Model comparison
Command R+ vs Llama 4 Scout
Command R+ is the stronger model overall, scoring 32.4 to 27.7 on the Noometry Index. Llama 4 Scout costs 29× less per token, which makes it the better buy when Command R+'s lead doesn't matter for your workload.
Last verified . 22 shared benchmarks.
Cohere
MetaSummary
- They share 22 benchmarks with published results for both. Command R+ scores higher in 6 categories and Llama 4 Scout in 2 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in long context, where Command R+ leads 37.3 to 27.5.
- The biggest single-benchmark swing is LMCA: 5% for Command R+ and 12% for Llama 4 Scout.
- Llama 4 Scout is cheaper at $0.10 / $0.30 per million input/output tokens, against $2.50 / $10 for Command R+.
Side by side
| Command R+ | Llama 4 Scout | |
|---|---|---|
| Provider | Cohere | Meta |
| Noometry Index | 32.4 | 27.7 |
| Released | 2024-08-30 | 2025-04-05 |
| Weights | Open | Open |
| Context window | 128K | 128K |
| Max output | 4K | 4K |
| Input $ / M tokens | $2.50 | $0.10 |
| Output $ / M tokens | $10 | $0.30 |
| Results tracked | 34 | 43 |
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Category by category
Coding Command R+ leads
Command R+: 29.1 (#309), Llama 4 Scout: 20.2 (#339)
| Benchmark | Command R+ | Llama 4 Scout |
|---|---|---|
| LMArena Coding | 1187 | 1286 |
| BigCodeBench Complete | 41.9% | 43.1% |
| SWE-bench Verified (bash only) | — | 9.1% |
| SciCode | — | 17% |
| BigCodeBench Instruct | 33.8% | — |
| LiveBench Coding | 19.1% | — |
| HumanEval+ | 56.7% | — |
| MBPP+ | 63.5% | — |
Agentic & Tool Use Not comparable
Command R+: —, Llama 4 Scout: 24.6 (#119)
| Benchmark | Command R+ | Llama 4 Scout |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 28.1% |
Reasoning Too close to call
Command R+: 9.2 (#344), Llama 4 Scout: 9.1 (#345)
| Benchmark | Command R+ | Llama 4 Scout |
|---|---|---|
| LMArena Hard Prompts | 1186 | 1266 |
| DTBench | 54.9% | 57.9% |
| LMCA | 5% | 12% |
| Epoch Capabilities Index | 119.34 | 129.64 |
| ARC-AGI-2 | — | 0% |
| SimpleBench | 17.4% | — |
| Kagi LLM Benchmark | — | 36.9% |
| ARC-AGI-1 | — | 0.5% |
| CritPt | — | 0% |
| LiveBench Reasoning | 24.8% | — |
| LiveBench Data Analysis | 38.1% | — |
| ForecastBench | — | 57.5 |
| LiveBench | 31.8% | — |
Math Command R+ leads
Command R+: 28.9 (#242), Llama 4 Scout: 19.6 (#286)
| Benchmark | Command R+ | Llama 4 Scout |
|---|---|---|
| LMArena Math | 1188 | 1287 |
| OTIS Mock AIME 2024-2025 | — | 7.8% |
| Omni-MATH | — | 37.3% |
| LiveBench Math | 21.3% | — |
| MATH Level 5 | — | 62.3% |
| FrontierMath (Feb 2025 set) | — | 0% |
Knowledge Command R+ leads
Command R+: 36.4 (#169), Llama 4 Scout: 31.9 (#217)
| Benchmark | Command R+ | Llama 4 Scout |
|---|---|---|
| Vectara Hallucination Rate | 6.9% | 7.7% |
| LMArena Expert | 1174 | 1235 |
| GPQA Diamond | — | 51.8% |
| MMLU-Pro | — | 74.2% |
| GPQA (HELM) | — | 50.7% |
| MMLU | 69.4% | — |
Multimodal Not comparable
Command R+: —, Llama 4 Scout: 32.2 (#102)
| Benchmark | Command R+ | Llama 4 Scout |
|---|---|---|
| LMArena Vision | — | 1118 |
| SpatialViz-Bench | — | 34.2% |
Multilingual Llama 4 Scout leads
Command R+: 38.6 (#227), Llama 4 Scout: 41.0 (#212)
| Benchmark | Command R+ | Llama 4 Scout |
|---|---|---|
| LMArena Non-English | 1216 | 1252 |
| LMArena Chinese | 1226 | 1255 |
| LMArena French | 1209 | 1282 |
| LMArena German | 1216 | 1272 |
| LMArena Japanese | 1166 | 1206 |
| LMArena Korean | 1138 | 1207 |
| LMArena Russian | 1227 | 1263 |
| LMArena Spanish | 1189 | 1278 |
Instruction Following Llama 4 Scout leads
Command R+: 60.0 (#254), Llama 4 Scout: 65.8 (#217)
| Benchmark | Command R+ | Llama 4 Scout |
|---|---|---|
| LMArena Instruction Following | 1197 | 1248 |
| LiveBench Instruction Following | 57.6% | — |
| IFEval | — | 81.8% |
Long Context Command R+ leads
Command R+: 37.3 (#219), Llama 4 Scout: 27.5 (#294)
| Benchmark | Command R+ | Llama 4 Scout |
|---|---|---|
| LMArena Longer Query | 1230 | 1265 |
| Fiction.LiveBench | — | 36% |
Writing & Preference Command R+ leads
Command R+: 43.5 (#228), Llama 4 Scout: 37.0 (#261)
| Benchmark | Command R+ | Llama 4 Scout |
|---|---|---|
| LMArena Text | 1229 | 1279 |
| LMArena Creative Writing | 1235 | 1249 |
| LMArena Multi-Turn | 1213 | 1280 |
| EQ-Bench Creative Writing | — | 783 |
| WildBench | — | 78% |
| LiveBench Language | 29.7% | — |
Frequently asked questions
Is Command R+ better than Llama 4 Scout?
Command R+ is the stronger model overall, scoring 32.4 to 27.7 on the Noometry Index. Llama 4 Scout costs 29× 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 Llama 4 Scout?
Llama 4 Scout is cheaper. It lists at $0.10 per million input tokens and $0.30 per million output tokens; Command R+ lists at $2.50 and $10.
Is Command R+ or Llama 4 Scout better for coding?
Command R+ scores higher on coding benchmarks: 29.1 versus 20.2 in the Noometry coding category.
Which has the bigger context window?
Both accept 128K tokens.
How many benchmarks do Command R+ and Llama 4 Scout share?
22 benchmarks have published results for both models. Command R+ has 34 scored results on Noometry and Llama 4 Scout has 43.