# Gemini 2.5 Flash-Lite vs GLM-5.3

> GLM-5.3 is the stronger model overall, scoring 54.6 to 36.4 on the Noometry Index. Gemini 2.5 Flash-Lite costs 12× less per token, which makes it the better buy when GLM-5.3's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gemini-2-5-flash-lite-vs-glm-5-3
- Last updated: 2026-10-10
- Shared benchmarks: 22

## Summary

- They share 22 benchmarks with published results for both. Gemini 2.5 Flash-Lite scores higher in 0 categories and GLM-5.3 in 9 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-5.3 leads 62.1 to 35.5.
- The biggest single-benchmark swing is WeirdML: 35.2% for Gemini 2.5 Flash-Lite and 75.4% for GLM-5.3.
- Gemini 2.5 Flash-Lite is cheaper at $0.10 / $0.40 per million input/output tokens, against $1.40 / $4.40 for GLM-5.3.
- Gemini 2.5 Flash-Lite accepts more context: 1.05M tokens versus 1M.
- GLM-5.3 has downloadable open weights; the other is API-only.

## Snapshot

| | Gemini 2.5 Flash-Lite | GLM-5.3 |
|---|---|---|
| Provider | Google | Z.ai (Zhipu) |
| Noometry Index | 36.4 | 54.6 |
| Rank | 208 | 25 |
| Context | 1.05M | 1M |
| Input $/M | $0.10 | $1.40 |
| Output $/M | $0.40 | $4.40 |
| Weights | Proprietary | Open |

## Coding

- Gemini 2.5 Flash-Lite: 38.0 (#167)
- GLM-5.3: 59.0 (#12)

| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.3 |
|---|---|---|
| WeirdML | 35.2% | 75.4% |
| LMArena Coding | 1373 | 1499 |
| ALE-Bench | 325.9 | 1,317 |
| DeepSWE | — | 69% |
| FrontierCode | — | 40.1% |
| LMArena WebDev | — | 1623 |
| FrontierSWE | — | 30.2% |
| SciCode | — | 59% |

## Agentic & Tool Use

- Gemini 2.5 Flash-Lite: 27.8 (#89)
- GLM-5.3: 36.3 (#34)

| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.3 |
|---|---|---|
| APEX-Agents | — | 56.6% |
| Berkeley Function Calling Leaderboard | 36.9% | — |
| Vending-Bench 2 | — | 8,164 |

## Reasoning

- Gemini 2.5 Flash-Lite: 21.5 (#196)
- GLM-5.3: 45.2 (#42)

| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.3 |
|---|---|---|
| LMArena Hard Prompts | 1377 | 1491 |
| DTBench | 62.8% | 87.7% |
| LMCA | 18.1% | 55.5% |
| Epoch Capabilities Index | 133.93 | 155.56 |
| Kagi LLM Benchmark | 40.5% | — |
| NYT Connections (extended) | — | 74.2% |
| CritPt | — | 19.1% |
| Chess Puzzles | — | 21% |
| Mystery Game Puzzles | — | 33% |
| Bench to the Future 3 | — | 0.15 |

## Math

- Gemini 2.5 Flash-Lite: 35.5 (#144)
- GLM-5.3: 62.1 (#27)

| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.3 |
|---|---|---|
| LMArena Math | 1373 | 1493 |
| FrontierMath (Tiers 1-3) | — | 68.8% |
| FrontierMath Tier 4 | — | 29.3% |
| OTIS Mock AIME 2024-2025 | — | 91.1% |
| ProofBench | — | 49% |
| Omni-MATH | 48% | — |

## Knowledge

- Gemini 2.5 Flash-Lite: 32.1 (#206)
- GLM-5.3: 58.3 (#34)

| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.3 |
|---|---|---|
| LMArena Expert | 1373 | 1512 |
| GPQA Diamond | — | 90.9% |
| SimpleQA Verified | — | 41% |
| 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: —

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

## Multilingual

- Gemini 2.5 Flash-Lite: 49.5 (#129)
- GLM-5.3: 55.9 (#27)

| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.3 |
|---|---|---|
| LMArena Non-English | 1369 | 1457 |
| LMArena Chinese | 1404 | 1523 |
| LMArena French | 1388 | 1499 |
| LMArena German | 1390 | 1505 |
| LMArena Japanese | 1359 | 1438 |
| LMArena Korean | 1358 | 1478 |
| LMArena Russian | 1373 | 1460 |
| LMArena Spanish | 1396 | 1444 |

## Instruction Following

- Gemini 2.5 Flash-Lite: 70.2 (#163)
- GLM-5.3: 77.8 (#15)

| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.3 |
|---|---|---|
| LMArena Instruction Following | 1366 | 1481 |
| IFEval | 81% | — |

## Long Context

- Gemini 2.5 Flash-Lite: 33.3 (#257)
- GLM-5.3: 45.5 (#32)

| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.3 |
|---|---|---|
| LMArena Longer Query | 1373 | 1485 |
| Fiction.LiveBench | 47.2% | — |

## Writing & Preference

- Gemini 2.5 Flash-Lite: 57.0 (#130)
- GLM-5.3: 75.9 (#6)

| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.3 |
|---|---|---|
| LMArena Text | 1379 | 1473 |
| LMArena Creative Writing | 1366 | 1459 |
| LMArena Multi-Turn | 1367 | 1473 |
| EQ-Bench Creative Writing | — | 2075 |
| WildBench | 81.8% | — |

## FAQ

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

GLM-5.3 is the stronger model overall, scoring 54.6 to 36.4 on the Noometry Index. Gemini 2.5 Flash-Lite costs 12× less per token, which makes it the better buy when GLM-5.3's lead doesn't matter for your workload.

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

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 lists at $1.40 and $4.40.

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

GLM-5.3 scores higher on coding benchmarks: 59.0 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 share?

22 benchmarks have published results for both models. Gemini 2.5 Flash-Lite has 33 scored results on Noometry and GLM-5.3 has 41.