# Claude Haiku 4.5 vs GLM-4.6

> GLM-4.6 is the stronger model overall, scoring 41.4 to 39.5 on the Noometry Index.

- Canonical page: https://noometry.com/compare/claude-haiku-4-5-vs-glm-4-6
- Last updated: 2026-10-12
- Shared benchmarks: 27

## Summary

- They share 27 benchmarks with published results for both. Claude Haiku 4.5 scores higher in 4 categories and GLM-4.6 in 5 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GLM-4.6 leads 23.7 to 15.1.
- The biggest single-benchmark swing is SWE-bench Verified (bash only): 66.6% for Claude Haiku 4.5 and 55.4% for GLM-4.6.
- GLM-4.6 is cheaper at $0.60 / $2.20 per million input/output tokens, against $1 / $5 for Claude Haiku 4.5.
- GLM-4.6 accepts more context: 205K tokens versus 200K.
- GLM-4.6 has downloadable open weights; the other is API-only.

## Snapshot

| | Claude Haiku 4.5 | GLM-4.6 |
|---|---|---|
| Provider | Anthropic | Z.ai (Zhipu) |
| Noometry Index | 39.5 | 41.4 |
| Rank | 165 | 135 |
| Context | 200K | 205K |
| Input $/M | $1 | $0.60 |
| Output $/M | $5 | $2.20 |
| Weights | Proprietary | Open |

## Coding

- Claude Haiku 4.5: 44.0 (#78)
- GLM-4.6: 40.1 (#148)

| Benchmark | Claude Haiku 4.5 | GLM-4.6 |
|---|---|---|
| SWE-bench Verified (bash only) | 66.6% | 55.4% |
| LMArena WebDev | 1330 | 1340 |
| SciCode | 43.3% | 38.4% |
| LMArena Coding | 1453 | 1449 |
| ALE-Bench | 653.48 | 340.82 |
| SWE-bench Multilingual | 64.7% | — |
| WeirdML | 45.4% | — |

## Agentic & Tool Use

- Claude Haiku 4.5: 33.6 (#52)
- GLM-4.6: 32.3 (#66)

| Benchmark | Claude Haiku 4.5 | GLM-4.6 |
|---|---|---|
| Terminal-Bench | 35.5% | 24.5% |
| Berkeley Function Calling Leaderboard | 68.7% | 72.4% |
| DeepResearch Bench | 45.5% | — |
| BALROG | 31.2% | — |
| ExploitBench | 13.7% | — |
| Vending-Bench 2 | 458.89 | — |

## Reasoning

- Claude Haiku 4.5: 15.1 (#320)
- GLM-4.6: 23.7 (#172)

| Benchmark | Claude Haiku 4.5 | GLM-4.6 |
|---|---|---|
| CritPt | 0% | 1.1% |
| LMArena Hard Prompts | 1420 | 1440 |
| ARC-AGI-2 | 4% | — |
| Kagi LLM Benchmark | — | 47.4% |
| NYT Connections (extended) | 14.3% | — |
| ARC-AGI-1 | 47.7% | — |
| Chess Puzzles | 8% | — |
| DTBench | 73.6% | — |
| LMCA | 30.9% | — |
| Epoch Capabilities Index | 142.41 | — |
| ForecastBench | 61.4 | — |

## Math

- Claude Haiku 4.5: 44.9 (#78)
- GLM-4.6: 39.1 (#111)

| Benchmark | Claude Haiku 4.5 | GLM-4.6 |
|---|---|---|
| LMArena Math | 1396 | 1432 |
| FrontierMath (Feb 2025 set) | 5.9% | 3.8% |
| FrontierMath Tier 4 (v1) | 2.1% | 2.1% |
| OTIS Mock AIME 2024-2025 | 66.7% | — |
| Omni-MATH | 56.1% | — |
| MATH Level 5 | 96.4% | — |

## Knowledge

- Claude Haiku 4.5: 37.7 (#153)
- GLM-4.6: 40.2 (#124)

| Benchmark | Claude Haiku 4.5 | GLM-4.6 |
|---|---|---|
| Vectara Hallucination Rate | 9.8% | 9.5% |
| LMArena Expert | 1442 | 1431 |
| GPQA Diamond | 71.2% | — |
| SimpleQA Verified | 13.2% | — |
| MMLU-Pro | 77.7% | — |
| GPQA (HELM) | 60.5% | — |

## Multimodal

- Claude Haiku 4.5: 26.8 (#118)
- GLM-4.6: —

| Benchmark | Claude Haiku 4.5 | GLM-4.6 |
|---|---|---|
| Blueprint-Bench 2 | 0% | — |
| LMArena Document | 1420 | — |

## Multilingual

- Claude Haiku 4.5: 49.9 (#129)
- GLM-4.6: 53.5 (#66)

| Benchmark | Claude Haiku 4.5 | GLM-4.6 |
|---|---|---|
| LMArena Non-English | 1377 | 1426 |
| LMArena Chinese | 1417 | 1499 |
| LMArena French | 1408 | 1459 |
| LMArena German | 1375 | 1447 |
| LMArena Japanese | 1339 | 1393 |
| LMArena Korean | 1347 | 1400 |
| LMArena Russian | 1381 | 1419 |
| LMArena Spanish | 1420 | 1436 |

## Instruction Following

- Claude Haiku 4.5: 71.4 (#149)
- GLM-4.6: 74.3 (#98)

| Benchmark | Claude Haiku 4.5 | GLM-4.6 |
|---|---|---|
| LMArena Instruction Following | 1414 | 1410 |
| IFEval | 80.1% | — |

## Long Context

- Claude Haiku 4.5: 43.6 (#92)
- GLM-4.6: 43.4 (#94)

| Benchmark | Claude Haiku 4.5 | GLM-4.6 |
|---|---|---|
| LMArena Longer Query | 1427 | 1422 |

## Writing & Preference

- Claude Haiku 4.5: 57.9 (#123)
- GLM-4.6: 61.1 (#90)

| Benchmark | Claude Haiku 4.5 | GLM-4.6 |
|---|---|---|
| LMArena Text | 1396 | 1440 |
| LMArena Creative Writing | 1372 | 1411 |
| LMArena Multi-Turn | 1409 | 1427 |
| EQ-Bench Creative Writing | — | 1411 |
| WildBench | 83.9% | — |
| EQ-Bench 4 | 1064 | — |

## FAQ

### Is Claude Haiku 4.5 better than GLM-4.6?

GLM-4.6 is the stronger model overall, scoring 41.4 to 39.5 on the Noometry Index.

### Which is cheaper, Claude Haiku 4.5 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 Haiku 4.5 lists at $1 and $5.

### Is Claude Haiku 4.5 or GLM-4.6 better for coding?

Claude Haiku 4.5 scores higher on coding benchmarks: 44.0 versus 40.1 in the Noometry coding category.

### Which has the bigger context window?

GLM-4.6 does, with 205K tokens against 200K.

### How many benchmarks do Claude Haiku 4.5 and GLM-4.6 share?

27 benchmarks have published results for both models. Claude Haiku 4.5 has 53 scored results on Noometry and GLM-4.6 has 29.