# GLM-5.3-Flash vs Hy3

> GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 44.2 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-5-3-flash-vs-hy3
- Last updated: 2026-10-11
- Shared benchmarks: 18

## Summary

- They share 18 benchmarks with published results for both. GLM-5.3-Flash scores higher in 8 categories and Hy3 in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GLM-5.3-Flash leads 48.0 to 26.1.
- Both cost about the same: $0.15 input and $0.50 output per million tokens.
- GLM-5.3-Flash accepts more context: 1M tokens versus 262K.

## Snapshot

| | GLM-5.3-Flash | Hy3 |
|---|---|---|
| Provider | Z.ai (Zhipu) | Tencent |
| Noometry Index | 51.8 | 44.2 |
| Rank | 41 | 79 |
| Context | 1M | 262K |
| Input $/M | $0.15 | $0.13 |
| Output $/M | $0.50 | $0.53 |
| Weights | Open | Open |

## Coding

- GLM-5.3-Flash: 53.1 (#31)
- Hy3: 46.8 (#63)

| Benchmark | GLM-5.3-Flash | Hy3 |
|---|---|---|
| LMArena WebDev | 1609 | 1508 |
| LMArena Coding | 1508 | 1464 |
| DeepSWE | 63.4% | — |
| FrontierCode | 31.8% | — |
| CursorBench | 36.8% | — |
| FrontierSWE | 18.1% | — |
| SciCode | 51.6% | — |
| ALE-Bench | 303.55 | — |

## Agentic & Tool Use

- GLM-5.3-Flash: 34.2 (#47)
- Hy3: —

| Benchmark | GLM-5.3-Flash | Hy3 |
|---|---|---|
| APEX-Agents | 52.8% | — |
| GDP.pdf | 14% | — |

## Reasoning

- GLM-5.3-Flash: 48.0 (#42)
- Hy3: 26.1 (#136)

| Benchmark | GLM-5.3-Flash | Hy3 |
|---|---|---|
| LMArena Hard Prompts | 1491 | 1447 |
| ARC-AGI-2 | 65.8% | — |
| NYT Connections (extended) | — | 41.2% |
| ARC-AGI-1 | 91% | — |
| CritPt | 15.4% | — |
| Chess Puzzles | 14% | — |
| Mystery Game Puzzles | 8% | — |
| Surface Evolver Bench | 52.5% | — |
| Bench to the Future 3 | 0.15 | — |
| Epoch Capabilities Index | 151.88 | — |

## Math

- GLM-5.3-Flash: 53.3 (#47)
- Hy3: 40.1 (#93)

| Benchmark | GLM-5.3-Flash | Hy3 |
|---|---|---|
| LMArena Math | 1500 | 1475 |
| FrontierMath (Tiers 1-3) | 55.8% | — |
| FrontierMath Tier 4 | 17.1% | — |
| OTIS Mock AIME 2024-2025 | 93.9% | — |
| ProofBench | 21% | — |

## Knowledge

- GLM-5.3-Flash: 58.4 (#36)
- Hy3: 40.8 (#114)

| Benchmark | GLM-5.3-Flash | Hy3 |
|---|---|---|
| LMArena Expert | 1513 | 1460 |
| GPQA Diamond | 90.2% | — |

## Multimodal

- GLM-5.3-Flash: 42.8 (#27)
- Hy3: —

| Benchmark | GLM-5.3-Flash | Hy3 |
|---|---|---|
| LMArena Vision | 1296 | — |

## Multilingual

- GLM-5.3-Flash: 56.0 (#25)
- Hy3: 53.5 (#65)

| Benchmark | GLM-5.3-Flash | Hy3 |
|---|---|---|
| LMArena Non-English | 1462 | 1426 |
| LMArena Chinese | 1527 | 1493 |
| LMArena French | 1496 | 1461 |
| LMArena German | 1470 | 1439 |
| LMArena Japanese | 1429 | 1392 |
| LMArena Korean | 1446 | 1395 |
| LMArena Russian | 1469 | 1432 |
| LMArena Spanish | 1471 | 1456 |

## Instruction Following

- GLM-5.3-Flash: 77.5 (#20)
- Hy3: 75.1 (#70)

| Benchmark | GLM-5.3-Flash | Hy3 |
|---|---|---|
| LMArena Instruction Following | 1478 | 1426 |

## Long Context

- GLM-5.3-Flash: 45.4 (#39)
- Hy3: 44.1 (#75)

| Benchmark | GLM-5.3-Flash | Hy3 |
|---|---|---|
| LMArena Longer Query | 1482 | 1442 |

## Writing & Preference

- GLM-5.3-Flash: 65.3 (#50)
- Hy3: 62.2 (#81)

| Benchmark | GLM-5.3-Flash | Hy3 |
|---|---|---|
| LMArena Text | 1471 | 1439 |
| LMArena Creative Writing | 1442 | 1402 |
| LMArena Multi-Turn | 1467 | 1436 |

## FAQ

### Is GLM-5.3-Flash better than Hy3?

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 44.2 on the Noometry Index.

### Which is cheaper, GLM-5.3-Flash or Hy3?

Hy3 is cheaper. It lists at $0.13 per million input tokens and $0.53 per million output tokens; GLM-5.3-Flash lists at $0.15 and $0.50.

### Is GLM-5.3-Flash or Hy3 better for coding?

GLM-5.3-Flash scores higher on coding benchmarks: 53.1 versus 46.8 in the Noometry coding category.

### Which has the bigger context window?

GLM-5.3-Flash does, with 1M tokens against 262K.

### How many benchmarks do GLM-5.3-Flash and Hy3 share?

18 benchmarks have published results for both models. GLM-5.3-Flash has 40 scored results on Noometry and Hy3 has 19.
