# Gemini 2.5 Flash-Lite vs GLM-5.3-Flash

> GLM-5.3-Flash is the stronger model overall, scoring 49.6 to 36.4 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gemini-2-5-flash-lite-vs-glm-5-3-flash
- Last updated: 2026-10-10
- Shared benchmarks: 20

## Summary

- They share 20 benchmarks with published results for both. Gemini 2.5 Flash-Lite scores higher in 0 categories and GLM-5.3-Flash in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-5.3-Flash leads 58.4 to 32.1.
- Gemini 2.5 Flash-Lite is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.15 / $0.50 for GLM-5.3-Flash.
- Gemini 2.5 Flash-Lite accepts more context: 1.05M tokens versus 1M.
- GLM-5.3-Flash has downloadable open weights; the other is API-only.

## Snapshot

| | Gemini 2.5 Flash-Lite | GLM-5.3-Flash |
|---|---|---|
| Provider | Google | Z.ai (Zhipu) |
| Noometry Index | 36.4 | 49.6 |
| Rank | 208 | 45 |
| Context | 1.05M | 1M |
| Input $/M | $0.10 | $0.15 |
| Output $/M | $0.40 | $0.50 |
| Weights | Proprietary | Open |

## Coding

- Gemini 2.5 Flash-Lite: 38.0 (#167)
- GLM-5.3-Flash: 53.7 (#26)

| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.3-Flash |
|---|---|---|
| LMArena Coding | 1373 | 1506 |
| ALE-Bench | 325.9 | 303.55 |
| DeepSWE | — | 63.4% |
| FrontierCode | — | 31.8% |
| LMArena WebDev | — | 1614 |
| SciCode | — | 51.6% |
| WeirdML | 35.2% | — |

## Agentic & Tool Use

- Gemini 2.5 Flash-Lite: 27.8 (#89)
- GLM-5.3-Flash: 34.3 (#41)

| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.3-Flash |
|---|---|---|
| APEX-Agents | — | 52.8% |
| Berkeley Function Calling Leaderboard | 36.9% | — |
| GDP.pdf | — | 14% |

## Reasoning

- Gemini 2.5 Flash-Lite: 21.5 (#196)
- GLM-5.3-Flash: 31.7 (#69)

| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.3-Flash |
|---|---|---|
| LMArena Hard Prompts | 1377 | 1490 |
| Epoch Capabilities Index | 133.93 | 151.9 |
| Kagi LLM Benchmark | 40.5% | — |
| CritPt | — | 15.4% |
| Chess Puzzles | — | 14% |
| Mystery Game Puzzles | — | 8% |
| DTBench | 62.8% | — |
| LMCA | 18.1% | — |
| Surface Evolver Bench | — | 52.5% |
| Bench to the Future 3 | — | 0.15 |

## Math

- Gemini 2.5 Flash-Lite: 35.5 (#144)
- GLM-5.3-Flash: 53.1 (#38)

| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.3-Flash |
|---|---|---|
| LMArena Math | 1373 | 1499 |
| FrontierMath (Tiers 1-3) | — | 55.8% |
| FrontierMath Tier 4 | — | 17.1% |
| OTIS Mock AIME 2024-2025 | — | 93.9% |
| ProofBench | — | 21% |
| Omni-MATH | 48% | — |

## Knowledge

- Gemini 2.5 Flash-Lite: 32.1 (#206)
- GLM-5.3-Flash: 58.4 (#33)

| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.3-Flash |
|---|---|---|
| LMArena Expert | 1373 | 1512 |
| GPQA Diamond | — | 90.2% |
| MMLU-Pro | 53.7% | — |
| Vectara Hallucination Rate | 3.3% | — |
| GPQA (HELM) | 30.9% | — |

## Multimodal

- Gemini 2.5 Flash-Lite: 28.6 (#109)
- GLM-5.3-Flash: 42.6 (#25)

| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.3-Flash |
|---|---|---|
| LMArena Vision | 1198 | 1304 |
| VPCT | 30% | — |

## Multilingual

- Gemini 2.5 Flash-Lite: 49.5 (#129)
- GLM-5.3-Flash: 56.2 (#24)

| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.3-Flash |
|---|---|---|
| LMArena Non-English | 1369 | 1462 |
| LMArena Chinese | 1404 | 1529 |
| LMArena French | 1388 | 1495 |
| LMArena German | 1390 | 1457 |
| LMArena Japanese | 1359 | 1420 |
| LMArena Korean | 1358 | 1443 |
| LMArena Russian | 1373 | 1472 |
| LMArena Spanish | 1396 | 1471 |

## Instruction Following

- Gemini 2.5 Flash-Lite: 70.2 (#163)
- GLM-5.3-Flash: 77.8 (#17)

| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.3-Flash |
|---|---|---|
| LMArena Instruction Following | 1366 | 1480 |
| IFEval | 81% | — |

## Long Context

- Gemini 2.5 Flash-Lite: 33.3 (#257)
- GLM-5.3-Flash: 45.3 (#41)

| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.3-Flash |
|---|---|---|
| LMArena Longer Query | 1373 | 1479 |
| Fiction.LiveBench | 47.2% | — |

## Writing & Preference

- Gemini 2.5 Flash-Lite: 57.0 (#130)
- GLM-5.3-Flash: 65.4 (#49)

| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.3-Flash |
|---|---|---|
| LMArena Text | 1379 | 1471 |
| LMArena Creative Writing | 1366 | 1440 |
| LMArena Multi-Turn | 1367 | 1471 |
| WildBench | 81.8% | — |

## FAQ

### Is Gemini 2.5 Flash-Lite better than GLM-5.3-Flash?

GLM-5.3-Flash is the stronger model overall, scoring 49.6 to 36.4 on the Noometry Index.

### Which is cheaper, Gemini 2.5 Flash-Lite or GLM-5.3-Flash?

Gemini 2.5 Flash-Lite is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; GLM-5.3-Flash lists at $0.15 and $0.50.

### Is Gemini 2.5 Flash-Lite or GLM-5.3-Flash better for coding?

GLM-5.3-Flash scores higher on coding benchmarks: 53.7 versus 38.0 in the Noometry coding category.

### Which has the bigger context window?

Gemini 2.5 Flash-Lite does, with 1.05M tokens against 1M.

### How many benchmarks do Gemini 2.5 Flash-Lite and GLM-5.3-Flash share?

20 benchmarks have published results for both models. Gemini 2.5 Flash-Lite has 33 scored results on Noometry and GLM-5.3-Flash has 36.