# GLM-4.6 vs Sonar

> GLM-4.6 is the stronger model overall, scoring 40.9 to 37.8 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-4-6-vs-sonar
- Last updated: 2026-10-10
- Shared benchmarks: 0

## Summary

- The widest gap is in writing & preference, where GLM-4.6 leads 61.3 to 52.6.
- Both cost about the same: $0.60 input and $2.20 output per million tokens.
- GLM-4.6 accepts more context: 205K tokens versus 128K.
- GLM-4.6 has downloadable open weights; the other is API-only.

## Snapshot

| | GLM-4.6 | Sonar |
|---|---|---|
| Provider | Z.ai (Zhipu) | Perplexity |
| Noometry Index | 40.9 | 37.8 |
| Rank | 132 | 184 |
| Context | 205K | 128K |
| Input $/M | $0.60 | $1 |
| Output $/M | $2.20 | $1 |
| Weights | Open | Proprietary |

## Coding

- GLM-4.6: 39.9 (#137)
- Sonar: 35.1 (#217)

| Benchmark | GLM-4.6 | Sonar |
|---|---|---|
| SWE-bench Verified (bash only) | 55.4% | — |
| LMArena WebDev | 1339 | — |
| SciCode | 38.4% | — |
| LiveBench Coding | — | 35.1% |
| LMArena Coding | 1449 | — |
| ALE-Bench | 340.82 | — |

## Agentic & Tool Use

- GLM-4.6: 32.1 (#60)
- Sonar: —

| Benchmark | GLM-4.6 | Sonar |
|---|---|---|
| Terminal-Bench | 24.5% | — |
| Berkeley Function Calling Leaderboard | 72.4% | — |

## Reasoning

- GLM-4.6: 23.1 (#168)
- Sonar: 20.3 (#221)

| Benchmark | GLM-4.6 | Sonar |
|---|---|---|
| Kagi LLM Benchmark | 47.4% | — |
| CritPt | 1.1% | — |
| LiveBench Reasoning | — | 46.3% |
| LMArena Hard Prompts | 1440 | — |
| LiveBench Data Analysis | — | 37.9% |
| LiveBench | — | 46.9% |

## Math

- GLM-4.6: 36.4 (#115)
- Sonar: 31.3 (#197)

| Benchmark | GLM-4.6 | Sonar |
|---|---|---|
| LiveBench Math | — | 41.6% |
| LMArena Math | 1431 | — |
| FrontierMath (Feb 2025 set) | 3.8% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |

## Knowledge

- GLM-4.6: 39.6 (#118)
- Sonar: —

| Benchmark | GLM-4.6 | Sonar |
|---|---|---|
| Vectara Hallucination Rate | 9.5% | — |
| LMArena Expert | 1432 | — |

## Multilingual

- GLM-4.6: 53.6 (#62)
- Sonar: —

| Benchmark | GLM-4.6 | Sonar |
|---|---|---|
| LMArena Non-English | 1426 | — |
| LMArena Chinese | 1500 | — |
| LMArena French | 1459 | — |
| LMArena German | 1447 | — |
| LMArena Japanese | 1394 | — |
| LMArena Korean | 1401 | — |
| LMArena Russian | 1418 | — |
| LMArena Spanish | 1436 | — |

## Instruction Following

- GLM-4.6: 74.5 (#93)
- Sonar: 71.5 (#146)

| Benchmark | GLM-4.6 | Sonar |
|---|---|---|
| LiveBench Instruction Following | — | 76.2% |
| LMArena Instruction Following | 1410 | — |

## Long Context

- GLM-4.6: 43.4 (#91)
- Sonar: —

| Benchmark | GLM-4.6 | Sonar |
|---|---|---|
| LMArena Longer Query | 1423 | — |

## Writing & Preference

- GLM-4.6: 61.3 (#86)
- Sonar: 52.6 (#166)

| Benchmark | GLM-4.6 | Sonar |
|---|---|---|
| LMArena Text | 1440 | — |
| LMArena Creative Writing | 1411 | — |
| EQ-Bench Creative Writing | 1411 | — |
| LMArena Multi-Turn | 1427 | — |
| LiveBench Language | — | 44.1% |

## FAQ

### Is GLM-4.6 better than Sonar?

GLM-4.6 is the stronger model overall, scoring 40.9 to 37.8 on the Noometry Index.

### Which is cheaper, GLM-4.6 or Sonar?

Sonar is cheaper. It lists at $1 per million input tokens and $1 per million output tokens; GLM-4.6 lists at $0.60 and $2.20.

### Is GLM-4.6 or Sonar better for coding?

GLM-4.6 scores higher on coding benchmarks: 39.9 versus 35.1 in the Noometry coding category.

### Which has the bigger context window?

GLM-4.6 does, with 205K tokens against 128K.

### How many benchmarks do GLM-4.6 and Sonar share?

0 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and Sonar has 7.