Model comparison
Command R+ vs GPT-5 Nano
GPT-5 Nano is the stronger model overall, scoring 33.5 to 32.4 on the Noometry Index.
Last verified . 20 shared benchmarks.
CohereSummary
- They share 20 benchmarks with published results for both. Command R+ scores higher in 3 categories and GPT-5 Nano in 5 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in instruction following, where GPT-5 Nano leads 75.0 to 60.0.
- The biggest single-benchmark swing is DTBench: 54.9% for Command R+ and 62.7% 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 R+.
- GPT-5 Nano accepts more context: 400K tokens versus 128K.
- Command R+ has downloadable open weights; the other is API-only.
Side by side
| Command R+ | GPT-5 Nano | |
|---|---|---|
| Provider | Cohere | OpenAI |
| Noometry Index | 32.4 | 33.5 |
| Released | 2024-08-30 | 2025-08-07 |
| Weights | Open | Proprietary |
| Context window | 128K | 400K |
| Max output | 4K | 128K |
| Input $ / M tokens | $2.50 | $0.05 |
| Output $ / M tokens | $10 | $0.40 |
| Results tracked | 34 | 49 |
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Category by category
Coding GPT-5 Nano leads
Command R+: 29.1 (#309), GPT-5 Nano: 33.6 (#254)
| Benchmark | Command R+ | GPT-5 Nano |
|---|---|---|
| LMArena Coding | 1187 | 1351 |
| SWE-bench Verified (bash only) | — | 34.8% |
| WeirdML | — | 38.1% |
| BigCodeBench Instruct | 33.8% | — |
| LiveBench Coding | 19.1% | — |
| BigCodeBench Complete | 41.9% | — |
| ALE-Bench | — | 718.67 |
| HumanEval+ | 56.7% | — |
| MBPP+ | 63.5% | — |
Agentic & Tool Use Not comparable
Command R+: —, GPT-5 Nano: 25.8 (#106)
| Benchmark | Command R+ | GPT-5 Nano |
|---|---|---|
| Terminal-Bench | — | 21.8% |
| Berkeley Function Calling Leaderboard | — | 51.5% |
Reasoning GPT-5 Nano leads
Command R+: 9.2 (#344), GPT-5 Nano: 16.3 (#306)
| Benchmark | Command R+ | GPT-5 Nano |
|---|---|---|
| LMArena Hard Prompts | 1186 | 1328 |
| DTBench | 54.9% | 62.7% |
| LMCA | 5% | 7.9% |
| Epoch Capabilities Index | 119.34 | 139.38 |
| ARC-AGI-2 | — | 2.6% |
| SimpleBench | 17.4% | — |
| Kagi LLM Benchmark | — | 62.2% |
| ARC-AGI-1 | — | 20.7% |
| Chess Puzzles | — | 27% |
| LiveBench Reasoning | 24.8% | — |
| Mystery Game Puzzles | — | 9% |
| LiveBench Data Analysis | 38.1% | — |
| ForecastBench | — | 59.1 |
| LiveBench | 31.8% | — |
Math Too close to call
Command R+: 28.9 (#242), GPT-5 Nano: 29.4 (#241)
| Benchmark | Command R+ | GPT-5 Nano |
|---|---|---|
| LMArena Math | 1188 | 1317 |
| FrontierMath (Tiers 1-3) | — | 20% |
| FrontierMath Tier 4 | — | 2.4% |
| OTIS Mock AIME 2024-2025 | — | 81.1% |
| ProofBench | — | 12% |
| Omni-MATH | — | 54.6% |
| LiveBench Math | 21.3% | — |
| MATH Level 5 | — | 95.2% |
| FrontierMath (Feb 2025 set) | — | 8.3% |
| FrontierMath Tier 4 (v1) | — | 2.1% |
Knowledge Too close to call
Command R+: 36.4 (#169), GPT-5 Nano: 35.9 (#178)
| Benchmark | Command R+ | GPT-5 Nano |
|---|---|---|
| Vectara Hallucination Rate | 6.9% | 10.5% |
| LMArena Expert | 1174 | 1321 |
| GPQA Diamond | — | 69.4% |
| SimpleQA Verified | — | 11.7% |
| MMLU-Pro | — | 77.8% |
| GPQA (HELM) | — | 67.9% |
| MMLU | 69.4% | — |
Multimodal Not comparable
Command R+: —, GPT-5 Nano: 31.3 (#108)
| Benchmark | Command R+ | GPT-5 Nano |
|---|---|---|
| LMArena Vision | — | 1159 |
| VPCT | — | 37.2% |
Multilingual GPT-5 Nano leads
Command R+: 38.6 (#227), GPT-5 Nano: 45.3 (#172)
| Benchmark | Command R+ | GPT-5 Nano |
|---|---|---|
| LMArena Non-English | 1216 | 1313 |
| LMArena Chinese | 1226 | 1356 |
| LMArena German | 1216 | 1327 |
| LMArena Japanese | 1166 | 1226 |
| LMArena Korean | 1138 | 1269 |
| LMArena Russian | 1227 | 1296 |
| LMArena Spanish | 1189 | 1360 |
| LMArena French | 1209 | — |
Instruction Following GPT-5 Nano leads
Command R+: 60.0 (#254), GPT-5 Nano: 75.0 (#79)
| Benchmark | Command R+ | GPT-5 Nano |
|---|---|---|
| LMArena Instruction Following | 1197 | 1306 |
| LiveBench Instruction Following | 57.6% | — |
| IFEval | — | 93.2% |
Long Context Command R+ leads
Command R+: 37.3 (#219), GPT-5 Nano: 31.3 (#281)
| Benchmark | Command R+ | GPT-5 Nano |
|---|---|---|
| LMArena Longer Query | 1230 | 1312 |
| Fiction.LiveBench | — | 44.4% |
Writing & Preference Command R+ leads
Command R+: 43.5 (#228), GPT-5 Nano: 39.1 (#249)
| Benchmark | Command R+ | GPT-5 Nano |
|---|---|---|
| LMArena Text | 1229 | 1320 |
| LMArena Creative Writing | 1235 | 1249 |
| LMArena Multi-Turn | 1213 | 1311 |
| EQ-Bench Creative Writing | — | 705 |
| WildBench | — | 80.6% |
| LiveBench Language | 29.7% | — |
Frequently asked questions
Is Command R+ better than GPT-5 Nano?
GPT-5 Nano is the stronger model overall, scoring 33.5 to 32.4 on the Noometry Index.
Which is cheaper, Command R+ 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 R+ lists at $2.50 and $10.
Is Command R+ or GPT-5 Nano better for coding?
GPT-5 Nano scores higher on coding benchmarks: 33.6 versus 29.1 in the Noometry coding category.
Which has the bigger context window?
GPT-5 Nano does, with 400K tokens against 128K.
How many benchmarks do Command R+ and GPT-5 Nano share?
20 benchmarks have published results for both models. Command R+ has 34 scored results on Noometry and GPT-5 Nano has 49.