# Claude Opus 4.7 vs GLM-5.3-Flash

> Claude Opus 4.7 is the stronger model overall, scoring 58.4 to 49.6 on the Noometry Index. GLM-5.3-Flash costs 42× less per token, which makes it the better buy when Claude Opus 4.7's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/claude-opus-4-7-vs-glm-5-3-flash
- Last updated: 2026-10-10
- Shared benchmarks: 33

## Summary

- They share 33 benchmarks with published results for both. Claude Opus 4.7 scores higher in 9 categories and GLM-5.3-Flash in 1 category; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Claude Opus 4.7 leads 53.7 to 31.7.
- The biggest single-benchmark swing is ProofBench: 54% for Claude Opus 4.7 and 21% for GLM-5.3-Flash.
- GLM-5.3-Flash is cheaper at $0.15 / $0.50 per million input/output tokens, against $5 / $25 for Claude Opus 4.7.
- GLM-5.3-Flash has downloadable open weights; the other is API-only.

## Snapshot

| | Claude Opus 4.7 | GLM-5.3-Flash |
|---|---|---|
| Provider | Anthropic | Z.ai (Zhipu) |
| Noometry Index | 58.4 | 49.6 |
| Rank | 17 | 45 |
| Context | 1M | 1M |
| Input $/M | $5 | $0.15 |
| Output $/M | $25 | $0.50 |
| Weights | Proprietary | Open |

## Coding

- Claude Opus 4.7: 59.9 (#10)
- GLM-5.3-Flash: 53.7 (#26)

| Benchmark | Claude Opus 4.7 | GLM-5.3-Flash |
|---|---|---|
| FrontierCode | 38.5% | 31.8% |
| LMArena WebDev | 1557 | 1614 |
| SciCode | 54.5% | 51.6% |
| LMArena Coding | 1519 | 1506 |
| ALE-Bench | 1,323 | 303.55 |
| SWE-bench Verified | 83.5% | — |
| DeepSWE | — | 63.4% |
| GSO | 44.1% | — |
| WeirdML | 76.4% | — |
| MirrorCode | 31.1% | — |

## Agentic & Tool Use

- Claude Opus 4.7: 47.9 (#8)
- GLM-5.3-Flash: 34.3 (#41)

| Benchmark | Claude Opus 4.7 | GLM-5.3-Flash |
|---|---|---|
| APEX-Agents | 49.2% | 52.8% |
| GDP.pdf | 21% | 14% |
| Terminal-Bench | 80.2% | — |
| OSWorld 2.0 | 18.2% | — |
| τ²-bench Banking | 40.2% | — |
| PostTrainBench | 28.6% | — |
| ExploitBench | 26.5% | — |
| GBAEval | 43.8% | — |
| LMArena Search | 1233 | — |
| Vending-Bench 2 | 10,937 | — |

## Reasoning

- Claude Opus 4.7: 53.7 (#24)
- GLM-5.3-Flash: 31.7 (#69)

| Benchmark | Claude Opus 4.7 | GLM-5.3-Flash |
|---|---|---|
| CritPt | 12% | 15.4% |
| Chess Puzzles | 30% | 14% |
| LMArena Hard Prompts | 1507 | 1490 |
| Mystery Game Puzzles | 28% | 8% |
| Epoch Capabilities Index | 156.39 | 151.9 |
| ARC-AGI-2 | 75.8% | — |
| SimpleBench | 61.7% | — |
| Kagi LLM Benchmark | 80.7% | — |
| NYT Connections (extended) | 39% | — |
| ARC-AGI-1 | 93.5% | — |
| Thematic Generalization | 72.8% | — |
| EBR-Bench | 19% | — |
| DTBench | 94.7% | — |
| LMCA | 52.2% | — |
| Surface Evolver Bench | — | 52.5% |
| Bench to the Future 3 | — | 0.15 |
| ForecastBench | 60.3 | — |

## Math

- Claude Opus 4.7: 66.5 (#20)
- GLM-5.3-Flash: 53.1 (#38)

| Benchmark | Claude Opus 4.7 | GLM-5.3-Flash |
|---|---|---|
| FrontierMath (Tiers 1-3) | 70.2% | 55.8% |
| FrontierMath Tier 4 | 31.7% | 17.1% |
| OTIS Mock AIME 2024-2025 | 97.8% | 93.9% |
| ProofBench | 54% | 21% |
| LMArena Math | 1499 | 1499 |
| MathArena Final-Answer Competitions | 73.6% | — |
| FrontierMath (Feb 2025 set) | 43.8% | — |
| FrontierMath Tier 4 (v1) | 22.9% | — |

## Knowledge

- Claude Opus 4.7: 62.6 (#20)
- GLM-5.3-Flash: 58.4 (#33)

| Benchmark | Claude Opus 4.7 | GLM-5.3-Flash |
|---|---|---|
| GPQA Diamond | 90.2% | 90.2% |
| LMArena Expert | 1521 | 1512 |
| Humanity's Last Exam | 36.2% | — |
| SimpleQA Verified | 51.7% | — |
| Vectara Hallucination Rate | 12% | — |

## Multimodal

- Claude Opus 4.7: 41.5 (#29)
- GLM-5.3-Flash: 42.6 (#25)

| Benchmark | Claude Opus 4.7 | GLM-5.3-Flash |
|---|---|---|
| LMArena Vision | 1317 | 1304 |
| Blueprint-Bench 2 | 24.5% | — |
| Furniture Assembly | 33.3% | — |
| LMArena Document | 1495 | — |

## Multilingual

- Claude Opus 4.7: 57.5 (#9)
- GLM-5.3-Flash: 56.2 (#24)

| Benchmark | Claude Opus 4.7 | GLM-5.3-Flash |
|---|---|---|
| LMArena Non-English | 1481 | 1462 |
| LMArena Chinese | 1530 | 1529 |
| LMArena French | 1505 | 1495 |
| LMArena German | 1494 | 1457 |
| LMArena Japanese | 1472 | 1420 |
| LMArena Korean | 1466 | 1443 |
| LMArena Russian | 1494 | 1472 |
| LMArena Spanish | 1497 | 1471 |

## Instruction Following

- Claude Opus 4.7: 78.6 (#9)
- GLM-5.3-Flash: 77.8 (#17)

| Benchmark | Claude Opus 4.7 | GLM-5.3-Flash |
|---|---|---|
| LMArena Instruction Following | 1498 | 1480 |

## Long Context

- Claude Opus 4.7: 46.1 (#24)
- GLM-5.3-Flash: 45.3 (#41)

| Benchmark | Claude Opus 4.7 | GLM-5.3-Flash |
|---|---|---|
| LMArena Longer Query | 1505 | 1479 |

## Writing & Preference

- Claude Opus 4.7: 75.3 (#8)
- GLM-5.3-Flash: 65.4 (#49)

| Benchmark | Claude Opus 4.7 | GLM-5.3-Flash |
|---|---|---|
| LMArena Text | 1491 | 1471 |
| LMArena Creative Writing | 1486 | 1440 |
| LMArena Multi-Turn | 1506 | 1471 |
| EQ-Bench Creative Writing | 1914 | — |
| EQ-Bench 4 | 1311 | — |

## FAQ

### Is Claude Opus 4.7 better than GLM-5.3-Flash?

Claude Opus 4.7 is the stronger model overall, scoring 58.4 to 49.6 on the Noometry Index. GLM-5.3-Flash costs 42× less per token, which makes it the better buy when Claude Opus 4.7's lead doesn't matter for your workload.

### Which is cheaper, Claude Opus 4.7 or GLM-5.3-Flash?

GLM-5.3-Flash is cheaper. It lists at $0.15 per million input tokens and $0.50 per million output tokens; Claude Opus 4.7 lists at $5 and $25.

### Is Claude Opus 4.7 or GLM-5.3-Flash better for coding?

Claude Opus 4.7 scores higher on coding benchmarks: 59.9 versus 53.7 in the Noometry coding category.

### Which has the bigger context window?

Both accept 1M tokens.

### How many benchmarks do Claude Opus 4.7 and GLM-5.3-Flash share?

33 benchmarks have published results for both models. Claude Opus 4.7 has 66 scored results on Noometry and GLM-5.3-Flash has 36.