Model comparison
Claude Opus 4.8 vs Command R
Claude Opus 4.8 is the stronger model overall, scoring 60.7 to 31.4 on the Noometry Index. Command R costs 38× less per token, which makes it the better buy when Claude Opus 4.8's lead doesn't matter for your workload.
Last verified . 19 shared benchmarks.
CohereSummary
- They share 19 benchmarks with published results for both. Claude Opus 4.8 scores higher in 8 categories and Command R in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Claude Opus 4.8 leads 64.7 to 13.8.
- The biggest single-benchmark swing is DTBench: 94.9% for Claude Opus 4.8 and 46.4% for Command R.
- Command R is cheaper at $0.15 / $0.60 per million input/output tokens, against $5 / $25 for Claude Opus 4.8.
- Claude Opus 4.8 accepts more context: 1M tokens versus 128K.
- Command R has downloadable open weights; the other is API-only.
Side by side
| Claude Opus 4.8 | Command R | |
|---|---|---|
| Provider | Anthropic | Cohere |
| Noometry Index | 60.7 | 31.4 |
| Released | 2026-05-28 | 2024-08-30 |
| Weights | Proprietary | Open |
| Context window | 1M | 128K |
| Max output | 128K | 4K |
| Input $ / M tokens | $5 | $0.15 |
| Output $ / M tokens | $25 | $0.60 |
| Results tracked | 65 | 29 |
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Category by category
Coding Claude Opus 4.8 leads
Claude Opus 4.8: 59.9 (#12), Command R: 29.3 (#306)
| Benchmark | Claude Opus 4.8 | Command R |
|---|---|---|
| LMArena Coding | 1490 | 1169 |
| DeepSWE | 59% | — |
| FrontierCode | 46.5% | — |
| LMArena WebDev | 1556 | — |
| SciCode | 53.5% | — |
| GSO | 47.1% | — |
| WeirdML | 82.9% | — |
| BigCodeBench Instruct | — | 37.1% |
| LiveBench Coding | — | 17.9% |
| BigCodeBench Complete | — | 45.2% |
| ALE-Bench | 1,564 | — |
Agentic & Tool Use Not comparable
Claude Opus 4.8: 47.6 (#11), Command R: —
| Benchmark | Claude Opus 4.8 | Command R |
|---|---|---|
| APEX-Agents | 48.9% | — |
| OSWorld 2.0 | 20.6% | — |
| Remote Labor Index | 8.3% | — |
| τ²-bench Banking | 39.7% | — |
| DeepResearch Bench | 50.2% | — |
| PostTrainBench | 33.8% | — |
| GBAEval | 70.9% | — |
| GDP.pdf | 24% | — |
| LMArena Search | 1204 | — |
| Vending-Bench 2 | 5,787 | — |
Reasoning Claude Opus 4.8 leads
Claude Opus 4.8: 64.7 (#16), Command R: 13.8 (#331)
| Benchmark | Claude Opus 4.8 | Command R |
|---|---|---|
| LMArena Hard Prompts | 1482 | 1164 |
| DTBench | 94.9% | 46.4% |
| LMCA | 57.5% | 9.2% |
| ARC-AGI-2 | 72.1% | — |
| SimpleBench | 64.8% | — |
| Kagi LLM Benchmark | 88.8% | — |
| NYT Connections (extended) | 91.1% | — |
| ARC-AGI-1 | 92.5% | — |
| CritPt | 20.9% | — |
| Chess Puzzles | 34% | — |
| EnigmaEval | 23.5% | — |
| EBR-Bench | 28.6% | — |
| LiveBench Reasoning | — | 21.9% |
| Mystery Game Puzzles | 36% | — |
| LiveBench Data Analysis | — | 33.3% |
| Surface Evolver Bench | 87.5% | — |
| Bench to the Future 3 | 0.14 | — |
| Epoch Capabilities Index | 158.21 | — |
| ForecastBench | 59.9 | — |
| LiveBench | — | 27.5% |
Math Claude Opus 4.8 leads
Claude Opus 4.8: 78.4 (#13), Command R: 28.0 (#246)
| Benchmark | Claude Opus 4.8 | Command R |
|---|---|---|
| LMArena Math | 1487 | 1155 |
| FrontierMath (Tiers 1-3) | 80% | — |
| FrontierMath Tier 4 | 56.1% | — |
| MathArena Final-Answer Competitions | 91.8% | — |
| OTIS Mock AIME 2024-2025 | 98.3% | — |
| ProofBench | 69% | — |
| LiveBench Math | — | 19.4% |
| FrontierMath (Feb 2025 set) | 47.2% | — |
| FrontierMath Tier 4 (v1) | 31.3% | — |
Knowledge Claude Opus 4.8 leads
Claude Opus 4.8: 61.3 (#29), Command R: 31.0 (#221)
| Benchmark | Claude Opus 4.8 | Command R |
|---|---|---|
| LMArena Expert | 1502 | 1138 |
| GPQA Diamond | 91% | — |
| SimpleQA Verified | 53% | — |
| MMLU | — | 65.2% |
Multimodal Not comparable
Claude Opus 4.8: 42.9 (#26), Command R: —
| Benchmark | Claude Opus 4.8 | Command R |
|---|---|---|
| LMArena Vision | 1294 | — |
| Blueprint-Bench 2 | 14.5% | — |
| Furniture Assembly | 42.5% | — |
| LMArena Document | 1475 | — |
Multilingual Claude Opus 4.8 leads
Claude Opus 4.8: 55.2 (#33), Command R: 35.7 (#245)
| Benchmark | Claude Opus 4.8 | Command R |
|---|---|---|
| LMArena Non-English | 1450 | 1174 |
| LMArena Chinese | 1507 | 1182 |
| LMArena French | 1481 | 1162 |
| LMArena German | 1472 | 1176 |
| LMArena Japanese | 1440 | 1143 |
| LMArena Korean | 1432 | 1163 |
| LMArena Russian | 1474 | 1174 |
| LMArena Spanish | 1466 | 1151 |
Instruction Following Claude Opus 4.8 leads
Claude Opus 4.8: 77.4 (#24), Command R: 58.1 (#261)
| Benchmark | Claude Opus 4.8 | Command R |
|---|---|---|
| LMArena Instruction Following | 1476 | 1167 |
| LiveBench Instruction Following | — | 55.6% |
Long Context Claude Opus 4.8 leads
Claude Opus 4.8: 45.4 (#35), Command R: 36.3 (#231)
| Benchmark | Claude Opus 4.8 | Command R |
|---|---|---|
| LMArena Longer Query | 1483 | 1198 |
Writing & Preference Claude Opus 4.8 leads
Claude Opus 4.8: 72.0 (#16), Command R: 38.2 (#254)
| Benchmark | Claude Opus 4.8 | Command R |
|---|---|---|
| LMArena Text | 1461 | 1187 |
| LMArena Creative Writing | 1454 | 1170 |
| LMArena Multi-Turn | 1476 | 1163 |
| EQ-Bench Creative Writing | 1840 | — |
| EQ-Bench 4 | 1281 | — |
| LiveBench Language | — | 16.7% |
Frequently asked questions
Is Claude Opus 4.8 better than Command R?
Claude Opus 4.8 is the stronger model overall, scoring 60.7 to 31.4 on the Noometry Index. Command R costs 38× less per token, which makes it the better buy when Claude Opus 4.8's lead doesn't matter for your workload.
Which is cheaper, Claude Opus 4.8 or Command R?
Command R is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; Claude Opus 4.8 lists at $5 and $25.
Is Claude Opus 4.8 or Command R better for coding?
Claude Opus 4.8 scores higher on coding benchmarks: 59.9 versus 29.3 in the Noometry coding category.
Which has the bigger context window?
Claude Opus 4.8 does, with 1M tokens against 128K.
How many benchmarks do Claude Opus 4.8 and Command R share?
19 benchmarks have published results for both models. Claude Opus 4.8 has 65 scored results on Noometry and Command R has 29.