# GLM-5.3-Flash vs Inkling

> GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 44.1 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-5-3-flash-vs-inkling
- Last updated: 2026-10-11
- Shared benchmarks: 33

## Summary

- They share 33 benchmarks with published results for both. GLM-5.3-Flash scores higher in 9 categories and Inkling in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-5.3-Flash leads 53.3 to 31.3.
- The biggest single-benchmark swing is ARC-AGI-2: 65.8% for GLM-5.3-Flash and 36.5% for Inkling.
- GLM-5.3-Flash is cheaper at $0.15 / $0.50 per million input/output tokens, against $1.87 / $4.68 for Inkling.
- GLM-5.3-Flash accepts more context: 1M tokens versus 66K.

## Snapshot

| | GLM-5.3-Flash | Inkling |
|---|---|---|
| Provider | Z.ai (Zhipu) | Thinking Machines Lab |
| Noometry Index | 51.8 | 44.1 |
| Rank | 41 | 80 |
| Context | 1M | 66K |
| Input $/M | $0.15 | $1.87 |
| Output $/M | $0.50 | $4.68 |
| Weights | Open | Open |

## Coding

- GLM-5.3-Flash: 53.1 (#31)
- Inkling: 34.5 (#234)

| Benchmark | GLM-5.3-Flash | Inkling |
|---|---|---|
| FrontierCode | 31.8% | 14% |
| LMArena WebDev | 1609 | 1413 |
| FrontierSWE | 18.1% | 4.1% |
| SciCode | 51.6% | 47% |
| LMArena Coding | 1508 | 1464 |
| ALE-Bench | 303.55 | 946 |
| DeepSWE | 63.4% | — |
| CursorBench | 36.8% | — |
| WeirdML | — | 32.3% |

## Agentic & Tool Use

- GLM-5.3-Flash: 34.2 (#47)
- Inkling: 29.6 (#85)

| Benchmark | GLM-5.3-Flash | Inkling |
|---|---|---|
| APEX-Agents | 52.8% | 33.8% |
| τ²-bench Banking | — | 25% |
| GDP.pdf | 14% | — |

## Reasoning

- GLM-5.3-Flash: 48.0 (#42)
- Inkling: 40.4 (#56)

| Benchmark | GLM-5.3-Flash | Inkling |
|---|---|---|
| ARC-AGI-2 | 65.8% | 36.5% |
| ARC-AGI-1 | 91% | 79.5% |
| CritPt | 15.4% | 5.4% |
| Chess Puzzles | 14% | 21% |
| LMArena Hard Prompts | 1491 | 1451 |
| Epoch Capabilities Index | 151.88 | 148.54 |
| SimpleBench | — | 50% |
| Mystery Game Puzzles | 8% | — |
| DTBench | — | 87.5% |
| LMCA | — | 37.6% |
| Surface Evolver Bench | 52.5% | — |
| Bench to the Future 3 | 0.15 | — |

## Math

- GLM-5.3-Flash: 53.3 (#47)
- Inkling: 31.3 (#225)

| Benchmark | GLM-5.3-Flash | Inkling |
|---|---|---|
| FrontierMath (Tiers 1-3) | 55.8% | 33.3% |
| FrontierMath Tier 4 | 17.1% | 4.9% |
| OTIS Mock AIME 2024-2025 | 93.9% | 88.9% |
| ProofBench | 21% | 0% |
| LMArena Math | 1500 | 1479 |

## Knowledge

- GLM-5.3-Flash: 58.4 (#36)
- Inkling: 55.1 (#49)

| Benchmark | GLM-5.3-Flash | Inkling |
|---|---|---|
| GPQA Diamond | 90.2% | 88.3% |
| LMArena Expert | 1513 | 1465 |
| SimpleQA Verified | — | 40.3% |

## Multimodal

- GLM-5.3-Flash: 42.8 (#27)
- Inkling: —

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

## Multilingual

- GLM-5.3-Flash: 56.0 (#25)
- Inkling: 54.0 (#52)

| Benchmark | GLM-5.3-Flash | Inkling |
|---|---|---|
| LMArena Non-English | 1462 | 1434 |
| LMArena Chinese | 1527 | 1490 |
| LMArena French | 1496 | 1458 |
| LMArena German | 1470 | 1446 |
| LMArena Japanese | 1429 | 1429 |
| LMArena Korean | 1446 | 1404 |
| LMArena Russian | 1469 | 1429 |
| LMArena Spanish | 1471 | 1448 |

## Instruction Following

- GLM-5.3-Flash: 77.5 (#20)
- Inkling: 75.1 (#71)

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

## Long Context

- GLM-5.3-Flash: 45.4 (#39)
- Inkling: 43.8 (#86)

| Benchmark | GLM-5.3-Flash | Inkling |
|---|---|---|
| LMArena Longer Query | 1482 | 1434 |

## Writing & Preference

- GLM-5.3-Flash: 65.3 (#50)
- Inkling: 65.2 (#51)

| Benchmark | GLM-5.3-Flash | Inkling |
|---|---|---|
| LMArena Text | 1471 | 1441 |
| LMArena Creative Writing | 1442 | 1387 |
| LMArena Multi-Turn | 1467 | 1436 |
| EQ-Bench Creative Writing | — | 1611 |
| EQ-Bench 4 | — | 1226 |

## FAQ

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

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 44.1 on the Noometry Index.

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

GLM-5.3-Flash is cheaper. It lists at $0.15 per million input tokens and $0.50 per million output tokens; Inkling lists at $1.87 and $4.68.

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

GLM-5.3-Flash scores higher on coding benchmarks: 53.1 versus 34.5 in the Noometry coding category.

### Which has the bigger context window?

GLM-5.3-Flash does, with 1M tokens against 66K.

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

33 benchmarks have published results for both models. GLM-5.3-Flash has 40 scored results on Noometry and Inkling has 41.