Model comparison
GLM-4.5V vs GPT-4.1 nano
GLM-4.5V is the stronger model overall, scoring 39.2 to 27.7 on the Noometry Index. GPT-4.1 nano costs 5.1× less per token, which makes it the better buy when GLM-4.5V's lead doesn't matter for your workload.
Last verified . 14 shared benchmarks.
Summary
- They share 14 benchmarks with published results for both. GLM-4.5V scores higher in 9 categories and GPT-4.1 nano in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GLM-4.5V leads 26.5 to 8.6.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 59.8% for GLM-4.5V and 33.3% for GPT-4.1 nano.
- GPT-4.1 nano is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.60 / $1.80 for GLM-4.5V.
- GPT-4.1 nano accepts more context: 1.05M tokens versus 64K.
- GLM-4.5V has downloadable open weights; the other is API-only.
Side by side
| GLM-4.5V | GPT-4.1 nano | |
|---|---|---|
| Provider | Z.ai (Zhipu) | OpenAI |
| Noometry Index | 39.2 | 27.7 |
| Released | 2025-08-11 | 2025-04-14 |
| Weights | Open | Proprietary |
| Context window | 64K | 1.05M |
| Max output | 16K | 33K |
| Input $ / M tokens | $0.60 | $0.10 |
| Output $ / M tokens | $1.80 | $0.40 |
| Results tracked | 15 | 38 |
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Category by category
Coding GLM-4.5V leads
GLM-4.5V: 38.9 (#152), GPT-4.1 nano: 23.8 (#325)
| Benchmark | GLM-4.5V | GPT-4.1 nano |
|---|---|---|
| LMArena Coding | 1347 | 1306 |
| Aider Polyglot | — | 8.9% |
| SciCode | — | 25.9% |
| WeirdML | — | 19% |
Agentic & Tool Use Not comparable
GLM-4.5V: —, GPT-4.1 nano: 26.3 (#98)
| Benchmark | GLM-4.5V | GPT-4.1 nano |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 33% |
Reasoning GLM-4.5V leads
GLM-4.5V: 26.5 (#118), GPT-4.1 nano: 8.6 (#344)
| Benchmark | GLM-4.5V | GPT-4.1 nano |
|---|---|---|
| Kagi LLM Benchmark | 59.8% | 33.3% |
| LMArena Hard Prompts | 1335 | 1286 |
| ARC-AGI-2 | — | 0% |
| ARC-AGI-1 | — | 0% |
| CritPt | — | 0% |
| DTBench | — | 52.5% |
| LMCA | — | 5.5% |
| Epoch Capabilities Index | — | 129.62 |
Math GLM-4.5V leads
GLM-4.5V: 34.7 (#157), GPT-4.1 nano: 25.5 (#246)
| Benchmark | GLM-4.5V | GPT-4.1 nano |
|---|---|---|
| LMArena Math | 1353 | 1274 |
| OTIS Mock AIME 2024-2025 | — | 28.9% |
| Omni-MATH | — | 36.7% |
| MATH Level 5 | — | 70% |
| FrontierMath (Feb 2025 set) | — | 1% |
Knowledge GLM-4.5V leads
GLM-4.5V: 36.8 (#155), GPT-4.1 nano: 21.8 (#268)
| Benchmark | GLM-4.5V | GPT-4.1 nano |
|---|---|---|
| LMArena Expert | 1353 | 1272 |
| GPQA Diamond | — | 48.9% |
| SimpleQA Verified | — | 6% |
| MMLU-Pro | — | 55% |
| GPQA (HELM) | — | 50.7% |
Multimodal GLM-4.5V leads
GLM-4.5V: 33.6 (#86), GPT-4.1 nano: 28.6 (#108)
| Benchmark | GLM-4.5V | GPT-4.1 nano |
|---|---|---|
| LMArena Vision | 1154 | 1063 |
Multilingual GLM-4.5V leads
GLM-4.5V: 44.9 (#172), GPT-4.1 nano: 41.8 (#200)
| Benchmark | GLM-4.5V | GPT-4.1 nano |
|---|---|---|
| LMArena Non-English | 1304 | 1260 |
| LMArena Chinese | 1338 | 1270 |
| LMArena Russian | 1299 | 1261 |
| LMArena German | — | 1288 |
| LMArena Japanese | — | 1199 |
| LMArena Spanish | 1335 | — |
Instruction Following GLM-4.5V leads
GLM-4.5V: 69.4 (#170), GPT-4.1 nano: 68.0 (#188)
| Benchmark | GLM-4.5V | GPT-4.1 nano |
|---|---|---|
| LMArena Instruction Following | 1311 | 1267 |
| IFEval | — | 84.3% |
Long Context GLM-4.5V leads
GLM-4.5V: 39.6 (#166), GPT-4.1 nano: 23.7 (#291)
| Benchmark | GLM-4.5V | GPT-4.1 nano |
|---|---|---|
| LMArena Longer Query | 1305 | 1283 |
| Fiction.LiveBench | — | 25% |
Writing & Preference GLM-4.5V leads
GLM-4.5V: 52.7 (#162), GPT-4.1 nano: 40.7 (#238)
| Benchmark | GLM-4.5V | GPT-4.1 nano |
|---|---|---|
| LMArena Text | 1333 | 1285 |
| LMArena Creative Writing | 1295 | 1260 |
| LMArena Multi-Turn | 1333 | 1277 |
| EQ-Bench Creative Writing | — | 946 |
| WildBench | — | 81.2% |
Frequently asked questions
Is GLM-4.5V better than GPT-4.1 nano?
GLM-4.5V is the stronger model overall, scoring 39.2 to 27.7 on the Noometry Index. GPT-4.1 nano costs 5.1× less per token, which makes it the better buy when GLM-4.5V's lead doesn't matter for your workload.
Which is cheaper, GLM-4.5V 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-4.5V lists at $0.60 and $1.80.
Is GLM-4.5V or GPT-4.1 nano better for coding?
GLM-4.5V scores higher on coding benchmarks: 38.9 versus 23.8 in the Noometry coding category.
Which has the bigger context window?
GPT-4.1 nano does, with 1.05M tokens against 64K.
How many benchmarks do GLM-4.5V and GPT-4.1 nano share?
14 benchmarks have published results for both models. GLM-4.5V has 15 scored results on Noometry and GPT-4.1 nano has 38.