# Claude Opus 5.5 vs GLM-4.6

> Claude Opus 5.5 is the stronger model overall, scoring 68.5 to 40.9 on the Noometry Index. GLM-4.6 costs 8.0× less per token, which makes it the better buy when Claude Opus 5.5's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/claude-opus-5-5-vs-glm-4-6
- Last updated: 2026-10-10
- Shared benchmarks: 15

## Summary

- They share 15 benchmarks with published results for both. Claude Opus 5.5 scores higher in 9 categories and GLM-4.6 in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Claude Opus 5.5 leads 79.5 to 23.1.
- The biggest single-benchmark swing is CritPt: 31.7% for Claude Opus 5.5 and 1.1% for GLM-4.6.
- GLM-4.6 is cheaper at $0.60 / $2.20 per million input/output tokens, against $4 / $20 for Claude Opus 5.5.
- Claude Opus 5.5 accepts more context: 1M tokens versus 205K.
- GLM-4.6 has downloadable open weights; the other is API-only.

## Snapshot

| | Claude Opus 5.5 | GLM-4.6 |
|---|---|---|
| Provider | Anthropic | Z.ai (Zhipu) |
| Noometry Index | 68.5 | 40.9 |
| Rank | 3 | 132 |
| Context | 1M | 205K |
| Input $/M | $4 | $0.60 |
| Output $/M | $20 | $2.20 |
| Weights | Proprietary | Open |

## Coding

- Claude Opus 5.5: 71.4 (#1)
- GLM-4.6: 39.9 (#137)

| Benchmark | Claude Opus 5.5 | GLM-4.6 |
|---|---|---|
| LMArena WebDev | 1820 | 1339 |
| SciCode | 66.9% | 38.4% |
| LMArena Coding | 1545 | 1449 |
| FrontierCode | 54.4% | — |
| SWE-bench Verified (bash only) | — | 55.4% |
| CursorBench | 57.8% | — |
| FrontierSWE | 62.3% | — |
| MirrorCode | 77.4% | — |
| ALE-Bench | — | 340.82 |

## Agentic & Tool Use

- Claude Opus 5.5: 45.3 (#13)
- GLM-4.6: 32.1 (#60)

| Benchmark | Claude Opus 5.5 | GLM-4.6 |
|---|---|---|
| Terminal-Bench | — | 24.5% |
| APEX-Agents | 73.5% | — |
| Berkeley Function Calling Leaderboard | — | 72.4% |
| GDP.pdf | 30.6% | — |

## Reasoning

- Claude Opus 5.5: 79.5 (#2)
- GLM-4.6: 23.1 (#168)

| Benchmark | Claude Opus 5.5 | GLM-4.6 |
|---|---|---|
| CritPt | 31.7% | 1.1% |
| LMArena Hard Prompts | 1545 | 1440 |
| ARC-AGI-2 | 92.5% | — |
| Kagi LLM Benchmark | — | 47.4% |
| NYT Connections (extended) | 88.5% | — |
| ARC-AGI-1 | 97.5% | — |
| EBR-Bench | 71.4% | — |
| Mystery Game Puzzles | 71% | — |
| DTBench | 98.9% | — |
| LMCA | 68.2% | — |

## Math

- Claude Opus 5.5: 92.4 (#2)
- GLM-4.6: 36.4 (#115)

| Benchmark | Claude Opus 5.5 | GLM-4.6 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 91.2% | — |
| FrontierMath Tier 4 | 95% | — |
| OTIS Mock AIME 2024-2025 | 100% | — |
| ProofBench | 100% | — |
| LMArena Math | — | 1431 |
| FrontierMath (Feb 2025 set) | — | 3.8% |
| FrontierMath Tier 4 (v1) | — | 2.1% |

## Knowledge

- Claude Opus 5.5: 66.6 (#9)
- GLM-4.6: 39.6 (#118)

| Benchmark | Claude Opus 5.5 | GLM-4.6 |
|---|---|---|
| LMArena Expert | 1564 | 1432 |
| GPQA Diamond | 90.6% | — |
| SimpleQA Verified | 72.2% | — |
| Vectara Hallucination Rate | — | 9.5% |

## Multimodal

- Claude Opus 5.5: 56.5 (#2)
- GLM-4.6: —

| Benchmark | Claude Opus 5.5 | GLM-4.6 |
|---|---|---|
| Furniture Assembly | 83.3% | — |

## Multilingual

- Claude Opus 5.5: 59.8 (#1)
- GLM-4.6: 53.6 (#62)

| Benchmark | Claude Opus 5.5 | GLM-4.6 |
|---|---|---|
| LMArena Non-English | 1513 | 1426 |
| LMArena Chinese | 1572 | 1500 |
| LMArena Russian | 1532 | 1418 |
| LMArena French | — | 1459 |
| LMArena German | — | 1447 |
| LMArena Japanese | — | 1394 |
| LMArena Korean | — | 1401 |
| LMArena Spanish | — | 1436 |

## Instruction Following

- Claude Opus 5.5: 80.1 (#2)
- GLM-4.6: 74.5 (#93)

| Benchmark | Claude Opus 5.5 | GLM-4.6 |
|---|---|---|
| LMArena Instruction Following | 1535 | 1410 |

## Long Context

- Claude Opus 5.5: 47.3 (#18)
- GLM-4.6: 43.4 (#91)

| Benchmark | Claude Opus 5.5 | GLM-4.6 |
|---|---|---|
| LMArena Longer Query | 1540 | 1423 |

## Writing & Preference

- Claude Opus 5.5: 78.7 (#3)
- GLM-4.6: 61.3 (#86)

| Benchmark | Claude Opus 5.5 | GLM-4.6 |
|---|---|---|
| LMArena Text | 1518 | 1440 |
| LMArena Creative Writing | 1538 | 1411 |
| EQ-Bench Creative Writing | 2050 | 1411 |
| LMArena Multi-Turn | 1520 | 1427 |

## FAQ

### Is Claude Opus 5.5 better than GLM-4.6?

Claude Opus 5.5 is the stronger model overall, scoring 68.5 to 40.9 on the Noometry Index. GLM-4.6 costs 8.0× less per token, which makes it the better buy when Claude Opus 5.5's lead doesn't matter for your workload.

### Which is cheaper, Claude Opus 5.5 or GLM-4.6?

GLM-4.6 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; Claude Opus 5.5 lists at $4 and $20.

### Is Claude Opus 5.5 or GLM-4.6 better for coding?

Claude Opus 5.5 scores higher on coding benchmarks: 71.4 versus 39.9 in the Noometry coding category.

### Which has the bigger context window?

Claude Opus 5.5 does, with 1M tokens against 205K.

### How many benchmarks do Claude Opus 5.5 and GLM-4.6 share?

15 benchmarks have published results for both models. Claude Opus 5.5 has 35 scored results on Noometry and GLM-4.6 has 29.