Model comparison
Command R+ vs GPT-4.1 nano
Command R+ is the stronger model overall, scoring 32.4 to 27.9 on the Noometry Index. GPT-4.1 nano costs 25× less per token, which makes it the better buy when Command R+'s lead doesn't matter for your workload.
Last verified . 17 shared benchmarks.
Summary
- They share 17 benchmarks with published results for both. Command R+ scores higher in 6 categories and GPT-4.1 nano in 2 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Command R+ leads 36.4 to 21.8.
- GPT-4.1 nano is cheaper at $0.10 / $0.40 per million input/output tokens, against $2.50 / $10 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 | 32.4 | 27.9 |
| Released | 2024-08-30 | 2025-04-14 |
| Weights | Open | Proprietary |
| Context window | 128K | 1.05M |
| Max output | 4K | 33K |
| Input $ / M tokens | $2.50 | $0.10 |
| Output $ / M tokens | $10 | $0.40 |
| Results tracked | 34 | 38 |
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Category by category
Coding Command R+ leads
Command R+: 29.1 (#309), GPT-4.1 nano: 24.1 (#330)
| Benchmark | Command R+ | GPT-4.1 nano |
|---|---|---|
| LMArena Coding | 1187 | 1306 |
| Aider Polyglot | — | 8.9% |
| SciCode | — | 25.9% |
| WeirdML | — | 19% |
| BigCodeBench Instruct | 33.8% | — |
| LiveBench Coding | 19.1% | — |
| BigCodeBench Complete | 41.9% | — |
| HumanEval+ | 56.7% | — |
| MBPP+ | 63.5% | — |
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 Too close to call
Command R+: 9.2 (#344), GPT-4.1 nano: 8.5 (#349)
| Benchmark | Command R+ | GPT-4.1 nano |
|---|---|---|
| LMArena Hard Prompts | 1186 | 1286 |
| DTBench | 54.9% | 52.5% |
| LMCA | 5% | 5.5% |
| Epoch Capabilities Index | 119.34 | 129.62 |
| ARC-AGI-2 | — | 0% |
| SimpleBench | 17.4% | — |
| Kagi LLM Benchmark | — | 33.3% |
| ARC-AGI-1 | — | 0% |
| CritPt | — | 0% |
| LiveBench Reasoning | 24.8% | — |
| LiveBench Data Analysis | 38.1% | — |
| LiveBench | 31.8% | — |
Math Command R+ leads
Command R+: 28.9 (#242), GPT-4.1 nano: 26.9 (#252)
| Benchmark | Command R+ | GPT-4.1 nano |
|---|---|---|
| LMArena Math | 1188 | 1274 |
| OTIS Mock AIME 2024-2025 | — | 28.9% |
| Omni-MATH | — | 36.7% |
| LiveBench Math | 21.3% | — |
| MATH Level 5 | — | 70% |
| FrontierMath (Feb 2025 set) | — | 1% |
Knowledge Command R+ leads
Command R+: 36.4 (#169), GPT-4.1 nano: 21.8 (#273)
| Benchmark | Command R+ | GPT-4.1 nano |
|---|---|---|
| LMArena Expert | 1174 | 1272 |
| GPQA Diamond | — | 48.9% |
| SimpleQA Verified | — | 6% |
| MMLU-Pro | — | 55% |
| Vectara Hallucination Rate | 6.9% | — |
| GPQA (HELM) | — | 50.7% |
| MMLU | 69.4% | — |
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+: 38.6 (#227), GPT-4.1 nano: 41.6 (#205)
| Benchmark | Command R+ | GPT-4.1 nano |
|---|---|---|
| LMArena Non-English | 1216 | 1260 |
| LMArena Chinese | 1226 | 1270 |
| LMArena German | 1216 | 1288 |
| LMArena Japanese | 1166 | 1198 |
| LMArena Russian | 1227 | 1261 |
| LMArena French | 1209 | — |
| LMArena Korean | 1138 | — |
| LMArena Spanish | 1189 | — |
Instruction Following GPT-4.1 nano leads
Command R+: 60.0 (#254), GPT-4.1 nano: 67.8 (#193)
| Benchmark | Command R+ | GPT-4.1 nano |
|---|---|---|
| LMArena Instruction Following | 1197 | 1267 |
| LiveBench Instruction Following | 57.6% | — |
| IFEval | — | 84.3% |
Long Context Command R+ leads
Command R+: 37.3 (#219), GPT-4.1 nano: 23.7 (#296)
| Benchmark | Command R+ | GPT-4.1 nano |
|---|---|---|
| LMArena Longer Query | 1230 | 1283 |
| Fiction.LiveBench | — | 25% |
Writing & Preference Command R+ leads
Command R+: 43.5 (#228), GPT-4.1 nano: 40.5 (#243)
| Benchmark | Command R+ | GPT-4.1 nano |
|---|---|---|
| LMArena Text | 1229 | 1285 |
| LMArena Creative Writing | 1235 | 1260 |
| LMArena Multi-Turn | 1213 | 1277 |
| EQ-Bench Creative Writing | — | 946 |
| WildBench | — | 81.2% |
| LiveBench Language | 29.7% | — |
Frequently asked questions
Is Command R+ better than GPT-4.1 nano?
Command R+ is the stronger model overall, scoring 32.4 to 27.9 on the Noometry Index. GPT-4.1 nano costs 25× less per token, which makes it the better buy when Command R+'s lead doesn't matter for your workload.
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 $2.50 and $10.
Is Command R+ or GPT-4.1 nano better for coding?
Command R+ scores higher on coding benchmarks: 29.1 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?
17 benchmarks have published results for both models. Command R+ has 34 scored results on Noometry and GPT-4.1 nano has 38.