Model comparison
Gemini 1.5 Pro (May 2024) vs GLM-4.5
GLM-4.5 is the stronger model overall, scoring 42.0 to 32.1 on the Noometry Index.
Last verified . 20 shared benchmarks.
GoogleSummary
- They share 20 benchmarks with published results for both. Gemini 1.5 Pro (May 2024) scores higher in 1 category and GLM-4.5 in 7 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GLM-4.5 leads 28.6 to 12.3.
- The biggest single-benchmark swing is WeirdML: 22.2% for Gemini 1.5 Pro (May 2024) and 40.6% for GLM-4.5.
- GLM-4.5 has downloadable open weights; the other is API-only.
Side by side
| Gemini 1.5 Pro (May 2024) | GLM-4.5 | |
|---|---|---|
| Provider | Z.ai (Zhipu) | |
| Noometry Index | 32.1 | 42.0 |
| Released | 2024-02-15 | 2025-07-27 |
| Weights | Proprietary | Open |
| Context window | — | 131K |
| Max output | — | 98K |
| Input $ / M tokens | — | $0.60 |
| Output $ / M tokens | — | $2.20 |
| Results tracked | 45 | 27 |
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Category by category
Coding GLM-4.5 leads
Gemini 1.5 Pro (May 2024): 34.2 (#241), GLM-4.5: 41.4 (#125)
| Benchmark | Gemini 1.5 Pro (May 2024) | GLM-4.5 |
|---|---|---|
| WeirdML | 22.2% | 40.6% |
| LMArena Coding | 1294 | 1434 |
| SWE-bench Verified (bash only) | — | 54.2% |
| BigCodeBench Instruct | 43.8% | — |
| BigCodeBench Complete | 57.5% | — |
| CadEval | 34% | — |
| ALE-Bench | — | 344.82 |
| AlgoTune | — | 1.52 |
| HumanEval+ | 79.3% | — |
| MBPP+ | 74.6% | — |
Agentic & Tool Use Not comparable
Gemini 1.5 Pro (May 2024): 17.9 (#145), GLM-4.5: —
| Benchmark | Gemini 1.5 Pro (May 2024) | GLM-4.5 |
|---|---|---|
| TheAgentCompany | 3.4% | — |
| Cybench | 7.5% | — |
| BALROG | 21% | — |
Reasoning GLM-4.5 leads
Gemini 1.5 Pro (May 2024): 12.3 (#338), GLM-4.5: 28.6 (#100)
| Benchmark | Gemini 1.5 Pro (May 2024) | GLM-4.5 |
|---|---|---|
| LMArena Hard Prompts | 1296 | 1429 |
| ARC-AGI-2 | 0.8% | — |
| SimpleBench | 27.1% | — |
| Kagi LLM Benchmark | — | 57.9% |
| DTBench | 59% | — |
| BIG-Bench Hard | 89.2% | — |
| Epoch Capabilities Index | 131.73 | — |
| ForecastBench | 58.4 | — |
Math GLM-4.5 leads
Gemini 1.5 Pro (May 2024): 25.8 (#266), GLM-4.5: 39.0 (#116)
| Benchmark | Gemini 1.5 Pro (May 2024) | GLM-4.5 |
|---|---|---|
| LMArena Math | 1315 | 1427 |
| OTIS Mock AIME 2024-2025 | 23.1% | — |
| Omni-MATH | 36.4% | — |
| MATH Level 5 | 70.4% | — |
Knowledge GLM-4.5 leads
Gemini 1.5 Pro (May 2024): 29.4 (#239), GLM-4.5: 35.9 (#179)
| Benchmark | Gemini 1.5 Pro (May 2024) | GLM-4.5 |
|---|---|---|
| Humanity's Last Exam | 4.6% | 8.3% |
| Confabulations | 13.5% | 11.3% |
| LMArena Expert | 1279 | 1433 |
| GPQA Diamond | 57.2% | — |
| MMLU-Pro | 73.7% | — |
| GPQA (HELM) | 53.4% | — |
| MMLU | 86.9% | — |
Multimodal Not comparable
Gemini 1.5 Pro (May 2024): 36.8 (#77), GLM-4.5: —
| Benchmark | Gemini 1.5 Pro (May 2024) | GLM-4.5 |
|---|---|---|
| LMArena Vision | 1161 | — |
| Video-MME | 75% | — |
Multilingual GLM-4.5 leads
Gemini 1.5 Pro (May 2024): 45.3 (#174), GLM-4.5: 52.8 (#77)
| Benchmark | Gemini 1.5 Pro (May 2024) | GLM-4.5 |
|---|---|---|
| LMArena Non-English | 1312 | 1417 |
| LMArena Chinese | 1331 | 1465 |
| LMArena French | 1302 | 1418 |
| LMArena German | 1286 | 1407 |
| LMArena Japanese | 1292 | 1415 |
| LMArena Korean | 1298 | 1380 |
| LMArena Russian | 1320 | 1414 |
| LMArena Spanish | 1311 | 1454 |
Instruction Following GLM-4.5 leads
Gemini 1.5 Pro (May 2024): 68.6 (#185), GLM-4.5: 74.1 (#104)
| Benchmark | Gemini 1.5 Pro (May 2024) | GLM-4.5 |
|---|---|---|
| LMArena Instruction Following | 1297 | 1404 |
| IFEval | 83.7% | — |
Long Context Gemini 1.5 Pro (May 2024) leads
Gemini 1.5 Pro (May 2024): 39.8 (#169), GLM-4.5: 38.2 (#201)
| Benchmark | Gemini 1.5 Pro (May 2024) | GLM-4.5 |
|---|---|---|
| LMArena Longer Query | 1308 | 1412 |
| Fiction.LiveBench | — | 58.3% |
Writing & Preference GLM-4.5 leads
Gemini 1.5 Pro (May 2024): 52.4 (#172), GLM-4.5: 57.5 (#127)
| Benchmark | Gemini 1.5 Pro (May 2024) | GLM-4.5 |
|---|---|---|
| LMArena Text | 1319 | 1430 |
| LMArena Creative Writing | 1333 | 1395 |
| LMArena Multi-Turn | 1296 | 1415 |
| Short-Story Creative Writing | — | 73.4% |
| EQ-Bench Creative Writing | — | 1343 |
| WildBench | 81.3% | — |
Frequently asked questions
Is Gemini 1.5 Pro (May 2024) better than GLM-4.5?
GLM-4.5 is the stronger model overall, scoring 42.0 to 32.1 on the Noometry Index.
Is Gemini 1.5 Pro (May 2024) or GLM-4.5 better for coding?
GLM-4.5 scores higher on coding benchmarks: 41.4 versus 34.2 in the Noometry coding category.
How many benchmarks do Gemini 1.5 Pro (May 2024) and GLM-4.5 share?
20 benchmarks have published results for both models. Gemini 1.5 Pro (May 2024) has 45 scored results on Noometry and GLM-4.5 has 27.