# Command R vs Gemini 2.5 Pro

> Gemini 2.5 Pro is the stronger model overall, scoring 45.0 to 31.4 on the Noometry Index. Command R costs 13× less per token, which makes it the better buy when Gemini 2.5 Pro's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/command-r-vs-gemini-2-5-pro
- Last updated: 2026-10-11
- Shared benchmarks: 26

## Summary

- They share 26 benchmarks with published results for both. Command R scores higher in 0 categories and Gemini 2.5 Pro in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Gemini 2.5 Pro leads 63.7 to 38.2.
- The biggest single-benchmark swing is LiveBench Math: 19.4% for Command R and 90.2% for Gemini 2.5 Pro.
- Command R is cheaper at $0.15 / $0.60 per million input/output tokens, against $1.25 / $10 for Gemini 2.5 Pro.
- Gemini 2.5 Pro accepts more context: 1.05M tokens versus 128K.
- Command R has downloadable open weights; the other is API-only.

## Snapshot

| | Command R | Gemini 2.5 Pro |
|---|---|---|
| Provider | Cohere | Google |
| Noometry Index | 31.4 | 45.0 |
| Rank | 272 | 75 |
| Context | 128K | 1.05M |
| Input $/M | $0.15 | $1.25 |
| Output $/M | $0.60 | $10 |
| Weights | Open | Proprietary |

## Coding

- Command R: 29.3 (#306)
- Gemini 2.5 Pro: 42.4 (#101)

| Benchmark | Command R | Gemini 2.5 Pro |
|---|---|---|
| LiveBench Coding | 17.9% | 85.9% |
| LMArena Coding | 1169 | 1452 |
| SWE-bench Verified | — | 57.6% |
| SWE-bench Verified (bash only) | — | 53.6% |
| Aider Polyglot | — | 83.1% |
| LMArena WebDev | — | 1227 |
| SciCode | — | 42.8% |
| GSO | — | 3.9% |
| WeirdML | — | 54% |
| BigCodeBench Instruct | 37.1% | — |
| BigCodeBench Complete | 45.2% | — |
| CadEval | — | 64% |
| ALE-Bench | — | 785.52 |
| AlgoTune | — | 1.51 |

## Agentic & Tool Use

- Command R: —
- Gemini 2.5 Pro: 29.2 (#88)

| Benchmark | Command R | Gemini 2.5 Pro |
|---|---|---|
| Terminal-Bench | — | 32.6% |
| GDPval | — | 23.3% |
| Remote Labor Index | — | 0.8% |
| TheAgentCompany | — | 30.3% |
| τ²-bench Banking | — | 13.7% |
| DeepResearch Bench | — | 42.8% |
| BALROG | — | 43.3% |
| LMArena Search | — | 1142 |
| METR Time Horizons | — | 55.4% |
| Vending-Bench 2 | — | 573.64 |

## Reasoning

- Command R: 13.8 (#331)
- Gemini 2.5 Pro: 28.8 (#99)

| Benchmark | Command R | Gemini 2.5 Pro |
|---|---|---|
| LiveBench Reasoning | 21.9% | 89.8% |
| LMArena Hard Prompts | 1164 | 1455 |
| DTBench | 46.4% | 82.4% |
| LiveBench Data Analysis | 33.3% | 79.9% |
| LMCA | 9.2% | 34.8% |
| LiveBench | 27.5% | 82.3% |
| ARC-AGI-2 | — | 4.9% |
| SimpleBench | — | 62.4% |
| Kagi LLM Benchmark | — | 70.3% |
| ARC-AGI-1 | — | 41% |
| CritPt | — | 2% |
| Chess Puzzles | — | 20% |
| EnigmaEval | — | 5.6% |
| Epoch Capabilities Index | — | 145.32 |
| ForecastBench | — | 61.3 |

## Math

- Command R: 28.0 (#246)
- Gemini 2.5 Pro: 32.5 (#213)

| Benchmark | Command R | Gemini 2.5 Pro |
|---|---|---|
| LiveBench Math | 19.4% | 90.2% |
| LMArena Math | 1155 | 1450 |
| FrontierMath (Tiers 1-3) | — | 24.6% |
| FrontierMath Tier 4 | — | 0% |
| OTIS Mock AIME 2024-2025 | — | 84.7% |
| Omni-MATH | — | 41.6% |
| MATH Level 5 | — | 95.9% |
| FrontierMath (Feb 2025 set) | — | 14.1% |
| FrontierMath Tier 4 (v1) | — | 4.2% |

## Knowledge

- Command R: 31.0 (#221)
- Gemini 2.5 Pro: 56.0 (#46)

| Benchmark | Command R | Gemini 2.5 Pro |
|---|---|---|
| LMArena Expert | 1138 | 1452 |
| GPQA Diamond | — | 85.3% |
| Humanity's Last Exam | — | 21.6% |
| MMLU-Pro | — | 86.3% |
| Confabulations | — | 10.6% |
| Vectara Hallucination Rate | — | 7% |
| GPQA (HELM) | — | 74.9% |
| MMLU | 65.2% | — |

## Multimodal

- Command R: —
- Gemini 2.5 Pro: 45.2 (#18)

| Benchmark | Command R | Gemini 2.5 Pro |
|---|---|---|
| LMArena Vision | — | 1263 |
| GeoBench | — | 86% |
| VPCT | — | 48% |
| LMArena Document | — | 1421 |
| SpatialViz-Bench | — | 44.7% |

## Multilingual

- Command R: 35.7 (#245)
- Gemini 2.5 Pro: 55.3 (#31)

| Benchmark | Command R | Gemini 2.5 Pro |
|---|---|---|
| LMArena Non-English | 1174 | 1451 |
| LMArena Chinese | 1182 | 1507 |
| LMArena French | 1162 | 1472 |
| LMArena German | 1176 | 1487 |
| LMArena Japanese | 1143 | 1461 |
| LMArena Korean | 1163 | 1434 |
| LMArena Russian | 1174 | 1461 |
| LMArena Spanish | 1151 | 1473 |

## Instruction Following

- Command R: 58.1 (#261)
- Gemini 2.5 Pro: 75.0 (#75)

| Benchmark | Command R | Gemini 2.5 Pro |
|---|---|---|
| LiveBench Instruction Following | 55.6% | 80.6% |
| LMArena Instruction Following | 1167 | 1437 |
| IFEval | — | 84% |

## Long Context

- Command R: 36.3 (#231)
- Gemini 2.5 Pro: 59.8 (#5)

| Benchmark | Command R | Gemini 2.5 Pro |
|---|---|---|
| LMArena Longer Query | 1198 | 1449 |
| Fiction.LiveBench | — | 91.7% |

## Writing & Preference

- Command R: 38.2 (#254)
- Gemini 2.5 Pro: 63.7 (#62)

| Benchmark | Command R | Gemini 2.5 Pro |
|---|---|---|
| LMArena Text | 1187 | 1458 |
| LMArena Creative Writing | 1170 | 1454 |
| LMArena Multi-Turn | 1163 | 1453 |
| LiveBench Language | 16.7% | 67.8% |
| Short-Story Creative Writing | — | 83.8% |
| EQ-Bench Creative Writing | — | 1421 |
| WildBench | — | 85.7% |

## FAQ

### Is Command R better than Gemini 2.5 Pro?

Gemini 2.5 Pro is the stronger model overall, scoring 45.0 to 31.4 on the Noometry Index. Command R costs 13× less per token, which makes it the better buy when Gemini 2.5 Pro's lead doesn't matter for your workload.

### Which is cheaper, Command R or Gemini 2.5 Pro?

Command R is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; Gemini 2.5 Pro lists at $1.25 and $10.

### Is Command R or Gemini 2.5 Pro better for coding?

Gemini 2.5 Pro scores higher on coding benchmarks: 42.4 versus 29.3 in the Noometry coding category.

### Which has the bigger context window?

Gemini 2.5 Pro does, with 1.05M tokens against 128K.

### How many benchmarks do Command R and Gemini 2.5 Pro share?

26 benchmarks have published results for both models. Command R has 29 scored results on Noometry and Gemini 2.5 Pro has 78.