Model comparison
Command R vs GPT-4.1 mini
GPT-4.1 mini is the stronger model overall, scoring 33.6 to 31.4 on the Noometry Index. Command R costs 2.7× less per token, which makes it the better buy when GPT-4.1 mini's lead doesn't matter for your workload.
Last verified . 20 shared benchmarks.
CohereSummary
- They share 20 benchmarks with published results for both. Command R scores higher in 3 categories and GPT-4.1 mini in 5 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in instruction following, where GPT-4.1 mini leads 73.7 to 58.1.
- The biggest single-benchmark swing is DTBench: 46.4% for Command R and 68.8% for GPT-4.1 mini.
- Command R is cheaper at $0.15 / $0.60 per million input/output tokens, against $0.40 / $1.60 for GPT-4.1 mini.
- GPT-4.1 mini 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 mini | |
|---|---|---|
| Provider | Cohere | OpenAI |
| Noometry Index | 31.4 | 33.6 |
| Released | 2024-08-30 | 2025-04-14 |
| Weights | Open | Proprietary |
| Context window | 128K | 1.05M |
| Max output | 4K | 33K |
| Input $ / M tokens | $0.15 | $0.40 |
| Output $ / M tokens | $0.60 | $1.60 |
| Results tracked | 29 | 47 |
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Category by category
Coding GPT-4.1 mini leads
Command R: 29.3 (#306), GPT-4.1 mini: 30.6 (#293)
| Benchmark | Command R | GPT-4.1 mini |
|---|---|---|
| BigCodeBench Instruct | 37.1% | 48.9% |
| LMArena Coding | 1169 | 1367 |
| SWE-bench Verified (bash only) | — | 23.9% |
| Aider Polyglot | — | 32.4% |
| SciCode | — | 40.4% |
| WeirdML | — | 37.6% |
| LiveBench Coding | 17.9% | — |
| BigCodeBench Complete | 45.2% | — |
| CadEval | — | 16% |
Agentic & Tool Use Not comparable
Command R: —, GPT-4.1 mini: 33.3 (#55)
| Benchmark | Command R | GPT-4.1 mini |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 50.5% |
Reasoning Command R leads
Command R: 13.8 (#331), GPT-4.1 mini: 10.8 (#340)
| Benchmark | Command R | GPT-4.1 mini |
|---|---|---|
| LMArena Hard Prompts | 1164 | 1349 |
| DTBench | 46.4% | 68.8% |
| LMCA | 9.2% | 21.1% |
| ARC-AGI-2 | — | 0% |
| Kagi LLM Benchmark | — | 48.6% |
| ARC-AGI-1 | — | 3.5% |
| CritPt | — | 0% |
| Chess Puzzles | — | 7% |
| LiveBench Reasoning | 21.9% | — |
| Mystery Game Puzzles | — | 7% |
| LiveBench Data Analysis | 33.3% | — |
| Epoch Capabilities Index | — | 135.01 |
| LiveBench | 27.5% | — |
Math Command R leads
Command R: 28.0 (#246), GPT-4.1 mini: 24.1 (#270)
| Benchmark | Command R | GPT-4.1 mini |
|---|---|---|
| LMArena Math | 1155 | 1343 |
| FrontierMath (Tiers 1-3) | — | 6.7% |
| OTIS Mock AIME 2024-2025 | — | 44.7% |
| Omni-MATH | — | 49.1% |
| LiveBench Math | 19.4% | — |
| MATH Level 5 | — | 87.3% |
| FrontierMath (Feb 2025 set) | — | 4.5% |
Knowledge GPT-4.1 mini leads
Command R: 31.0 (#221), GPT-4.1 mini: 34.7 (#194)
| Benchmark | Command R | GPT-4.1 mini |
|---|---|---|
| LMArena Expert | 1138 | 1338 |
| GPQA Diamond | — | 65.8% |
| SimpleQA Verified | — | 12.7% |
| MMLU-Pro | — | 78.3% |
| GPQA (HELM) | — | 61.4% |
| MMLU | 65.2% | — |
Multimodal Not comparable
Command R: —, GPT-4.1 mini: 35.8 (#82)
| Benchmark | Command R | GPT-4.1 mini |
|---|---|---|
| LMArena Vision | — | 1181 |
Multilingual GPT-4.1 mini leads
Command R: 35.7 (#245), GPT-4.1 mini: 45.7 (#166)
| Benchmark | Command R | GPT-4.1 mini |
|---|---|---|
| LMArena Non-English | 1174 | 1318 |
| LMArena Chinese | 1182 | 1329 |
| LMArena French | 1162 | 1358 |
| LMArena German | 1176 | 1351 |
| LMArena Japanese | 1143 | 1290 |
| LMArena Korean | 1163 | 1298 |
| LMArena Russian | 1174 | 1324 |
| LMArena Spanish | 1151 | 1319 |
Instruction Following GPT-4.1 mini leads
Command R: 58.1 (#261), GPT-4.1 mini: 73.7 (#118)
| Benchmark | Command R | GPT-4.1 mini |
|---|---|---|
| LMArena Instruction Following | 1167 | 1333 |
| LiveBench Instruction Following | 55.6% | — |
| IFEval | — | 90.4% |
Long Context Command R leads
Command R: 36.3 (#231), GPT-4.1 mini: 31.8 (#275)
| Benchmark | Command R | GPT-4.1 mini |
|---|---|---|
| LMArena Longer Query | 1198 | 1344 |
| Fiction.LiveBench | — | 44.4% |
Writing & Preference GPT-4.1 mini leads
Command R: 38.2 (#254), GPT-4.1 mini: 48.6 (#199)
| Benchmark | Command R | GPT-4.1 mini |
|---|---|---|
| LMArena Text | 1187 | 1340 |
| LMArena Creative Writing | 1170 | 1300 |
| LMArena Multi-Turn | 1163 | 1354 |
| EQ-Bench Creative Writing | — | 1147 |
| WildBench | — | 83.8% |
| LiveBench Language | 16.7% | — |
Frequently asked questions
Is Command R better than GPT-4.1 mini?
GPT-4.1 mini is the stronger model overall, scoring 33.6 to 31.4 on the Noometry Index. Command R costs 2.7× less per token, which makes it the better buy when GPT-4.1 mini's lead doesn't matter for your workload.
Which is cheaper, Command R or GPT-4.1 mini?
Command R is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; GPT-4.1 mini lists at $0.40 and $1.60.
Is Command R or GPT-4.1 mini better for coding?
GPT-4.1 mini scores higher on coding benchmarks: 30.6 versus 29.3 in the Noometry coding category.
Which has the bigger context window?
GPT-4.1 mini does, with 1.05M tokens against 128K.
How many benchmarks do Command R and GPT-4.1 mini share?
20 benchmarks have published results for both models. Command R has 29 scored results on Noometry and GPT-4.1 mini has 47.