Model comparison
Gemini 2.5 Pro vs GLM-5.3-Flash
GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 45.0 on the Noometry Index.
Last verified . 30 shared benchmarks.
Summary
- They share 30 benchmarks with published results for both. Gemini 2.5 Pro scores higher in 2 categories and GLM-5.3-Flash in 8 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-5.3-Flash leads 53.3 to 32.5.
- The biggest single-benchmark swing is ARC-AGI-2: 4.9% for Gemini 2.5 Pro and 65.8% for GLM-5.3-Flash.
- GLM-5.3-Flash is cheaper at $0.15 / $0.50 per million input/output tokens, against $1.25 / $10 for Gemini 2.5 Pro.
- Gemini 2.5 Pro accepts more context: 1.05M tokens versus 1M.
- GLM-5.3-Flash has downloadable open weights; the other is API-only.
Side by side
| Gemini 2.5 Pro | GLM-5.3-Flash | |
|---|---|---|
| Provider | Z.ai (Zhipu) | |
| Noometry Index | 45.0 | 51.8 |
| Released | 2025-03-25 | 2026-08-20 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 1M |
| Max output | 66K | 131K |
| Input $ / M tokens | $1.25 | $0.15 |
| Output $ / M tokens | $10 | $0.50 |
| Results tracked | 78 | 40 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding GLM-5.3-Flash leads
Gemini 2.5 Pro: 42.4 (#101), GLM-5.3-Flash: 53.1 (#31)
| Benchmark | Gemini 2.5 Pro | GLM-5.3-Flash |
|---|---|---|
| LMArena WebDev | 1227 | 1609 |
| SciCode | 42.8% | 51.6% |
| LMArena Coding | 1452 | 1508 |
| ALE-Bench | 785.52 | 303.55 |
| SWE-bench Verified | 57.6% | — |
| DeepSWE | — | 63.4% |
| FrontierCode | — | 31.8% |
| SWE-bench Verified (bash only) | 53.6% | — |
| Aider Polyglot | 83.1% | — |
| CursorBench | — | 36.8% |
| FrontierSWE | — | 18.1% |
| GSO | 3.9% | — |
| WeirdML | 54% | — |
| LiveBench Coding | 85.9% | — |
| CadEval | 64% | — |
| AlgoTune | 1.51 | — |
Agentic & Tool Use GLM-5.3-Flash leads
Gemini 2.5 Pro: 29.2 (#88), GLM-5.3-Flash: 34.2 (#47)
| Benchmark | Gemini 2.5 Pro | GLM-5.3-Flash |
|---|---|---|
| Terminal-Bench | 32.6% | — |
| APEX-Agents | — | 52.8% |
| GDPval | 23.3% | — |
| Remote Labor Index | 0.8% | — |
| TheAgentCompany | 30.3% | — |
| τ²-bench Banking | 13.7% | — |
| DeepResearch Bench | 42.8% | — |
| BALROG | 43.3% | — |
| GDP.pdf | — | 14% |
| LMArena Search | 1142 | — |
| METR Time Horizons | 55.4% | — |
| Vending-Bench 2 | 573.64 | — |
Reasoning GLM-5.3-Flash leads
Gemini 2.5 Pro: 28.8 (#99), GLM-5.3-Flash: 48.0 (#42)
| Benchmark | Gemini 2.5 Pro | GLM-5.3-Flash |
|---|---|---|
| ARC-AGI-2 | 4.9% | 65.8% |
| ARC-AGI-1 | 41% | 91% |
| CritPt | 2% | 15.4% |
| Chess Puzzles | 20% | 14% |
| LMArena Hard Prompts | 1455 | 1491 |
| Epoch Capabilities Index | 145.32 | 151.88 |
| SimpleBench | 62.4% | — |
| Kagi LLM Benchmark | 70.3% | — |
| EnigmaEval | 5.6% | — |
| LiveBench Reasoning | 89.8% | — |
| Mystery Game Puzzles | — | 8% |
| DTBench | 82.4% | — |
| LiveBench Data Analysis | 79.9% | — |
| LMCA | 34.8% | — |
| Surface Evolver Bench | — | 52.5% |
| Bench to the Future 3 | — | 0.15 |
| ForecastBench | 61.3 | — |
| LiveBench | 82.3% | — |
Math GLM-5.3-Flash leads
Gemini 2.5 Pro: 32.5 (#213), GLM-5.3-Flash: 53.3 (#47)
| Benchmark | Gemini 2.5 Pro | GLM-5.3-Flash |
|---|---|---|
| FrontierMath (Tiers 1-3) | 24.6% | 55.8% |
| FrontierMath Tier 4 | 0% | 17.1% |
| OTIS Mock AIME 2024-2025 | 84.7% | 93.9% |
| LMArena Math | 1450 | 1500 |
| ProofBench | — | 21% |
| Omni-MATH | 41.6% | — |
| LiveBench Math | 90.2% | — |
| MATH Level 5 | 95.9% | — |
| FrontierMath (Feb 2025 set) | 14.1% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |
Knowledge GLM-5.3-Flash leads
Gemini 2.5 Pro: 56.0 (#46), GLM-5.3-Flash: 58.4 (#36)
| Benchmark | Gemini 2.5 Pro | GLM-5.3-Flash |
|---|---|---|
| GPQA Diamond | 85.3% | 90.2% |
| LMArena Expert | 1452 | 1513 |
| Humanity's Last Exam | 21.6% | — |
| MMLU-Pro | 86.3% | — |
| Confabulations | 10.6% | — |
| Vectara Hallucination Rate | 7% | — |
| GPQA (HELM) | 74.9% | — |
Multimodal Gemini 2.5 Pro leads
Gemini 2.5 Pro: 45.2 (#18), GLM-5.3-Flash: 42.8 (#27)
| Benchmark | Gemini 2.5 Pro | GLM-5.3-Flash |
|---|---|---|
| LMArena Vision | 1263 | 1296 |
| GeoBench | 86% | — |
| VPCT | 48% | — |
| LMArena Document | 1421 | — |
| SpatialViz-Bench | 44.7% | — |
Multilingual Too close to call
Gemini 2.5 Pro: 55.3 (#31), GLM-5.3-Flash: 56.0 (#25)
| Benchmark | Gemini 2.5 Pro | GLM-5.3-Flash |
|---|---|---|
| LMArena Non-English | 1451 | 1462 |
| LMArena Chinese | 1507 | 1527 |
| LMArena French | 1472 | 1496 |
| LMArena German | 1487 | 1470 |
| LMArena Japanese | 1461 | 1429 |
| LMArena Korean | 1434 | 1446 |
| LMArena Russian | 1461 | 1469 |
| LMArena Spanish | 1473 | 1471 |
Instruction Following GLM-5.3-Flash leads
Gemini 2.5 Pro: 75.0 (#75), GLM-5.3-Flash: 77.5 (#20)
| Benchmark | Gemini 2.5 Pro | GLM-5.3-Flash |
|---|---|---|
| LMArena Instruction Following | 1437 | 1478 |
| LiveBench Instruction Following | 80.6% | — |
| IFEval | 84% | — |
Long Context Gemini 2.5 Pro leads
Gemini 2.5 Pro: 59.8 (#5), GLM-5.3-Flash: 45.4 (#39)
| Benchmark | Gemini 2.5 Pro | GLM-5.3-Flash |
|---|---|---|
| LMArena Longer Query | 1449 | 1482 |
| Fiction.LiveBench | 91.7% | — |
Writing & Preference GLM-5.3-Flash leads
Gemini 2.5 Pro: 63.7 (#62), GLM-5.3-Flash: 65.3 (#50)
| Benchmark | Gemini 2.5 Pro | GLM-5.3-Flash |
|---|---|---|
| LMArena Text | 1458 | 1471 |
| LMArena Creative Writing | 1454 | 1442 |
| LMArena Multi-Turn | 1453 | 1467 |
| Short-Story Creative Writing | 83.8% | — |
| EQ-Bench Creative Writing | 1421 | — |
| WildBench | 85.7% | — |
| LiveBench Language | 67.8% | — |
Frequently asked questions
Is Gemini 2.5 Pro better than GLM-5.3-Flash?
GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 45.0 on the Noometry Index.
Which is cheaper, Gemini 2.5 Pro or GLM-5.3-Flash?
GLM-5.3-Flash is cheaper. It lists at $0.15 per million input tokens and $0.50 per million output tokens; Gemini 2.5 Pro lists at $1.25 and $10.
Is Gemini 2.5 Pro or GLM-5.3-Flash better for coding?
GLM-5.3-Flash scores higher on coding benchmarks: 53.1 versus 42.4 in the Noometry coding category.
Which has the bigger context window?
Gemini 2.5 Pro does, with 1.05M tokens against 1M.
How many benchmarks do Gemini 2.5 Pro and GLM-5.3-Flash share?
30 benchmarks have published results for both models. Gemini 2.5 Pro has 78 scored results on Noometry and GLM-5.3-Flash has 40.