# Command A vs GPT-5.6 Luna

> GPT-5.6 Luna is the stronger model overall, scoring 54.7 to 35.9 on the Noometry Index.

- Canonical page: https://noometry.com/compare/command-a-vs-gpt-5-6-luna
- Last updated: 2026-10-10
- Shared benchmarks: 21

## Summary

- They share 21 benchmarks with published results for both. Command A scores higher in 1 category and GPT-5.6 Luna in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.6 Luna leads 77.5 to 33.5.
- The biggest single-benchmark swing is LMCA: 10.3% for Command A and 48.5% for GPT-5.6 Luna.
- GPT-5.6 Luna is cheaper at $0.20 / $1.20 per million input/output tokens, against $2.50 / $10 for Command A.
- GPT-5.6 Luna accepts more context: 1.05M tokens versus 256K.
- Command A has downloadable open weights; the other is API-only.

## Snapshot

| | Command A | GPT-5.6 Luna |
|---|---|---|
| Provider | Cohere | OpenAI |
| Noometry Index | 35.9 | 54.7 |
| Rank | 212 | 24 |
| Context | 256K | 1.05M |
| Input $/M | $2.50 | $0.20 |
| Output $/M | $10 | $1.20 |
| Weights | Open | Proprietary |

## Coding

- Command A: 26.8 (#317)
- GPT-5.6 Luna: 53.9 (#25)

| Benchmark | Command A | GPT-5.6 Luna |
|---|---|---|
| LMArena Coding | 1331 | 1466 |
| DeepSWE | — | 67.2% |
| FrontierCode | — | 39.8% |
| Aider Polyglot | 12% | — |
| CursorBench | — | 35.9% |
| LMArena WebDev | — | 1517 |
| SciCode | — | 53.6% |
| WeirdML | — | 60.9% |
| ALE-Bench | — | 1,667 |

## Agentic & Tool Use

- Command A: 35.7 (#36)
- GPT-5.6 Luna: 35.3 (#37)

| Benchmark | Command A | GPT-5.6 Luna |
|---|---|---|
| Berkeley Function Calling Leaderboard | 57.1% | — |
| BALROG | — | 45.6% |
| GDP.pdf | — | 22.7% |
| Vending-Bench 2 | — | 4,095 |

## Reasoning

- Command A: 17.7 (#276)
- GPT-5.6 Luna: 47.5 (#38)

| Benchmark | Command A | GPT-5.6 Luna |
|---|---|---|
| Kagi LLM Benchmark | 28.8% | 49.1% |
| LMArena Hard Prompts | 1326 | 1452 |
| DTBench | 61.3% | 89.1% |
| LMCA | 10.3% | 48.5% |
| ARC-AGI-2 | — | 59.5% |
| SimpleBench | — | 46.8% |
| NYT Connections (extended) | — | 69.4% |
| ARC-AGI-1 | — | 88% |
| CritPt | — | 20.6% |
| Chess Puzzles | — | 40% |
| Mystery Game Puzzles | — | 21% |
| Surface Evolver Bench | — | 61.9% |
| Epoch Capabilities Index | — | 156.32 |

## Math

- Command A: 33.5 (#172)
- GPT-5.6 Luna: 77.5 (#12)

| Benchmark | Command A | GPT-5.6 Luna |
|---|---|---|
| LMArena Math | 1300 | 1455 |
| FrontierMath (Tiers 1-3) | — | 82.1% |
| FrontierMath Tier 4 | — | 61% |
| OTIS Mock AIME 2024-2025 | — | 98.3% |
| ProofBench | — | 60% |

## Knowledge

- Command A: 36.5 (#157)
- GPT-5.6 Luna: 58.6 (#31)

| Benchmark | Command A | GPT-5.6 Luna |
|---|---|---|
| LMArena Expert | 1295 | 1479 |
| GPQA Diamond | — | 91.6% |
| SimpleQA Verified | — | 41% |
| Vectara Hallucination Rate | 9.3% | — |

## Multimodal

- Command A: —
- GPT-5.6 Luna: 43.0 (#22)

| Benchmark | Command A | GPT-5.6 Luna |
|---|---|---|
| LMArena Vision | — | 1259 |
| Blueprint-Bench 2 | — | 22.6% |
| Furniture Assembly | — | 42.5% |
| LMArena Document | — | 1457 |

## Multilingual

- Command A: 45.5 (#166)
- GPT-5.6 Luna: 53.0 (#73)

| Benchmark | Command A | GPT-5.6 Luna |
|---|---|---|
| LMArena Non-English | 1313 | 1418 |
| LMArena Chinese | 1327 | 1469 |
| LMArena French | 1352 | 1457 |
| LMArena German | 1341 | 1459 |
| LMArena Japanese | 1283 | 1416 |
| LMArena Korean | 1285 | 1414 |
| LMArena Russian | 1314 | 1428 |
| LMArena Spanish | 1346 | 1445 |

## Instruction Following

- Command A: 69.3 (#172)
- GPT-5.6 Luna: 76.0 (#48)

| Benchmark | Command A | GPT-5.6 Luna |
|---|---|---|
| LMArena Instruction Following | 1309 | 1440 |

## Long Context

- Command A: 40.6 (#147)
- GPT-5.6 Luna: 43.9 (#78)

| Benchmark | Command A | GPT-5.6 Luna |
|---|---|---|
| LMArena Longer Query | 1334 | 1437 |

## Writing & Preference

- Command A: 47.8 (#204)
- GPT-5.6 Luna: 68.3 (#27)

| Benchmark | Command A | GPT-5.6 Luna |
|---|---|---|
| LMArena Text | 1331 | 1432 |
| LMArena Creative Writing | 1319 | 1397 |
| EQ-Bench Creative Writing | 1145 | 1829 |
| LMArena Multi-Turn | 1338 | 1433 |
| EQ-Bench 4 | — | 1156 |

## FAQ

### Is Command A better than GPT-5.6 Luna?

GPT-5.6 Luna is the stronger model overall, scoring 54.7 to 35.9 on the Noometry Index.

### Which is cheaper, Command A or GPT-5.6 Luna?

GPT-5.6 Luna is cheaper. It lists at $0.20 per million input tokens and $1.20 per million output tokens; Command A lists at $2.50 and $10.

### Is Command A or GPT-5.6 Luna better for coding?

GPT-5.6 Luna scores higher on coding benchmarks: 53.9 versus 26.8 in the Noometry coding category.

### Which has the bigger context window?

GPT-5.6 Luna does, with 1.05M tokens against 256K.

### How many benchmarks do Command A and GPT-5.6 Luna share?

21 benchmarks have published results for both models. Command A has 24 scored results on Noometry and GPT-5.6 Luna has 51.