# Gemini 2.0 Flash (Feb 2025) vs GLM-5

> GLM-5 is the stronger model overall, scoring 46.1 to 35.1 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gemini-2-0-flash-vs-glm-5
- Last updated: 2026-10-10
- Shared benchmarks: 27

## Summary

- They share 27 benchmarks with published results for both. Gemini 2.0 Flash (Feb 2025) scores higher in 0 categories and GLM-5 in 9 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in coding, where GLM-5 leads 49.0 to 28.4.
- The biggest single-benchmark swing is SWE-bench Verified (bash only): 13.5% for Gemini 2.0 Flash (Feb 2025) and 72.8% for GLM-5.
- GLM-5 has downloadable open weights; the other is API-only.

## Snapshot

| | Gemini 2.0 Flash (Feb 2025) | GLM-5 |
|---|---|---|
| Provider | Google | Z.ai (Zhipu) |
| Noometry Index | 35.1 | 46.1 |
| Rank | 228 | 66 |
| Context | — | 205K |
| Input $/M | — | $1 |
| Output $/M | — | $3.20 |
| Weights | Proprietary | Open |

## Coding

- Gemini 2.0 Flash (Feb 2025): 28.4 (#315)
- GLM-5: 49.0 (#52)

| Benchmark | Gemini 2.0 Flash (Feb 2025) | GLM-5 |
|---|---|---|
| SWE-bench Verified (bash only) | 13.5% | 72.8% |
| WeirdML | 25.8% | 48.2% |
| LMArena Coding | 1350 | 1461 |
| SWE-bench Verified | — | 72.1% |
| Aider Polyglot | 38.2% | — |
| LMArena WebDev | — | 1434 |
| SWE-bench Multilingual | — | 69.7% |
| BigCodeBench Instruct | 45.9% | — |
| LiveBench Coding | 63.4% | — |
| BigCodeBench Complete | 59.9% | — |
| CadEval | 30% | — |
| ALE-Bench | — | 765.62 |

## Agentic & Tool Use

- Gemini 2.0 Flash (Feb 2025): 28.1 (#92)
- GLM-5: 31.1 (#71)

| Benchmark | Gemini 2.0 Flash (Feb 2025) | GLM-5 |
|---|---|---|
| Terminal-Bench | — | 52.4% |
| TheAgentCompany | 11.4% | — |
| τ²-bench Airline | — | 82.5% |
| τ²-bench Banking | — | 9.8% |
| τ²-bench Retail | — | 73.7% |
| τ²-bench Telecom | — | 86.8% |
| Vending-Bench 2 | — | 4,432 |

## Reasoning

- Gemini 2.0 Flash (Feb 2025): 15.2 (#318)
- GLM-5: 27.6 (#116)

| Benchmark | Gemini 2.0 Flash (Feb 2025) | GLM-5 |
|---|---|---|
| ARC-AGI-2 | 1.3% | 4.9% |
| SimpleBench | 31.1% | 53.2% |
| Kagi LLM Benchmark | 37.8% | 75% |
| LMArena Hard Prompts | 1346 | 1452 |
| Epoch Capabilities Index | 135.36 | 145.83 |
| NYT Connections (extended) | — | 74.8% |
| ARC-AGI-1 | — | 44.7% |
| Chess Puzzles | — | 10% |
| EnigmaEval | 1.1% | — |
| LiveBench Reasoning | 78.2% | — |
| DTBench | 63.2% | — |
| LiveBench Data Analysis | 69.4% | — |
| ForecastBench | — | 61 |
| LiveBench | 66.9% | — |

## Math

- Gemini 2.0 Flash (Feb 2025): 37.9 (#146)
- GLM-5: 46.4 (#71)

| Benchmark | Gemini 2.0 Flash (Feb 2025) | GLM-5 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 57.8% | 80% |
| LMArena Math | 1352 | 1440 |
| FrontierMath (Feb 2025 set) | 1.7% | 16.4% |
| MathArena Final-Answer Competitions | — | 65.7% |
| Omni-MATH | 45.9% | — |
| LiveBench Math | 75.8% | — |
| MATH Level 5 | 82.2% | — |
| FrontierMath Tier 4 (v1) | — | 2.1% |

## Knowledge

- Gemini 2.0 Flash (Feb 2025): 32.0 (#213)
- GLM-5: 52.3 (#64)

| Benchmark | Gemini 2.0 Flash (Feb 2025) | GLM-5 |
|---|---|---|
| GPQA Diamond | 64.1% | 87.8% |
| LMArena Expert | 1339 | 1454 |
| Humanity's Last Exam | 6.6% | — |
| MMLU-Pro | 73.7% | — |
| Confabulations | 12.4% | — |
| Vectara Hallucination Rate | — | 10.1% |
| GPQA (HELM) | 55.6% | — |
| MMLU | 79.7% | — |

## Multimodal

- Gemini 2.0 Flash (Feb 2025): 36.5 (#79)
- GLM-5: —

| Benchmark | Gemini 2.0 Flash (Feb 2025) | GLM-5 |
|---|---|---|
| LMArena Vision | 1158 | — |
| GeoBench | 77% | — |

## Multilingual

- Gemini 2.0 Flash (Feb 2025): 47.4 (#149)
- GLM-5: 53.7 (#58)

| Benchmark | Gemini 2.0 Flash (Feb 2025) | GLM-5 |
|---|---|---|
| LMArena Non-English | 1342 | 1430 |
| LMArena Chinese | 1373 | 1511 |
| LMArena French | 1391 | 1455 |
| LMArena German | 1353 | 1445 |
| LMArena Japanese | 1294 | 1416 |
| LMArena Korean | 1313 | 1423 |
| LMArena Russian | 1351 | 1436 |
| LMArena Spanish | 1363 | 1454 |

## Instruction Following

- Gemini 2.0 Flash (Feb 2025): 74.4 (#97)
- GLM-5: 75.2 (#67)

| Benchmark | Gemini 2.0 Flash (Feb 2025) | GLM-5 |
|---|---|---|
| LMArena Instruction Following | 1336 | 1428 |
| LiveBench Instruction Following | 85.8% | — |
| IFEval | 84.1% | — |

## Long Context

- Gemini 2.0 Flash (Feb 2025): 38.1 (#203)
- GLM-5: 44.7 (#60)

| Benchmark | Gemini 2.0 Flash (Feb 2025) | GLM-5 |
|---|---|---|
| LMArena Longer Query | 1344 | 1446 |
| Fiction.LiveBench | 61.1% | — |
| CL-bench | — | 18.7% |

## Writing & Preference

- Gemini 2.0 Flash (Feb 2025): 49.5 (#190)
- GLM-5: 66.0 (#38)

| Benchmark | Gemini 2.0 Flash (Feb 2025) | GLM-5 |
|---|---|---|
| LMArena Text | 1354 | 1446 |
| LMArena Creative Writing | 1340 | 1439 |
| EQ-Bench Creative Writing | 1128 | 1601 |
| LMArena Multi-Turn | 1350 | 1456 |
| Short-Story Creative Writing | 73.8% | — |
| WildBench | 80% | — |
| LiveBench Language | 51.3% | — |

## FAQ

### Is Gemini 2.0 Flash (Feb 2025) better than GLM-5?

GLM-5 is the stronger model overall, scoring 46.1 to 35.1 on the Noometry Index.

### Is Gemini 2.0 Flash (Feb 2025) or GLM-5 better for coding?

GLM-5 scores higher on coding benchmarks: 49.0 versus 28.4 in the Noometry coding category.

### How many benchmarks do Gemini 2.0 Flash (Feb 2025) and GLM-5 share?

27 benchmarks have published results for both models. Gemini 2.0 Flash (Feb 2025) has 54 scored results on Noometry and GLM-5 has 45.