# Command R+ vs GPT-5.6 Luna

> GPT-5.6 Luna is the stronger model overall, scoring 54.6 to 32.4 on the Noometry Index.

- Canonical page: https://noometry.com/compare/command-r-plus-vs-gpt-5-6-luna
- Last updated: 2026-10-11
- Shared benchmarks: 21

## Summary

- They share 21 benchmarks with published results for both. Command R+ scores higher in 0 categories 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 77.7 to 28.9.
- The biggest single-benchmark swing is LMCA: 5% for Command R+ 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 R+.
- GPT-5.6 Luna accepts more context: 1.05M tokens versus 128K.
- Command R+ has downloadable open weights; the other is API-only.

## Snapshot

| | Command R+ | GPT-5.6 Luna |
|---|---|---|
| Provider | Cohere | OpenAI |
| Noometry Index | 32.4 | 54.6 |
| Rank | 257 | 30 |
| Context | 128K | 1.05M |
| Input $/M | $2.50 | $0.20 |
| Output $/M | $10 | $1.20 |
| Weights | Open | Proprietary |

## Coding

- Command R+: 29.1 (#309)
- GPT-5.6 Luna: 54.5 (#28)

| Benchmark | Command R+ | GPT-5.6 Luna |
|---|---|---|
| LMArena Coding | 1187 | 1466 |
| DeepSWE | — | 67.2% |
| FrontierCode | — | 39.8% |
| CursorBench | — | 35.9% |
| LMArena WebDev | — | 1519 |
| SciCode | — | 53.6% |
| WeirdML | — | 60.9% |
| BigCodeBench Instruct | 33.8% | — |
| LiveBench Coding | 19.1% | — |
| BigCodeBench Complete | 41.9% | — |
| ALE-Bench | — | 1,667 |
| HumanEval+ | 56.7% | — |
| MBPP+ | 63.5% | — |

## Agentic & Tool Use

- Command R+: —
- GPT-5.6 Luna: 34.4 (#45)

| Benchmark | Command R+ | GPT-5.6 Luna |
|---|---|---|
| APEX-Agents | — | 43% |
| BALROG | — | 45.6% |
| GDP.pdf | — | 22.7% |
| Vending-Bench 2 | — | 4,095 |

## Reasoning

- Command R+: 9.2 (#344)
- GPT-5.6 Luna: 47.6 (#43)

| Benchmark | Command R+ | GPT-5.6 Luna |
|---|---|---|
| SimpleBench | 17.4% | 46.8% |
| LMArena Hard Prompts | 1186 | 1451 |
| DTBench | 54.9% | 89.1% |
| LMCA | 5% | 48.5% |
| Epoch Capabilities Index | 119.34 | 156.39 |
| ARC-AGI-2 | — | 59.5% |
| Kagi LLM Benchmark | — | 49.1% |
| NYT Connections (extended) | — | 69.4% |
| ARC-AGI-1 | — | 88% |
| CritPt | — | 20.6% |
| Chess Puzzles | — | 40% |
| LiveBench Reasoning | 24.8% | — |
| Mystery Game Puzzles | — | 21% |
| LiveBench Data Analysis | 38.1% | — |
| Surface Evolver Bench | — | 61.9% |
| LiveBench | 31.8% | — |

## Math

- Command R+: 28.9 (#242)
- GPT-5.6 Luna: 77.7 (#14)

| Benchmark | Command R+ | GPT-5.6 Luna |
|---|---|---|
| LMArena Math | 1188 | 1458 |
| FrontierMath (Tiers 1-3) | — | 82.1% |
| FrontierMath Tier 4 | — | 61% |
| OTIS Mock AIME 2024-2025 | — | 98.3% |
| ProofBench | — | 60% |
| LiveBench Math | 21.3% | — |

## Knowledge

- Command R+: 36.4 (#169)
- GPT-5.6 Luna: 58.5 (#34)

| Benchmark | Command R+ | GPT-5.6 Luna |
|---|---|---|
| LMArena Expert | 1174 | 1478 |
| GPQA Diamond | — | 91.6% |
| SimpleQA Verified | — | 41% |
| Vectara Hallucination Rate | 6.9% | — |
| MMLU | 69.4% | — |

## Multimodal

- Command R+: —
- GPT-5.6 Luna: 42.7 (#28)

| Benchmark | Command R+ | GPT-5.6 Luna |
|---|---|---|
| LMArena Vision | — | 1258 |
| Blueprint-Bench 2 | — | 22.6% |
| Furniture Assembly | — | 42.5% |
| LMArena Document | — | 1457 |

## Multilingual

- Command R+: 38.6 (#227)
- GPT-5.6 Luna: 52.8 (#78)

| Benchmark | Command R+ | GPT-5.6 Luna |
|---|---|---|
| LMArena Non-English | 1216 | 1417 |
| LMArena Chinese | 1226 | 1470 |
| LMArena French | 1209 | 1456 |
| LMArena German | 1216 | 1454 |
| LMArena Japanese | 1166 | 1411 |
| LMArena Korean | 1138 | 1415 |
| LMArena Russian | 1227 | 1428 |
| LMArena Spanish | 1189 | 1448 |

## Instruction Following

- Command R+: 60.0 (#254)
- GPT-5.6 Luna: 75.6 (#57)

| Benchmark | Command R+ | GPT-5.6 Luna |
|---|---|---|
| LMArena Instruction Following | 1197 | 1437 |
| LiveBench Instruction Following | 57.6% | — |

## Long Context

- Command R+: 37.3 (#219)
- GPT-5.6 Luna: 43.9 (#82)

| Benchmark | Command R+ | GPT-5.6 Luna |
|---|---|---|
| LMArena Longer Query | 1230 | 1436 |

## Writing & Preference

- Command R+: 43.5 (#228)
- GPT-5.6 Luna: 68.0 (#29)

| Benchmark | Command R+ | GPT-5.6 Luna |
|---|---|---|
| LMArena Text | 1229 | 1431 |
| LMArena Creative Writing | 1235 | 1396 |
| LMArena Multi-Turn | 1213 | 1434 |
| EQ-Bench Creative Writing | — | 1829 |
| EQ-Bench 4 | — | 1156 |
| LiveBench Language | 29.7% | — |

## FAQ

### Is Command R+ better than GPT-5.6 Luna?

GPT-5.6 Luna is the stronger model overall, scoring 54.6 to 32.4 on the Noometry Index.

### Which is cheaper, Command R+ 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 R+ lists at $2.50 and $10.

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

GPT-5.6 Luna scores higher on coding benchmarks: 54.5 versus 29.1 in the Noometry coding category.

### Which has the bigger context window?

GPT-5.6 Luna does, with 1.05M tokens against 128K.

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

21 benchmarks have published results for both models. Command R+ has 34 scored results on Noometry and GPT-5.6 Luna has 52.