Model comparison
Command R vs Llama-3.3-70B-Instruct
Command R and Llama-3.3-70B-Instruct score almost the same on the Noometry Index (31.4 vs 30.6), so choose on price, context window or the category you care about most.
Last verified . 29 shared benchmarks.
Cohere
MetaSummary
- They share 29 benchmarks with published results for both. Command R scores higher in 3 categories and Llama-3.3-70B-Instruct in 5 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in instruction following, where Llama-3.3-70B-Instruct leads 71.1 to 58.1.
- The biggest single-benchmark swing is LiveBench Reasoning: 21.9% for Command R and 50.8% for Llama-3.3-70B-Instruct.
- Llama-3.3-70B-Instruct is cheaper at $0.10 / $0.32 per million input/output tokens, against $0.15 / $0.60 for Command R.
Side by side
| Command R | Llama-3.3-70B-Instruct | |
|---|---|---|
| Provider | Cohere | Meta |
| Noometry Index | 31.4 | 30.6 |
| Released | 2024-08-30 | 2024-12-06 |
| Weights | Open | Open |
| Context window | 128K | 128K |
| Max output | 4K | 4K |
| Input $ / M tokens | $0.15 | $0.10 |
| Output $ / M tokens | $0.60 | $0.32 |
| Results tracked | 29 | 43 |
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Category by category
Coding Llama-3.3-70B-Instruct leads
Command R: 29.3 (#306), Llama-3.3-70B-Instruct: 31.0 (#290)
| Benchmark | Command R | Llama-3.3-70B-Instruct |
|---|---|---|
| BigCodeBench Instruct | 37.1% | 46.9% |
| LiveBench Coding | 17.9% | 36.6% |
| LMArena Coding | 1169 | 1268 |
| BigCodeBench Complete | 45.2% | 57.5% |
| SciCode | — | 26% |
| WeirdML | — | 14.4% |
Agentic & Tool Use Not comparable
Command R: —, Llama-3.3-70B-Instruct: 25.8 (#105)
| Benchmark | Command R | Llama-3.3-70B-Instruct |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 31.9% |
| BALROG | — | 23% |
Reasoning Too close to call
Command R: 13.8 (#331), Llama-3.3-70B-Instruct: 14.1 (#327)
| Benchmark | Command R | Llama-3.3-70B-Instruct |
|---|---|---|
| LiveBench Reasoning | 21.9% | 50.8% |
| LMArena Hard Prompts | 1164 | 1257 |
| DTBench | 46.4% | 59.5% |
| LiveBench Data Analysis | 33.3% | 49.5% |
| LMCA | 9.2% | 17.5% |
| LiveBench | 27.5% | 50.2% |
| SimpleBench | — | 19.9% |
| CritPt | — | 0% |
| Epoch Capabilities Index | — | 127.33 |
| ForecastBench | — | 58.6 |
Math Command R leads
Command R: 28.0 (#246), Llama-3.3-70B-Instruct: 15.3 (#298)
| Benchmark | Command R | Llama-3.3-70B-Instruct |
|---|---|---|
| LiveBench Math | 19.4% | 42.2% |
| LMArena Math | 1155 | 1267 |
| OTIS Mock AIME 2024-2025 | — | 5.1% |
| MATH Level 5 | — | 41.6% |
Knowledge Too close to call
Command R: 31.0 (#221), Llama-3.3-70B-Instruct: 30.6 (#226)
| Benchmark | Command R | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Expert | 1138 | 1225 |
| MMLU | 65.2% | 86.3% |
| GPQA Diamond | — | 47.4% |
| Confabulations | — | 22.8% |
| Vectara Hallucination Rate | — | 4.1% |
Multilingual Llama-3.3-70B-Instruct leads
Command R: 35.7 (#245), Llama-3.3-70B-Instruct: 39.9 (#220)
| Benchmark | Command R | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Non-English | 1174 | 1236 |
| LMArena Chinese | 1182 | 1217 |
| LMArena French | 1162 | 1281 |
| LMArena German | 1176 | 1251 |
| LMArena Japanese | 1143 | 1150 |
| LMArena Korean | 1163 | 1143 |
| LMArena Russian | 1174 | 1252 |
| LMArena Spanish | 1151 | 1270 |
Instruction Following Llama-3.3-70B-Instruct leads
Command R: 58.1 (#261), Llama-3.3-70B-Instruct: 71.1 (#157)
| Benchmark | Command R | Llama-3.3-70B-Instruct |
|---|---|---|
| LiveBench Instruction Following | 55.6% | 82.7% |
| LMArena Instruction Following | 1167 | 1242 |
Long Context Command R leads
Command R: 36.3 (#231), Llama-3.3-70B-Instruct: 26.4 (#295)
| Benchmark | Command R | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Longer Query | 1198 | 1256 |
| Fiction.LiveBench | — | 33.3% |
Writing & Preference Llama-3.3-70B-Instruct leads
Command R: 38.2 (#254), Llama-3.3-70B-Instruct: 47.6 (#207)
| Benchmark | Command R | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Text | 1187 | 1274 |
| LMArena Creative Writing | 1170 | 1250 |
| LMArena Multi-Turn | 1163 | 1280 |
| LiveBench Language | 16.7% | 39.2% |
Frequently asked questions
Is Command R better than Llama-3.3-70B-Instruct?
Command R and Llama-3.3-70B-Instruct score almost the same on the Noometry Index (31.4 vs 30.6), so choose on price, context window or the category you care about most.
Which is cheaper, Command R or Llama-3.3-70B-Instruct?
Llama-3.3-70B-Instruct is cheaper. It lists at $0.10 per million input tokens and $0.32 per million output tokens; Command R lists at $0.15 and $0.60.
Is Command R or Llama-3.3-70B-Instruct better for coding?
Llama-3.3-70B-Instruct scores higher on coding benchmarks: 31.0 versus 29.3 in the Noometry coding category.
Which has the bigger context window?
Both accept 128K tokens.
How many benchmarks do Command R and Llama-3.3-70B-Instruct share?
29 benchmarks have published results for both models. Command R has 29 scored results on Noometry and Llama-3.3-70B-Instruct has 43.