Model comparison
Gemini 1.5 Pro (May 2024) vs GLM-5.3
GLM-5.3 is the stronger model overall, scoring 54.8 to 32.1 on the Noometry Index.
Last verified . 22 shared benchmarks.
GoogleSummary
- They share 22 benchmarks with published results for both. Gemini 1.5 Pro (May 2024) scores higher in 0 categories and GLM-5.3 in 9 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-5.3 leads 62.3 to 25.8.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 23.1% for Gemini 1.5 Pro (May 2024) and 91.1% for GLM-5.3.
- GLM-5.3 has downloadable open weights; the other is API-only.
Side by side
| Gemini 1.5 Pro (May 2024) | GLM-5.3 | |
|---|---|---|
| Provider | Z.ai (Zhipu) | |
| Noometry Index | 32.1 | 54.8 |
| Released | 2024-02-15 | 2026-08-14 |
| Weights | Proprietary | Open |
| Context window | — | 1M |
| Max output | — | 131K |
| Input $ / M tokens | — | $1.40 |
| Output $ / M tokens | — | $4.40 |
| Results tracked | 45 | 42 |
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Category by category
Coding GLM-5.3 leads
Gemini 1.5 Pro (May 2024): 34.2 (#241), GLM-5.3: 59.5 (#14)
| Benchmark | Gemini 1.5 Pro (May 2024) | GLM-5.3 |
|---|---|---|
| WeirdML | 22.2% | 75.4% |
| LMArena Coding | 1294 | 1496 |
| DeepSWE | — | 69% |
| FrontierCode | — | 40.1% |
| CursorBench | — | 42.6% |
| LMArena WebDev | — | 1622 |
| FrontierSWE | — | 30.2% |
| SciCode | — | 59% |
| BigCodeBench Instruct | 43.8% | — |
| BigCodeBench Complete | 57.5% | — |
| CadEval | 34% | — |
| ALE-Bench | — | 1,317 |
| HumanEval+ | 79.3% | — |
| MBPP+ | 74.6% | — |
Agentic & Tool Use GLM-5.3 leads
Gemini 1.5 Pro (May 2024): 17.9 (#145), GLM-5.3: 36.4 (#38)
| Benchmark | Gemini 1.5 Pro (May 2024) | GLM-5.3 |
|---|---|---|
| APEX-Agents | — | 56.6% |
| TheAgentCompany | 3.4% | — |
| Cybench | 7.5% | — |
| BALROG | 21% | — |
| Vending-Bench 2 | — | 8,164 |
Reasoning GLM-5.3 leads
Gemini 1.5 Pro (May 2024): 12.3 (#338), GLM-5.3: 46.1 (#46)
| Benchmark | Gemini 1.5 Pro (May 2024) | GLM-5.3 |
|---|---|---|
| LMArena Hard Prompts | 1296 | 1489 |
| DTBench | 59% | 87.7% |
| Epoch Capabilities Index | 131.73 | 155.61 |
| ARC-AGI-2 | 0.8% | — |
| SimpleBench | 27.1% | — |
| NYT Connections (extended) | — | 74.2% |
| CritPt | — | 19.1% |
| Chess Puzzles | — | 21% |
| Mystery Game Puzzles | — | 33% |
| LMCA | — | 55.5% |
| Bench to the Future 3 | — | 0.15 |
| BIG-Bench Hard | 89.2% | — |
| ForecastBench | 58.4 | — |
Math GLM-5.3 leads
Gemini 1.5 Pro (May 2024): 25.8 (#266), GLM-5.3: 62.3 (#33)
| Benchmark | Gemini 1.5 Pro (May 2024) | GLM-5.3 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 23.1% | 91.1% |
| LMArena Math | 1315 | 1489 |
| FrontierMath (Tiers 1-3) | — | 68.8% |
| FrontierMath Tier 4 | — | 29.3% |
| ProofBench | — | 49% |
| Omni-MATH | 36.4% | — |
| MATH Level 5 | 70.4% | — |
Knowledge GLM-5.3 leads
Gemini 1.5 Pro (May 2024): 29.4 (#239), GLM-5.3: 58.3 (#37)
| Benchmark | Gemini 1.5 Pro (May 2024) | GLM-5.3 |
|---|---|---|
| GPQA Diamond | 57.2% | 90.9% |
| LMArena Expert | 1279 | 1516 |
| Humanity's Last Exam | 4.6% | — |
| SimpleQA Verified | — | 41% |
| MMLU-Pro | 73.7% | — |
| Confabulations | 13.5% | — |
| GPQA (HELM) | 53.4% | — |
| MMLU | 86.9% | — |
Multimodal Not comparable
Gemini 1.5 Pro (May 2024): 36.8 (#77), GLM-5.3: —
| Benchmark | Gemini 1.5 Pro (May 2024) | GLM-5.3 |
|---|---|---|
| LMArena Vision | 1161 | — |
| Video-MME | 75% | — |
Multilingual GLM-5.3 leads
Gemini 1.5 Pro (May 2024): 45.3 (#174), GLM-5.3: 55.7 (#28)
| Benchmark | Gemini 1.5 Pro (May 2024) | GLM-5.3 |
|---|---|---|
| LMArena Non-English | 1312 | 1457 |
| LMArena Chinese | 1331 | 1528 |
| LMArena French | 1302 | 1499 |
| LMArena German | 1286 | 1499 |
| LMArena Japanese | 1292 | 1453 |
| LMArena Korean | 1298 | 1472 |
| LMArena Russian | 1320 | 1463 |
| LMArena Spanish | 1311 | 1460 |
Instruction Following GLM-5.3 leads
Gemini 1.5 Pro (May 2024): 68.6 (#185), GLM-5.3: 77.5 (#23)
| Benchmark | Gemini 1.5 Pro (May 2024) | GLM-5.3 |
|---|---|---|
| LMArena Instruction Following | 1297 | 1477 |
| IFEval | 83.7% | — |
Long Context GLM-5.3 leads
Gemini 1.5 Pro (May 2024): 39.8 (#169), GLM-5.3: 45.4 (#41)
| Benchmark | Gemini 1.5 Pro (May 2024) | GLM-5.3 |
|---|---|---|
| LMArena Longer Query | 1308 | 1482 |
Writing & Preference GLM-5.3 leads
Gemini 1.5 Pro (May 2024): 52.4 (#172), GLM-5.3: 75.7 (#6)
| Benchmark | Gemini 1.5 Pro (May 2024) | GLM-5.3 |
|---|---|---|
| LMArena Text | 1319 | 1471 |
| LMArena Creative Writing | 1333 | 1457 |
| LMArena Multi-Turn | 1296 | 1472 |
| EQ-Bench Creative Writing | — | 2075 |
| WildBench | 81.3% | — |
Frequently asked questions
Is Gemini 1.5 Pro (May 2024) better than GLM-5.3?
GLM-5.3 is the stronger model overall, scoring 54.8 to 32.1 on the Noometry Index.
Is Gemini 1.5 Pro (May 2024) or GLM-5.3 better for coding?
GLM-5.3 scores higher on coding benchmarks: 59.5 versus 34.2 in the Noometry coding category.
How many benchmarks do Gemini 1.5 Pro (May 2024) and GLM-5.3 share?
22 benchmarks have published results for both models. Gemini 1.5 Pro (May 2024) has 45 scored results on Noometry and GLM-5.3 has 42.