Model comparison
Gemini 2.5 Pro vs GLM-5
GLM-5 is the stronger model overall, scoring 46.1 to 45.0 on the Noometry Index.
Last verified . 38 shared benchmarks.
GoogleSummary
- They share 38 benchmarks with published results for both. Gemini 2.5 Pro scores higher in 4 categories and GLM-5 in 5 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in long context, where Gemini 2.5 Pro leads 59.8 to 44.7.
- The biggest single-benchmark swing is Terminal-Bench: 32.6% for Gemini 2.5 Pro and 52.4% for GLM-5.
- GLM-5 is cheaper at $1 / $3.20 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 205K.
- GLM-5 has downloadable open weights; the other is API-only.
Side by side
| Gemini 2.5 Pro | GLM-5 | |
|---|---|---|
| Provider | Z.ai (Zhipu) | |
| Noometry Index | 45.0 | 46.1 |
| Released | 2025-03-25 | 2026-02-11 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 205K |
| Max output | 66K | 131K |
| Input $ / M tokens | $1.25 | $1 |
| Output $ / M tokens | $10 | $3.20 |
| Results tracked | 78 | 45 |
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Category by category
Coding GLM-5 leads
Gemini 2.5 Pro: 42.4 (#101), GLM-5: 49.0 (#52)
| Benchmark | Gemini 2.5 Pro | GLM-5 |
|---|---|---|
| SWE-bench Verified | 57.6% | 72.1% |
| SWE-bench Verified (bash only) | 53.6% | 72.8% |
| LMArena WebDev | 1227 | 1434 |
| WeirdML | 54% | 48.2% |
| LMArena Coding | 1452 | 1461 |
| ALE-Bench | 785.52 | 765.62 |
| Aider Polyglot | 83.1% | — |
| SWE-bench Multilingual | — | 69.7% |
| SciCode | 42.8% | — |
| GSO | 3.9% | — |
| LiveBench Coding | 85.9% | — |
| CadEval | 64% | — |
| AlgoTune | 1.51 | — |
Agentic & Tool Use GLM-5 leads
Gemini 2.5 Pro: 29.2 (#88), GLM-5: 31.1 (#71)
| Benchmark | Gemini 2.5 Pro | GLM-5 |
|---|---|---|
| Terminal-Bench | 32.6% | 52.4% |
| τ²-bench Banking | 13.7% | 9.8% |
| Vending-Bench 2 | 573.64 | 4,432 |
| GDPval | 23.3% | — |
| Remote Labor Index | 0.8% | — |
| TheAgentCompany | 30.3% | — |
| τ²-bench Airline | — | 82.5% |
| τ²-bench Retail | — | 73.7% |
| τ²-bench Telecom | — | 86.8% |
| DeepResearch Bench | 42.8% | — |
| BALROG | 43.3% | — |
| LMArena Search | 1142 | — |
| METR Time Horizons | 55.4% | — |
Reasoning Gemini 2.5 Pro leads
Gemini 2.5 Pro: 28.8 (#99), GLM-5: 27.6 (#116)
| Benchmark | Gemini 2.5 Pro | GLM-5 |
|---|---|---|
| ARC-AGI-2 | 4.9% | 4.9% |
| SimpleBench | 62.4% | 53.2% |
| Kagi LLM Benchmark | 70.3% | 75% |
| ARC-AGI-1 | 41% | 44.7% |
| Chess Puzzles | 20% | 10% |
| LMArena Hard Prompts | 1455 | 1452 |
| Epoch Capabilities Index | 145.32 | 145.83 |
| ForecastBench | 61.3 | 61 |
| NYT Connections (extended) | — | 74.8% |
| CritPt | 2% | — |
| EnigmaEval | 5.6% | — |
| LiveBench Reasoning | 89.8% | — |
| DTBench | 82.4% | — |
| LiveBench Data Analysis | 79.9% | — |
| LMCA | 34.8% | — |
| LiveBench | 82.3% | — |
Math GLM-5 leads
Gemini 2.5 Pro: 32.5 (#213), GLM-5: 46.4 (#71)
| Benchmark | Gemini 2.5 Pro | GLM-5 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 84.7% | 80% |
| LMArena Math | 1450 | 1440 |
| FrontierMath (Feb 2025 set) | 14.1% | 16.4% |
| FrontierMath Tier 4 (v1) | 4.2% | 2.1% |
| FrontierMath (Tiers 1-3) | 24.6% | — |
| FrontierMath Tier 4 | 0% | — |
| MathArena Final-Answer Competitions | — | 65.7% |
| Omni-MATH | 41.6% | — |
| LiveBench Math | 90.2% | — |
| MATH Level 5 | 95.9% | — |
Knowledge Gemini 2.5 Pro leads
Gemini 2.5 Pro: 56.0 (#46), GLM-5: 52.3 (#64)
| Benchmark | Gemini 2.5 Pro | GLM-5 |
|---|---|---|
| GPQA Diamond | 85.3% | 87.8% |
| Vectara Hallucination Rate | 7% | 10.1% |
| LMArena Expert | 1452 | 1454 |
| Humanity's Last Exam | 21.6% | — |
| MMLU-Pro | 86.3% | — |
| Confabulations | 10.6% | — |
| GPQA (HELM) | 74.9% | — |
Multimodal Not comparable
Gemini 2.5 Pro: 45.2 (#18), GLM-5: —
| Benchmark | Gemini 2.5 Pro | GLM-5 |
|---|---|---|
| LMArena Vision | 1263 | — |
| GeoBench | 86% | — |
| VPCT | 48% | — |
| LMArena Document | 1421 | — |
| SpatialViz-Bench | 44.7% | — |
Multilingual Gemini 2.5 Pro leads
Gemini 2.5 Pro: 55.3 (#31), GLM-5: 53.7 (#58)
| Benchmark | Gemini 2.5 Pro | GLM-5 |
|---|---|---|
| LMArena Non-English | 1451 | 1430 |
| LMArena Chinese | 1507 | 1511 |
| LMArena French | 1472 | 1455 |
| LMArena German | 1487 | 1445 |
| LMArena Japanese | 1461 | 1416 |
| LMArena Korean | 1434 | 1423 |
| LMArena Russian | 1461 | 1436 |
| LMArena Spanish | 1473 | 1454 |
Instruction Following Too close to call
Gemini 2.5 Pro: 75.0 (#75), GLM-5: 75.2 (#67)
| Benchmark | Gemini 2.5 Pro | GLM-5 |
|---|---|---|
| LMArena Instruction Following | 1437 | 1428 |
| LiveBench Instruction Following | 80.6% | — |
| IFEval | 84% | — |
Long Context Gemini 2.5 Pro leads
Gemini 2.5 Pro: 59.8 (#5), GLM-5: 44.7 (#60)
| Benchmark | Gemini 2.5 Pro | GLM-5 |
|---|---|---|
| LMArena Longer Query | 1449 | 1446 |
| Fiction.LiveBench | 91.7% | — |
| CL-bench | — | 18.7% |
Writing & Preference GLM-5 leads
Gemini 2.5 Pro: 63.7 (#62), GLM-5: 66.0 (#38)
| Benchmark | Gemini 2.5 Pro | GLM-5 |
|---|---|---|
| LMArena Text | 1458 | 1446 |
| LMArena Creative Writing | 1454 | 1439 |
| EQ-Bench Creative Writing | 1421 | 1601 |
| LMArena Multi-Turn | 1453 | 1456 |
| Short-Story Creative Writing | 83.8% | — |
| WildBench | 85.7% | — |
| LiveBench Language | 67.8% | — |
Frequently asked questions
Is Gemini 2.5 Pro better than GLM-5?
GLM-5 is the stronger model overall, scoring 46.1 to 45.0 on the Noometry Index.
Which is cheaper, Gemini 2.5 Pro or GLM-5?
GLM-5 is cheaper. It lists at $1 per million input tokens and $3.20 per million output tokens; Gemini 2.5 Pro lists at $1.25 and $10.
Is Gemini 2.5 Pro or GLM-5 better for coding?
GLM-5 scores higher on coding benchmarks: 49.0 versus 42.4 in the Noometry coding category.
Which has the bigger context window?
Gemini 2.5 Pro does, with 1.05M tokens against 205K.
How many benchmarks do Gemini 2.5 Pro and GLM-5 share?
38 benchmarks have published results for both models. Gemini 2.5 Pro has 78 scored results on Noometry and GLM-5 has 45.