LMArena Vision | — | 1063 |
Multilingual GLM-4.5 leads
GLM-4.5: 52.8 (#77), GPT-4.1 nano: 41.6 (#205)
| Benchmark | GLM-4.5 | GPT-4.1 nano |
|---|---|---|
| LMArena Non-English | 1417 | 1260 |
| LMArena Chinese | 1465 | 1270 |
| LMArena German | 1407 | 1288 |
| LMArena Japanese | 1415 | 1198 |
| LMArena Russian | 1414 | 1261 |
| LMArena French | 1418 | — |
| LMArena Korean | 1380 | — |
| LMArena Spanish | 1454 | — |
Instruction Following GLM-4.5 leads
GLM-4.5: 74.1 (#104), GPT-4.1 nano: 67.8 (#193)
| Benchmark | GLM-4.5 | GPT-4.1 nano |
|---|---|---|
| LMArena Instruction Following | 1404 | 1267 |
| IFEval | — | 84.3% |
Long Context GLM-4.5 leads
GLM-4.5: 38.2 (#201), GPT-4.1 nano: 23.7 (#296)
| Benchmark | GLM-4.5 | GPT-4.1 nano |
|---|---|---|
| Fiction.LiveBench | 58.3% | 25% |
| LMArena Longer Query | 1412 | 1283 |
Writing & Preference GLM-4.5 leads
GLM-4.5: 57.5 (#127), GPT-4.1 nano: 40.5 (#243)
| Benchmark | GLM-4.5 | GPT-4.1 nano |
|---|---|---|
| LMArena Text | 1430 | 1285 |
| LMArena Creative Writing | 1395 | 1260 |
| EQ-Bench Creative Writing | 1343 | 946 |
| LMArena Multi-Turn | 1415 | 1277 |
| Short-Story Creative Writing | 73.4% | — |
| WildBench | — | 81.2% |
Frequently asked questions
Is GLM-4.5 better than GPT-4.1 nano?
GLM-4.5 is the stronger model overall, scoring 42.0 to 27.9 on the Noometry Index. GPT-4.1 nano costs 5.7× less per token, which makes it the better buy when GLM-4.5's lead doesn't matter for your workload.
Which is cheaper, GLM-4.5 or GPT-4.1 nano?
GPT-4.1 nano is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; GLM-4.5 lists at $0.60 and $2.20.
Is GLM-4.5 or GPT-4.1 nano better for coding?
GLM-4.5 scores higher on coding benchmarks: 41.4 versus 24.1 in the Noometry coding category.
Which has the bigger context window?
GPT-4.1 nano does, with 1.05M tokens against 131K.
How many benchmarks do GLM-4.5 and GPT-4.1 nano share?
18 benchmarks have published results for both models. GLM-4.5 has 27 scored results on Noometry and GPT-4.1 nano has 38.