Model comparison
Command R vs GPT-3.5-turbo
Command R is the stronger model overall, scoring 31.0 to 23.1 on the Noometry Index.
Last verified . 22 shared benchmarks.
Summary
- They share 22 benchmarks with published results for both. Command R scores higher in 7 categories and GPT-3.5-turbo in 1 category; 6 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Command R leads 30.5 to 10.0.
- The biggest single-benchmark swing is BigCodeBench Complete: 45.2% for Command R and 50.6% for GPT-3.5-turbo.
- Command R is cheaper at $0.15 / $0.60 per million input/output tokens, against $0.50 / $1.50 for GPT-3.5-turbo.
- Command R accepts more context: 128K tokens versus 16K.
- Command R has downloadable open weights; the other is API-only.
Side by side
| Command R | GPT-3.5-turbo | |
|---|---|---|
| Provider | Cohere | OpenAI |
| Noometry Index | 31.0 | 23.1 |
| Released | 2024-08-30 | 2023-03-01 |
| Weights | Open | Proprietary |
| Context window | 128K | 16K |
| Max output | 4K | 4K |
| Input $ / M tokens | $0.15 | $0.50 |
| Output $ / M tokens | $0.60 | $1.50 |
| Results tracked | 29 | 44 |
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Category by category
Coding Command R leads
Command R: 28.8 (#301), GPT-3.5-turbo: 23.5 (#326)
| Benchmark | Command R | GPT-3.5-turbo |
|---|---|---|
| BigCodeBench Instruct | 37.1% | 39.1% |
| LMArena Coding | 1170 | 1137 |
| BigCodeBench Complete | 45.2% | 50.6% |
| WeirdML | — | 3.5% |
| LiveBench Coding | 17.9% | — |
| HumanEval+ | — | 70.7% |
| MBPP+ | — | 69.7% |
Agentic & Tool Use Not comparable
Command R: —, GPT-3.5-turbo: —
| Benchmark | Command R | GPT-3.5-turbo |
|---|---|---|
| METR Time Horizons | — | 21.5% |
Reasoning Too close to call
Command R: 13.3 (#329), GPT-3.5-turbo: 13.3 (#328)
| Benchmark | Command R | GPT-3.5-turbo |
|---|---|---|
| LMArena Hard Prompts | 1164 | 1108 |
| DTBench | 46.4% | 48.5% |
| LMCA | 9.2% | 9.7% |
| Chess Puzzles | — | 0% |
| LiveBench Reasoning | 21.9% | — |
| Mystery Game Puzzles | — | 3% |
| LiveBench Data Analysis | 33.3% | — |
| Adversarial NLI | — | 58.1% |
| BIG-Bench Hard | — | 61.6% |
| CommonsenseQA 2.0 | — | 57% |
| Epoch Capabilities Index | — | 118.48 |
| ForecastBench | — | 50.4 |
| LiveBench | 27.5% | — |
| WinoGrande | — | 81.6% |
Math Command R leads
Command R: 25.8 (#244), GPT-3.5-turbo: 6.0 (#321)
| Benchmark | Command R | GPT-3.5-turbo |
|---|---|---|
| LMArena Math | 1155 | 1142 |
| FrontierMath (Tiers 1-3) | — | 0% |
| OTIS Mock AIME 2024-2025 | — | 2.2% |
| LiveBench Math | 19.4% | — |
| MATH Level 5 | — | 15.9% |
| GSM8K | — | 57.8% |
Knowledge Command R leads
Command R: 30.5 (#219), GPT-3.5-turbo: 10.0 (#298)
| Benchmark | Command R | GPT-3.5-turbo |
|---|---|---|
| LMArena Expert | 1138 | 1070 |
| MMLU | 65.2% | 71.4% |
| GPQA Diamond | — | 28% |
| ARC (AI2) Challenge | — | 87.4% |
| BoolQ | — | 87% |
| OpenBookQA | — | 86% |
| TriviaQA | — | 85.8% |
Multilingual Command R leads
Command R: 35.9 (#240), GPT-3.5-turbo: 31.6 (#253)
| Benchmark | Command R | GPT-3.5-turbo |
|---|---|---|
| LMArena Non-English | 1174 | 1108 |
| LMArena Chinese | 1182 | 1075 |
| LMArena French | 1161 | 1117 |
| LMArena German | 1176 | 1090 |
| LMArena Japanese | 1143 | 1043 |
| LMArena Korean | 1162 | 1019 |
| LMArena Russian | 1174 | 1123 |
| LMArena Spanish | 1150 | 1120 |
Instruction Following Too close to call
Command R: 58.3 (#256), GPT-3.5-turbo: 58.1 (#257)
| Benchmark | Command R | GPT-3.5-turbo |
|---|---|---|
| LMArena Instruction Following | 1167 | 1119 |
| LiveBench Instruction Following | 55.6% | — |
Long Context Command R leads
Command R: 36.3 (#226), GPT-3.5-turbo: 34.0 (#249)
| Benchmark | Command R | GPT-3.5-turbo |
|---|---|---|
| LMArena Longer Query | 1198 | 1121 |
Writing & Preference Command R leads
Command R: 38.4 (#248), GPT-3.5-turbo: 25.4 (#300)
| Benchmark | Command R | GPT-3.5-turbo |
|---|---|---|
| LMArena Text | 1187 | 1125 |
| LMArena Creative Writing | 1170 | 1092 |
| LMArena Multi-Turn | 1163 | 1117 |
| EQ-Bench Creative Writing | — | 451 |
| LiveBench Language | 16.7% | — |
Frequently asked questions
Is Command R better than GPT-3.5-turbo?
Command R is the stronger model overall, scoring 31.0 to 23.1 on the Noometry Index.
Which is cheaper, Command R or GPT-3.5-turbo?
Command R is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; GPT-3.5-turbo lists at $0.50 and $1.50.
Is Command R or GPT-3.5-turbo better for coding?
Command R scores higher on coding benchmarks: 28.8 versus 23.5 in the Noometry coding category.
Which has the bigger context window?
Command R does, with 128K tokens against 16K.
How many benchmarks do Command R and GPT-3.5-turbo share?
22 benchmarks have published results for both models. Command R has 29 scored results on Noometry and GPT-3.5-turbo has 44.