Model comparison
Gemini 2.5 Pro vs GLM-5V-Turbo
Gemini 2.5 Pro is the stronger model overall, scoring 45.0 to 43.8 on the Noometry Index. GLM-5V-Turbo costs 1.8× less per token, which makes it the better buy when Gemini 2.5 Pro's lead doesn't matter for your workload.
Last verified . 19 shared benchmarks.
GoogleSummary
- They share 19 benchmarks with published results for both. Gemini 2.5 Pro scores higher in 7 categories and GLM-5V-Turbo in 2 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in long context, where Gemini 2.5 Pro leads 59.8 to 44.0.
- GLM-5V-Turbo is cheaper at $1.20 / $4 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 200K.
Side by side
| Gemini 2.5 Pro | GLM-5V-Turbo | |
|---|---|---|
| Provider | Z.ai (Zhipu) | |
| Noometry Index | 45.0 | 43.8 |
| Released | 2025-03-25 | 2026-04-01 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 200K |
| Max output | 66K | 131K |
| Input $ / M tokens | $1.25 | $1.20 |
| Output $ / M tokens | $10 | $4 |
| Results tracked | 78 | 19 |
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Category by category
Coding Too close to call
Gemini 2.5 Pro: 42.4 (#101), GLM-5V-Turbo: 42.1 (#111)
| Benchmark | Gemini 2.5 Pro | GLM-5V-Turbo |
|---|---|---|
| LMArena WebDev | 1227 | 1401 |
| LMArena Coding | 1452 | 1466 |
| SWE-bench Verified | 57.6% | — |
| SWE-bench Verified (bash only) | 53.6% | — |
| Aider Polyglot | 83.1% | — |
| SciCode | 42.8% | — |
| GSO | 3.9% | — |
| WeirdML | 54% | — |
| LiveBench Coding | 85.9% | — |
| CadEval | 64% | — |
| ALE-Bench | 785.52 | — |
| AlgoTune | 1.51 | — |
Agentic & Tool Use Not comparable
Gemini 2.5 Pro: 29.2 (#88), GLM-5V-Turbo: —
| Benchmark | Gemini 2.5 Pro | GLM-5V-Turbo |
|---|---|---|
| Terminal-Bench | 32.6% | — |
| GDPval | 23.3% | — |
| Remote Labor Index | 0.8% | — |
| TheAgentCompany | 30.3% | — |
| τ²-bench Banking | 13.7% | — |
| DeepResearch Bench | 42.8% | — |
| BALROG | 43.3% | — |
| LMArena Search | 1142 | — |
| METR Time Horizons | 55.4% | — |
| Vending-Bench 2 | 573.64 | — |
Reasoning Too close to call
Gemini 2.5 Pro: 28.8 (#99), GLM-5V-Turbo: 29.7 (#89)
| Benchmark | Gemini 2.5 Pro | GLM-5V-Turbo |
|---|---|---|
| LMArena Hard Prompts | 1455 | 1443 |
| ARC-AGI-2 | 4.9% | — |
| SimpleBench | 62.4% | — |
| Kagi LLM Benchmark | 70.3% | — |
| ARC-AGI-1 | 41% | — |
| CritPt | 2% | — |
| Chess Puzzles | 20% | — |
| EnigmaEval | 5.6% | — |
| LiveBench Reasoning | 89.8% | — |
| DTBench | 82.4% | — |
| LiveBench Data Analysis | 79.9% | — |
| LMCA | 34.8% | — |
| Epoch Capabilities Index | 145.32 | — |
| ForecastBench | 61.3 | — |
| LiveBench | 82.3% | — |
Math GLM-5V-Turbo leads
Gemini 2.5 Pro: 32.5 (#213), GLM-5V-Turbo: 39.4 (#106)
| Benchmark | Gemini 2.5 Pro | GLM-5V-Turbo |
|---|---|---|
| LMArena Math | 1450 | 1441 |
| FrontierMath (Tiers 1-3) | 24.6% | — |
| FrontierMath Tier 4 | 0% | — |
| OTIS Mock AIME 2024-2025 | 84.7% | — |
| 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 Gemini 2.5 Pro leads
Gemini 2.5 Pro: 56.0 (#46), GLM-5V-Turbo: 40.6 (#117)
| Benchmark | Gemini 2.5 Pro | GLM-5V-Turbo |
|---|---|---|
| LMArena Expert | 1452 | 1452 |
| GPQA Diamond | 85.3% | — |
| 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-5V-Turbo: 40.9 (#42)
| Benchmark | Gemini 2.5 Pro | GLM-5V-Turbo |
|---|---|---|
| LMArena Vision | 1263 | 1264 |
| LMArena Document | 1421 | 1416 |
| GeoBench | 86% | — |
| VPCT | 48% | — |
| SpatialViz-Bench | 44.7% | — |
Multilingual Gemini 2.5 Pro leads
Gemini 2.5 Pro: 55.3 (#31), GLM-5V-Turbo: 53.0 (#73)
| Benchmark | Gemini 2.5 Pro | GLM-5V-Turbo |
|---|---|---|
| LMArena Non-English | 1451 | 1420 |
| LMArena Chinese | 1507 | 1488 |
| LMArena French | 1472 | 1444 |
| LMArena German | 1487 | 1423 |
| LMArena Korean | 1434 | 1396 |
| LMArena Russian | 1461 | 1431 |
| LMArena Spanish | 1473 | 1450 |
| LMArena Japanese | 1461 | — |
Instruction Following Too close to call
Gemini 2.5 Pro: 75.0 (#75), GLM-5V-Turbo: 75.0 (#80)
| Benchmark | Gemini 2.5 Pro | GLM-5V-Turbo |
|---|---|---|
| LMArena Instruction Following | 1437 | 1423 |
| LiveBench Instruction Following | 80.6% | — |
| IFEval | 84% | — |
Long Context Gemini 2.5 Pro leads
Gemini 2.5 Pro: 59.8 (#5), GLM-5V-Turbo: 44.0 (#80)
| Benchmark | Gemini 2.5 Pro | GLM-5V-Turbo |
|---|---|---|
| LMArena Longer Query | 1449 | 1438 |
| Fiction.LiveBench | 91.7% | — |
Writing & Preference Gemini 2.5 Pro leads
Gemini 2.5 Pro: 63.7 (#62), GLM-5V-Turbo: 62.5 (#73)
| Benchmark | Gemini 2.5 Pro | GLM-5V-Turbo |
|---|---|---|
| LMArena Text | 1458 | 1437 |
| LMArena Creative Writing | 1454 | 1416 |
| LMArena Multi-Turn | 1453 | 1432 |
| 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-5V-Turbo?
Gemini 2.5 Pro is the stronger model overall, scoring 45.0 to 43.8 on the Noometry Index. GLM-5V-Turbo costs 1.8× less per token, which makes it the better buy when Gemini 2.5 Pro's lead doesn't matter for your workload.
Which is cheaper, Gemini 2.5 Pro or GLM-5V-Turbo?
GLM-5V-Turbo is cheaper. It lists at $1.20 per million input tokens and $4 per million output tokens; Gemini 2.5 Pro lists at $1.25 and $10.
Is Gemini 2.5 Pro or GLM-5V-Turbo better for coding?
They score almost the same on coding (42.4 vs 42.1); test both on your own repository before choosing.
Which has the bigger context window?
Gemini 2.5 Pro does, with 1.05M tokens against 200K.
How many benchmarks do Gemini 2.5 Pro and GLM-5V-Turbo share?
19 benchmarks have published results for both models. Gemini 2.5 Pro has 78 scored results on Noometry and GLM-5V-Turbo has 19.