# Command A vs GLM-5

> GLM-5 is the stronger model overall, scoring 45.9 to 35.9 on the Noometry Index.

- Canonical page: https://noometry.com/compare/command-a-vs-glm-5
- Last updated: 2026-10-10
- Shared benchmarks: 20

## Summary

- They share 20 benchmarks with published results for both. Command A scores higher in 1 category and GLM-5 in 8 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in coding, where GLM-5 leads 49.0 to 26.8.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 28.8% for Command A and 75% for GLM-5.
- GLM-5 is cheaper at $1 / $3.20 per million input/output tokens, against $2.50 / $10 for Command A.
- Command A accepts more context: 256K tokens versus 205K.

## Snapshot

| | Command A | GLM-5 |
|---|---|---|
| Provider | Cohere | Z.ai (Zhipu) |
| Noometry Index | 35.9 | 45.9 |
| Rank | 212 | 59 |
| Context | 256K | 205K |
| Input $/M | $2.50 | $1 |
| Output $/M | $10 | $3.20 |
| Weights | Open | Open |

## Coding

- Command A: 26.8 (#317)
- GLM-5: 49.0 (#47)

| Benchmark | Command A | GLM-5 |
|---|---|---|
| LMArena Coding | 1331 | 1461 |
| SWE-bench Verified | — | 72.1% |
| SWE-bench Verified (bash only) | — | 72.8% |
| Aider Polyglot | 12% | — |
| LMArena WebDev | — | 1434 |
| SWE-bench Multilingual | — | 69.7% |
| WeirdML | — | 48.2% |
| ALE-Bench | — | 765.62 |

## Agentic & Tool Use

- Command A: 35.7 (#36)
- GLM-5: 30.9 (#65)

| Benchmark | Command A | GLM-5 |
|---|---|---|
| Terminal-Bench | — | 52.4% |
| Berkeley Function Calling Leaderboard | 57.1% | — |
| τ²-bench Airline | — | 82.5% |
| τ²-bench Banking | — | 9.8% |
| τ²-bench Retail | — | 73.7% |
| τ²-bench Telecom | — | 86.8% |
| Vending-Bench 2 | — | 4,432 |

## Reasoning

- Command A: 17.7 (#276)
- GLM-5: 27.6 (#100)

| Benchmark | Command A | GLM-5 |
|---|---|---|
| Kagi LLM Benchmark | 28.8% | 75% |
| LMArena Hard Prompts | 1326 | 1451 |
| ARC-AGI-2 | — | 4.9% |
| SimpleBench | — | 53.2% |
| NYT Connections (extended) | — | 74.8% |
| ARC-AGI-1 | — | 44.7% |
| Chess Puzzles | — | 10% |
| DTBench | 61.3% | — |
| LMCA | 10.3% | — |
| Epoch Capabilities Index | — | 145.84 |
| ForecastBench | — | 61 |

## Math

- Command A: 33.5 (#172)
- GLM-5: 44.8 (#66)

| Benchmark | Command A | GLM-5 |
|---|---|---|
| LMArena Math | 1300 | 1440 |
| MathArena Final-Answer Competitions | — | 65.7% |
| OTIS Mock AIME 2024-2025 | — | 80% |
| FrontierMath (Feb 2025 set) | — | 16.4% |
| FrontierMath Tier 4 (v1) | — | 2.1% |

## Knowledge

- Command A: 36.5 (#157)
- GLM-5: 52.2 (#59)

| Benchmark | Command A | GLM-5 |
|---|---|---|
| Vectara Hallucination Rate | 9.3% | 10.1% |
| LMArena Expert | 1295 | 1454 |
| GPQA Diamond | — | 87.8% |

## Multilingual

- Command A: 45.5 (#166)
- GLM-5: 53.9 (#57)

| Benchmark | Command A | GLM-5 |
|---|---|---|
| LMArena Non-English | 1313 | 1430 |
| LMArena Chinese | 1327 | 1511 |
| LMArena French | 1352 | 1455 |
| LMArena German | 1341 | 1445 |
| LMArena Japanese | 1283 | 1416 |
| LMArena Korean | 1285 | 1421 |
| LMArena Russian | 1314 | 1436 |
| LMArena Spanish | 1346 | 1452 |

## Instruction Following

- Command A: 69.3 (#172)
- GLM-5: 75.4 (#64)

| Benchmark | Command A | GLM-5 |
|---|---|---|
| LMArena Instruction Following | 1309 | 1427 |

## Long Context

- Command A: 40.6 (#147)
- GLM-5: 44.6 (#58)

| Benchmark | Command A | GLM-5 |
|---|---|---|
| LMArena Longer Query | 1334 | 1446 |
| CL-bench | — | 18.7% |

## Writing & Preference

- Command A: 47.8 (#204)
- GLM-5: 66.2 (#38)

| Benchmark | Command A | GLM-5 |
|---|---|---|
| LMArena Text | 1331 | 1446 |
| LMArena Creative Writing | 1319 | 1438 |
| EQ-Bench Creative Writing | 1145 | 1601 |
| LMArena Multi-Turn | 1338 | 1456 |

## FAQ

### Is Command A better than GLM-5?

GLM-5 is the stronger model overall, scoring 45.9 to 35.9 on the Noometry Index.

### Which is cheaper, Command A or GLM-5?

GLM-5 is cheaper. It lists at $1 per million input tokens and $3.20 per million output tokens; Command A lists at $2.50 and $10.

### Is Command A or GLM-5 better for coding?

GLM-5 scores higher on coding benchmarks: 49.0 versus 26.8 in the Noometry coding category.

### Which has the bigger context window?

Command A does, with 256K tokens against 205K.

### How many benchmarks do Command A and GLM-5 share?

20 benchmarks have published results for both models. Command A has 24 scored results on Noometry and GLM-5 has 45.