# Claude Opus 4.6 vs GLM-5.3

> Claude Opus 4.6 is the stronger model overall, scoring 58.2 to 54.8 on the Noometry Index. GLM-5.3 costs 4.7× less per token, which makes it the better buy when Claude Opus 4.6's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/claude-opus-4-6-vs-glm-5-3
- Last updated: 2026-10-10
- Shared benchmarks: 36

## Summary

- They share 36 benchmarks with published results for both. Claude Opus 4.6 scores higher in 7 categories and GLM-5.3 in 2 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in agentic & tool use, where Claude Opus 4.6 leads 51.1 to 36.4.
- The biggest single-benchmark swing is NYT Connections (extended): 92.1% for Claude Opus 4.6 and 74.2% for GLM-5.3.
- GLM-5.3 is cheaper at $1.40 / $4.40 per million input/output tokens, against $5 / $25 for Claude Opus 4.6.
- GLM-5.3 has downloadable open weights; the other is API-only.

## Snapshot

| | Claude Opus 4.6 | GLM-5.3 |
|---|---|---|
| Provider | Anthropic | Z.ai (Zhipu) |
| Noometry Index | 58.2 | 54.8 |
| Rank | 20 | 26 |
| Context | 1M | 1M |
| Input $/M | $5 | $1.40 |
| Output $/M | $25 | $4.40 |
| Weights | Proprietary | Open |

## Coding

- Claude Opus 4.6: 57.2 (#20)
- GLM-5.3: 59.5 (#14)

| Benchmark | Claude Opus 4.6 | GLM-5.3 |
|---|---|---|
| FrontierCode | 26.6% | 40.1% |
| LMArena WebDev | 1547 | 1622 |
| WeirdML | 78% | 75.4% |
| LMArena Coding | 1536 | 1496 |
| ALE-Bench | 996.5 | 1,317 |
| SWE-bench Verified | 78.7% | — |
| DeepSWE | — | 69% |
| SWE-bench Verified (bash only) | 75.6% | — |
| CursorBench | — | 42.6% |
| SWE-bench Multilingual | 72% | — |
| FrontierSWE | — | 30.2% |
| SciCode | — | 59% |
| GSO | 41.2% | — |
| AlgoTune | 1.47 | — |

## Agentic & Tool Use

- Claude Opus 4.6: 51.1 (#4)
- GLM-5.3: 36.4 (#38)

| Benchmark | Claude Opus 4.6 | GLM-5.3 |
|---|---|---|
| APEX-Agents | 46.3% | 56.6% |
| Vending-Bench 2 | 8,018 | 8,164 |
| Terminal-Bench | 79.8% | — |
| Remote Labor Index | 4.2% | — |
| τ²-bench Banking | 27.3% | — |
| Cybench | 93% | — |
| DeepResearch Bench | 55.3% | — |
| GBAEval | 44.1% | — |
| LMArena Search | 1253 | — |
| METR Time Horizons | 78.9% | — |

## Reasoning

- Claude Opus 4.6: 57.8 (#23)
- GLM-5.3: 46.1 (#46)

| Benchmark | Claude Opus 4.6 | GLM-5.3 |
|---|---|---|
| NYT Connections (extended) | 92.1% | 74.2% |
| Chess Puzzles | 17% | 21% |
| LMArena Hard Prompts | 1527 | 1489 |
| Mystery Game Puzzles | 25% | 33% |
| DTBench | 91.2% | 87.7% |
| LMCA | 55.8% | 55.5% |
| Epoch Capabilities Index | 155.24 | 155.61 |
| ARC-AGI-2 | 69.2% | — |
| SimpleBench | 67.6% | — |
| Kagi LLM Benchmark | 83.6% | — |
| ARC-AGI-1 | 94% | — |
| CritPt | — | 19.1% |
| EnigmaEval | 7.6% | — |
| Thematic Generalization | 80.6% | — |
| EBR-Bench | 12.7% | — |
| Bench to the Future 3 | — | 0.15 |
| ForecastBench | 60 | — |

## Math

- Claude Opus 4.6: 63.0 (#31)
- GLM-5.3: 62.3 (#33)

| Benchmark | Claude Opus 4.6 | GLM-5.3 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 66% | 68.8% |
| FrontierMath Tier 4 | 26.8% | 29.3% |
| OTIS Mock AIME 2024-2025 | 94.4% | 91.1% |
| ProofBench | 50% | 49% |
| LMArena Math | 1519 | 1489 |
| MathArena Final-Answer Competitions | 78.5% | — |
| FrontierMath (Feb 2025 set) | 40.7% | — |
| FrontierMath Tier 4 (v1) | 22.9% | — |

## Knowledge

- Claude Opus 4.6: 61.9 (#26)
- GLM-5.3: 58.3 (#37)

| Benchmark | Claude Opus 4.6 | GLM-5.3 |
|---|---|---|
| GPQA Diamond | 90.5% | 90.9% |
| SimpleQA Verified | 47% | 41% |
| LMArena Expert | 1546 | 1516 |
| Humanity's Last Exam | 34.4% | — |
| Vectara Hallucination Rate | 12.2% | — |

## Multimodal

- Claude Opus 4.6: 37.3 (#74)
- GLM-5.3: —

| Benchmark | Claude Opus 4.6 | GLM-5.3 |
|---|---|---|
| LMArena Vision | 1316 | — |
| Furniture Assembly | 28.3% | — |
| LMArena Document | 1507 | — |

## Multilingual

- Claude Opus 4.6: 57.9 (#6)
- GLM-5.3: 55.7 (#28)

| Benchmark | Claude Opus 4.6 | GLM-5.3 |
|---|---|---|
| LMArena Non-English | 1489 | 1457 |
| LMArena Chinese | 1551 | 1528 |
| LMArena French | 1513 | 1499 |
| LMArena German | 1502 | 1499 |
| LMArena Japanese | 1484 | 1453 |
| LMArena Korean | 1464 | 1472 |
| LMArena Russian | 1497 | 1463 |
| LMArena Spanish | 1510 | 1460 |

## Instruction Following

- Claude Opus 4.6: 79.5 (#4)
- GLM-5.3: 77.5 (#23)

| Benchmark | Claude Opus 4.6 | GLM-5.3 |
|---|---|---|
| LMArena Instruction Following | 1523 | 1477 |

## Long Context

- Claude Opus 4.6: 48.1 (#13)
- GLM-5.3: 45.4 (#41)

| Benchmark | Claude Opus 4.6 | GLM-5.3 |
|---|---|---|
| LMArena Longer Query | 1520 | 1482 |
| CL-bench | 20.7% | — |
| CL-bench Life | 17% | — |

## Writing & Preference

- Claude Opus 4.6: 73.5 (#10)
- GLM-5.3: 75.7 (#6)

| Benchmark | Claude Opus 4.6 | GLM-5.3 |
|---|---|---|
| LMArena Text | 1503 | 1471 |
| LMArena Creative Writing | 1505 | 1457 |
| EQ-Bench Creative Writing | 1809 | 2075 |
| LMArena Multi-Turn | 1513 | 1472 |
| EQ-Bench 4 | 1223 | — |

## FAQ

### Is Claude Opus 4.6 better than GLM-5.3?

Claude Opus 4.6 is the stronger model overall, scoring 58.2 to 54.8 on the Noometry Index. GLM-5.3 costs 4.7× less per token, which makes it the better buy when Claude Opus 4.6's lead doesn't matter for your workload.

### Which is cheaper, Claude Opus 4.6 or GLM-5.3?

GLM-5.3 is cheaper. It lists at $1.40 per million input tokens and $4.40 per million output tokens; Claude Opus 4.6 lists at $5 and $25.

### Is Claude Opus 4.6 or GLM-5.3 better for coding?

GLM-5.3 scores higher on coding benchmarks: 59.5 versus 57.2 in the Noometry coding category.

### Which has the bigger context window?

Both accept 1M tokens.

### How many benchmarks do Claude Opus 4.6 and GLM-5.3 share?

36 benchmarks have published results for both models. Claude Opus 4.6 has 68 scored results on Noometry and GLM-5.3 has 42.