# Command A vs GPT-5 Nano

> Command A is the stronger model overall, scoring 35.9 to 33.4 on the Noometry Index. GPT-5 Nano costs 32× less per token, which makes it the better buy when Command A's lead doesn't matter for your workload.

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

## Summary

- They share 21 benchmarks with published results for both. Command A scores higher in 7 categories and GPT-5 Nano in 2 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in agentic & tool use, where Command A leads 35.7 to 25.6.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 28.8% for Command A and 62.2% for GPT-5 Nano.
- GPT-5 Nano is cheaper at $0.05 / $0.40 per million input/output tokens, against $2.50 / $10 for Command A.
- GPT-5 Nano accepts more context: 400K tokens versus 256K.
- Command A has downloadable open weights; the other is API-only.

## Snapshot

| | Command A | GPT-5 Nano |
|---|---|---|
| Provider | Cohere | OpenAI |
| Noometry Index | 35.9 | 33.4 |
| Rank | 212 | 234 |
| Context | 256K | 400K |
| Input $/M | $2.50 | $0.05 |
| Output $/M | $10 | $0.40 |
| Weights | Open | Proprietary |

## Coding

- Command A: 26.8 (#317)
- GPT-5 Nano: 33.3 (#248)

| Benchmark | Command A | GPT-5 Nano |
|---|---|---|
| LMArena Coding | 1331 | 1351 |
| SWE-bench Verified (bash only) | — | 34.8% |
| Aider Polyglot | 12% | — |
| WeirdML | — | 38.1% |
| ALE-Bench | — | 718.67 |

## Agentic & Tool Use

- Command A: 35.7 (#36)
- GPT-5 Nano: 25.6 (#99)

| Benchmark | Command A | GPT-5 Nano |
|---|---|---|
| Berkeley Function Calling Leaderboard | 57.1% | 51.5% |
| Terminal-Bench | — | 21.8% |

## Reasoning

- Command A: 17.7 (#276)
- GPT-5 Nano: 16.4 (#291)

| Benchmark | Command A | GPT-5 Nano |
|---|---|---|
| Kagi LLM Benchmark | 28.8% | 62.2% |
| LMArena Hard Prompts | 1326 | 1329 |
| DTBench | 61.3% | 62.7% |
| LMCA | 10.3% | 7.9% |
| ARC-AGI-2 | — | 2.6% |
| ARC-AGI-1 | — | 20.7% |
| Chess Puzzles | — | 27% |
| Mystery Game Puzzles | — | 9% |
| Epoch Capabilities Index | — | 139.39 |
| ForecastBench | — | 59.1 |

## Math

- Command A: 33.5 (#172)
- GPT-5 Nano: 29.1 (#221)

| Benchmark | Command A | GPT-5 Nano |
|---|---|---|
| LMArena Math | 1300 | 1318 |
| FrontierMath (Tiers 1-3) | — | 20% |
| FrontierMath Tier 4 | — | 2.4% |
| OTIS Mock AIME 2024-2025 | — | 81.1% |
| ProofBench | — | 12% |
| Omni-MATH | — | 54.6% |
| MATH Level 5 | — | 95.2% |
| FrontierMath (Feb 2025 set) | — | 8.3% |
| FrontierMath Tier 4 (v1) | — | 2.1% |

## Knowledge

- Command A: 36.5 (#157)
- GPT-5 Nano: 35.8 (#166)

| Benchmark | Command A | GPT-5 Nano |
|---|---|---|
| Vectara Hallucination Rate | 9.3% | 10.5% |
| LMArena Expert | 1295 | 1321 |
| GPQA Diamond | — | 69.4% |
| SimpleQA Verified | — | 11.7% |
| MMLU-Pro | — | 77.8% |
| GPQA (HELM) | — | 67.9% |

## Multimodal

- Command A: —
- GPT-5 Nano: 30.7 (#102)

| Benchmark | Command A | GPT-5 Nano |
|---|---|---|
| LMArena Vision | — | 1159 |
| VPCT | — | 37.2% |

## Multilingual

- Command A: 45.5 (#166)
- GPT-5 Nano: 45.5 (#167)

| Benchmark | Command A | GPT-5 Nano |
|---|---|---|
| LMArena Non-English | 1313 | 1313 |
| LMArena Chinese | 1327 | 1355 |
| LMArena German | 1341 | 1329 |
| LMArena Korean | 1285 | 1269 |
| LMArena Russian | 1314 | 1296 |
| LMArena Spanish | 1346 | 1360 |
| LMArena French | 1352 | — |
| LMArena Japanese | 1283 | — |

## Instruction Following

- Command A: 69.3 (#172)
- GPT-5 Nano: 75.2 (#72)

| Benchmark | Command A | GPT-5 Nano |
|---|---|---|
| LMArena Instruction Following | 1309 | 1306 |
| IFEval | — | 93.2% |

## Long Context

- Command A: 40.6 (#147)
- GPT-5 Nano: 31.3 (#275)

| Benchmark | Command A | GPT-5 Nano |
|---|---|---|
| LMArena Longer Query | 1334 | 1313 |
| Fiction.LiveBench | — | 44.4% |

## Writing & Preference

- Command A: 47.8 (#204)
- GPT-5 Nano: 39.4 (#244)

| Benchmark | Command A | GPT-5 Nano |
|---|---|---|
| LMArena Text | 1331 | 1320 |
| LMArena Creative Writing | 1319 | 1250 |
| EQ-Bench Creative Writing | 1145 | 705 |
| LMArena Multi-Turn | 1338 | 1311 |
| WildBench | — | 80.6% |

## FAQ

### Is Command A better than GPT-5 Nano?

Command A is the stronger model overall, scoring 35.9 to 33.4 on the Noometry Index. GPT-5 Nano costs 32× less per token, which makes it the better buy when Command A's lead doesn't matter for your workload.

### Which is cheaper, Command A or GPT-5 Nano?

GPT-5 Nano is cheaper. It lists at $0.05 per million input tokens and $0.40 per million output tokens; Command A lists at $2.50 and $10.

### Is Command A or GPT-5 Nano better for coding?

GPT-5 Nano scores higher on coding benchmarks: 33.3 versus 26.8 in the Noometry coding category.

### Which has the bigger context window?

GPT-5 Nano does, with 400K tokens against 256K.

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

21 benchmarks have published results for both models. Command A has 24 scored results on Noometry and GPT-5 Nano has 48.