Model comparison
Command R vs GPT-4.1 nano
Command R is the stronger model overall, scoring 31.4 to 27.9 on the Noometry Index.
Last verified . 16 shared benchmarks.
CohereSummary
- They share 16 benchmarks with published results for both. Command R scores higher in 5 categories and GPT-4.1 nano in 3 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in long context, where Command R leads 36.3 to 23.7.
- The biggest single-benchmark swing is DTBench: 46.4% for Command R and 52.5% for GPT-4.1 nano.
- GPT-4.1 nano is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.15 / $0.60 for Command R.
- GPT-4.1 nano accepts more context: 1.05M tokens versus 128K.
- Command R has downloadable open weights; the other is API-only.
Side by side
| Command R | GPT-4.1 nano | |
|---|---|---|
| Provider | Cohere | OpenAI |
| Noometry Index | 31.4 | 27.9 |
| Released | 2024-08-30 | 2025-04-14 |
| Weights | Open | Proprietary |
| Context window | 128K | 1.05M |
| Max output | 4K | 33K |
| Input $ / M tokens | $0.15 | $0.10 |
| Output $ / M tokens | $0.60 | $0.40 |
| Results tracked | 29 | 38 |
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Category by category
Coding Command R leads
Command R: 29.3 (#306), GPT-4.1 nano: 24.1 (#330)
| Benchmark | Command R | GPT-4.1 nano |
|---|---|---|
| LMArena Coding | 1169 | 1306 |
| Aider Polyglot | — | 8.9% |
| SciCode | — | 25.9% |
| WeirdML | — | 19% |
| BigCodeBench Instruct | 37.1% | — |
| LiveBench Coding | 17.9% | — |
| BigCodeBench Complete | 45.2% | — |
Agentic & Tool Use Not comparable
Command R: —, GPT-4.1 nano: 26.5 (#104)
| Benchmark | Command R | GPT-4.1 nano |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 33% |
Reasoning Command R leads
Command R: 13.8 (#331), GPT-4.1 nano: 8.5 (#349)
| Benchmark | Command R | GPT-4.1 nano |
|---|---|---|
| LMArena Hard Prompts | 1164 | 1286 |
| DTBench | 46.4% | 52.5% |
| LMCA | 9.2% | 5.5% |
| ARC-AGI-2 | — | 0% |
| Kagi LLM Benchmark | — | 33.3% |
| ARC-AGI-1 | — | 0% |
| CritPt | — | 0% |
| LiveBench Reasoning | 21.9% | — |
| LiveBench Data Analysis | 33.3% | — |
| Epoch Capabilities Index | — | 129.62 |
| LiveBench | 27.5% | — |
Math Command R leads
Command R: 28.0 (#246), GPT-4.1 nano: 26.9 (#252)
| Benchmark | Command R | GPT-4.1 nano |
|---|---|---|
| LMArena Math | 1155 | 1274 |
| OTIS Mock AIME 2024-2025 | — | 28.9% |
| Omni-MATH | — | 36.7% |
| LiveBench Math | 19.4% | — |
| MATH Level 5 | — | 70% |
| FrontierMath (Feb 2025 set) | — | 1% |
Knowledge Command R leads
Command R: 31.0 (#221), GPT-4.1 nano: 21.8 (#273)
| Benchmark | Command R | GPT-4.1 nano |
|---|---|---|
| LMArena Expert | 1138 | 1272 |
| GPQA Diamond | — | 48.9% |
| SimpleQA Verified | — | 6% |
| MMLU-Pro | — | 55% |
| GPQA (HELM) | — | 50.7% |
| MMLU | 65.2% | — |
Multimodal Not comparable
Command R: —, GPT-4.1 nano: 29.2 (#113)
| Benchmark | Command R | GPT-4.1 nano |
|---|---|---|
| LMArena Vision | — | 1063 |
Multilingual GPT-4.1 nano leads
Command R: 35.7 (#245), GPT-4.1 nano: 41.6 (#205)
| Benchmark | Command R | GPT-4.1 nano |
|---|---|---|
| LMArena Non-English | 1174 | 1260 |
| LMArena Chinese | 1182 | 1270 |
| LMArena German | 1176 | 1288 |
| LMArena Japanese | 1143 | 1198 |
| LMArena Russian | 1174 | 1261 |
| LMArena French | 1162 | — |
| LMArena Korean | 1163 | — |
| LMArena Spanish | 1151 | — |
Instruction Following GPT-4.1 nano leads
Command R: 58.1 (#261), GPT-4.1 nano: 67.8 (#193)
| Benchmark | Command R | GPT-4.1 nano |
|---|---|---|
| LMArena Instruction Following | 1167 | 1267 |
| LiveBench Instruction Following | 55.6% | — |
| IFEval | — | 84.3% |
Long Context Command R leads
Command R: 36.3 (#231), GPT-4.1 nano: 23.7 (#296)
| Benchmark | Command R | GPT-4.1 nano |
|---|---|---|
| LMArena Longer Query | 1198 | 1283 |
| Fiction.LiveBench | — | 25% |
Writing & Preference GPT-4.1 nano leads
Command R: 38.2 (#254), GPT-4.1 nano: 40.5 (#243)
| Benchmark | Command R | GPT-4.1 nano |
|---|---|---|
| LMArena Text | 1187 | 1285 |
| LMArena Creative Writing | 1170 | 1260 |
| LMArena Multi-Turn | 1163 | 1277 |
| EQ-Bench Creative Writing | — | 946 |
| WildBench | — | 81.2% |
| LiveBench Language | 16.7% | — |
Frequently asked questions
Is Command R better than GPT-4.1 nano?
Command R is the stronger model overall, scoring 31.4 to 27.9 on the Noometry Index.
Which is cheaper, Command R or GPT-4.1 nano?
GPT-4.1 nano is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; Command R lists at $0.15 and $0.60.
Is Command R or GPT-4.1 nano better for coding?
Command R scores higher on coding benchmarks: 29.3 versus 24.1 in the Noometry coding category.
Which has the bigger context window?
GPT-4.1 nano does, with 1.05M tokens against 128K.
How many benchmarks do Command R and GPT-4.1 nano share?
16 benchmarks have published results for both models. Command R has 29 scored results on Noometry and GPT-4.1 nano has 38.