# Gemini 3.5 Flash vs GLM-5V-Turbo

> Gemini 3.5 Flash is the stronger model overall, scoring 54.1 to 43.1 on the Noometry Index. GLM-5V-Turbo costs 1.8× less per token, which makes it the better buy when Gemini 3.5 Flash's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gemini-3-5-flash-vs-glm-5v-turbo
- Last updated: 2026-10-10
- Shared benchmarks: 19

## Summary

- They share 19 benchmarks with published results for both. Gemini 3.5 Flash scores higher in 9 categories and GLM-5V-Turbo in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Gemini 3.5 Flash leads 62.7 to 28.5.
- GLM-5V-Turbo is cheaper at $1.20 / $4 per million input/output tokens, against $1.50 / $9 for Gemini 3.5 Flash.
- Gemini 3.5 Flash accepts more context: 1.05M tokens versus 200K.

## Snapshot

| | Gemini 3.5 Flash | GLM-5V-Turbo |
|---|---|---|
| Provider | Google | Z.ai (Zhipu) |
| Noometry Index | 54.1 | 43.1 |
| Rank | 29 | 86 |
| Context | 1.05M | 200K |
| Input $/M | $1.50 | $1.20 |
| Output $/M | $9 | $4 |
| Weights | Proprietary | Proprietary |

## Coding

- Gemini 3.5 Flash: 49.1 (#46)
- GLM-5V-Turbo: 41.8 (#105)

| Benchmark | Gemini 3.5 Flash | GLM-5V-Turbo |
|---|---|---|
| LMArena WebDev | 1499 | 1400 |
| LMArena Coding | 1492 | 1467 |
| SWE-bench Verified | 79.3% | — |
| DeepSWE | 37.4% | — |
| SciCode | 53.1% | — |
| WeirdML | 62.6% | — |
| ALE-Bench | 911.02 | — |

## Agentic & Tool Use

- Gemini 3.5 Flash: 24.8 (#107)
- GLM-5V-Turbo: —

| Benchmark | Gemini 3.5 Flash | GLM-5V-Turbo |
|---|---|---|
| APEX-Agents | 27.5% | — |
| GBAEval | 6.7% | — |
| GDP.pdf | 14% | — |
| Vending-Bench 2 | 5,396 | — |

## Reasoning

- Gemini 3.5 Flash: 62.7 (#16)
- GLM-5V-Turbo: 28.5 (#87)

| Benchmark | Gemini 3.5 Flash | GLM-5V-Turbo |
|---|---|---|
| LMArena Hard Prompts | 1488 | 1443 |
| ARC-AGI-2 | 72.1% | — |
| SimpleBench | 76.7% | — |
| NYT Connections (extended) | 92.6% | — |
| ARC-AGI-1 | 92.5% | — |
| CritPt | 13.1% | — |
| Chess Puzzles | 50% | — |
| EnigmaEval | 25.4% | — |
| EBR-Bench | 4.8% | — |
| Mystery Game Puzzles | 32% | — |
| DTBench | 94.7% | — |
| LMCA | 47.1% | — |
| Surface Evolver Bench | 58.1% | — |
| Epoch Capabilities Index | 154.55 | — |
| ForecastBench | 59 | — |

## Math

- Gemini 3.5 Flash: 60.5 (#30)
- GLM-5V-Turbo: 36.6 (#109)

| Benchmark | Gemini 3.5 Flash | GLM-5V-Turbo |
|---|---|---|
| LMArena Math | 1502 | 1440 |
| FrontierMath (Tiers 1-3) | 62.8% | — |
| FrontierMath Tier 4 | 26.8% | — |
| MathArena Final-Answer Competitions | 76.3% | — |
| OTIS Mock AIME 2024-2025 | 95.6% | — |
| ProofBench | 31% | — |
| FrontierMath (Feb 2025 set) | 39% | — |
| FrontierMath Tier 4 (v1) | 14.6% | — |

## Knowledge

- Gemini 3.5 Flash: 66.3 (#10)
- GLM-5V-Turbo: 39.9 (#113)

| Benchmark | Gemini 3.5 Flash | GLM-5V-Turbo |
|---|---|---|
| LMArena Expert | 1493 | 1451 |
| GPQA Diamond | 92.8% | — |
| SimpleQA Verified | 66.2% | — |

## Multimodal

- Gemini 3.5 Flash: 45.7 (#13)
- GLM-5V-Turbo: 40.1 (#41)

| Benchmark | Gemini 3.5 Flash | GLM-5V-Turbo |
|---|---|---|
| LMArena Vision | 1311 | 1264 |
| LMArena Document | 1463 | 1416 |
| Blueprint-Bench 2 | 33.6% | — |

## Multilingual

- Gemini 3.5 Flash: 57.1 (#12)
- GLM-5V-Turbo: 53.2 (#69)

| Benchmark | Gemini 3.5 Flash | GLM-5V-Turbo |
|---|---|---|
| LMArena Non-English | 1475 | 1420 |
| LMArena Chinese | 1525 | 1488 |
| LMArena French | 1490 | 1443 |
| LMArena German | 1500 | 1422 |
| LMArena Korean | 1453 | 1399 |
| LMArena Russian | 1491 | 1432 |
| LMArena Spanish | 1478 | 1446 |
| LMArena Japanese | 1481 | — |

## Instruction Following

- Gemini 3.5 Flash: 77.2 (#29)
- GLM-5V-Turbo: 75.1 (#75)

| Benchmark | Gemini 3.5 Flash | GLM-5V-Turbo |
|---|---|---|
| LMArena Instruction Following | 1466 | 1422 |

## Long Context

- Gemini 3.5 Flash: 45.3 (#39)
- GLM-5V-Turbo: 44.0 (#76)

| Benchmark | Gemini 3.5 Flash | GLM-5V-Turbo |
|---|---|---|
| LMArena Longer Query | 1481 | 1439 |

## Writing & Preference

- Gemini 3.5 Flash: 65.5 (#46)
- GLM-5V-Turbo: 62.6 (#69)

| Benchmark | Gemini 3.5 Flash | GLM-5V-Turbo |
|---|---|---|
| LMArena Text | 1481 | 1437 |
| LMArena Creative Writing | 1467 | 1414 |
| LMArena Multi-Turn | 1482 | 1432 |
| EQ-Bench 4 | 1087 | — |

## FAQ

### Is Gemini 3.5 Flash better than GLM-5V-Turbo?

Gemini 3.5 Flash is the stronger model overall, scoring 54.1 to 43.1 on the Noometry Index. GLM-5V-Turbo costs 1.8× less per token, which makes it the better buy when Gemini 3.5 Flash's lead doesn't matter for your workload.

### Which is cheaper, Gemini 3.5 Flash 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 3.5 Flash lists at $1.50 and $9.

### Is Gemini 3.5 Flash or GLM-5V-Turbo better for coding?

Gemini 3.5 Flash scores higher on coding benchmarks: 49.1 versus 41.8 in the Noometry coding category.

### Which has the bigger context window?

Gemini 3.5 Flash does, with 1.05M tokens against 200K.

### How many benchmarks do Gemini 3.5 Flash and GLM-5V-Turbo share?

19 benchmarks have published results for both models. Gemini 3.5 Flash has 54 scored results on Noometry and GLM-5V-Turbo has 19.