# Command R vs GLM-4.6

> GLM-4.6 is the stronger model overall, scoring 40.9 to 31.0 on the Noometry Index. Command R costs 3.8× less per token, which makes it the better buy when GLM-4.6's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/command-r-vs-glm-4-6
- Last updated: 2026-10-10
- Shared benchmarks: 17

## Summary

- They share 17 benchmarks with published results for both. Command R scores higher in 0 categories and GLM-4.6 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GLM-4.6 leads 61.3 to 38.4.
- Command R is cheaper at $0.15 / $0.60 per million input/output tokens, against $0.60 / $2.20 for GLM-4.6.
- GLM-4.6 accepts more context: 205K tokens versus 128K.

## Snapshot

| | Command R | GLM-4.6 |
|---|---|---|
| Provider | Cohere | Z.ai (Zhipu) |
| Noometry Index | 31.0 | 40.9 |
| Rank | 267 | 132 |
| Context | 128K | 205K |
| Input $/M | $0.15 | $0.60 |
| Output $/M | $0.60 | $2.20 |
| Weights | Open | Open |

## Coding

- Command R: 28.8 (#301)
- GLM-4.6: 39.9 (#137)

| Benchmark | Command R | GLM-4.6 |
|---|---|---|
| LMArena Coding | 1170 | 1449 |
| SWE-bench Verified (bash only) | — | 55.4% |
| LMArena WebDev | — | 1339 |
| SciCode | — | 38.4% |
| BigCodeBench Instruct | 37.1% | — |
| LiveBench Coding | 17.9% | — |
| BigCodeBench Complete | 45.2% | — |
| ALE-Bench | — | 340.82 |

## Agentic & Tool Use

- Command R: —
- GLM-4.6: 32.1 (#60)

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

## Reasoning

- Command R: 13.3 (#329)
- GLM-4.6: 23.1 (#168)

| Benchmark | Command R | GLM-4.6 |
|---|---|---|
| LMArena Hard Prompts | 1164 | 1440 |
| Kagi LLM Benchmark | — | 47.4% |
| CritPt | — | 1.1% |
| LiveBench Reasoning | 21.9% | — |
| DTBench | 46.4% | — |
| LiveBench Data Analysis | 33.3% | — |
| LMCA | 9.2% | — |
| LiveBench | 27.5% | — |

## Math

- Command R: 25.8 (#244)
- GLM-4.6: 36.4 (#115)

| Benchmark | Command R | GLM-4.6 |
|---|---|---|
| LMArena Math | 1155 | 1431 |
| LiveBench Math | 19.4% | — |
| FrontierMath (Feb 2025 set) | — | 3.8% |
| FrontierMath Tier 4 (v1) | — | 2.1% |

## Knowledge

- Command R: 30.5 (#219)
- GLM-4.6: 39.6 (#118)

| Benchmark | Command R | GLM-4.6 |
|---|---|---|
| LMArena Expert | 1138 | 1432 |
| Vectara Hallucination Rate | — | 9.5% |
| MMLU | 65.2% | — |

## Multilingual

- Command R: 35.9 (#240)
- GLM-4.6: 53.6 (#62)

| Benchmark | Command R | GLM-4.6 |
|---|---|---|
| LMArena Non-English | 1174 | 1426 |
| LMArena Chinese | 1182 | 1500 |
| LMArena French | 1161 | 1459 |
| LMArena German | 1176 | 1447 |
| LMArena Japanese | 1143 | 1394 |
| LMArena Korean | 1162 | 1401 |
| LMArena Russian | 1174 | 1418 |
| LMArena Spanish | 1150 | 1436 |

## Instruction Following

- Command R: 58.3 (#256)
- GLM-4.6: 74.5 (#93)

| Benchmark | Command R | GLM-4.6 |
|---|---|---|
| LMArena Instruction Following | 1167 | 1410 |
| LiveBench Instruction Following | 55.6% | — |

## Long Context

- Command R: 36.3 (#226)
- GLM-4.6: 43.4 (#91)

| Benchmark | Command R | GLM-4.6 |
|---|---|---|
| LMArena Longer Query | 1198 | 1423 |

## Writing & Preference

- Command R: 38.4 (#248)
- GLM-4.6: 61.3 (#86)

| Benchmark | Command R | GLM-4.6 |
|---|---|---|
| LMArena Text | 1187 | 1440 |
| LMArena Creative Writing | 1170 | 1411 |
| LMArena Multi-Turn | 1163 | 1427 |
| EQ-Bench Creative Writing | — | 1411 |
| LiveBench Language | 16.7% | — |

## FAQ

### Is Command R better than GLM-4.6?

GLM-4.6 is the stronger model overall, scoring 40.9 to 31.0 on the Noometry Index. Command R costs 3.8× less per token, which makes it the better buy when GLM-4.6's lead doesn't matter for your workload.

### Which is cheaper, Command R or GLM-4.6?

Command R is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; GLM-4.6 lists at $0.60 and $2.20.

### Is Command R or GLM-4.6 better for coding?

GLM-4.6 scores higher on coding benchmarks: 39.9 versus 28.8 in the Noometry coding category.

### Which has the bigger context window?

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

### How many benchmarks do Command R and GLM-4.6 share?

17 benchmarks have published results for both models. Command R has 29 scored results on Noometry and GLM-4.6 has 29.