Model comparison
Command R vs Qwen3.7 Max
Qwen3.7 Max is the stronger model overall, scoring 51.5 to 31.4 on the Noometry Index. Command R costs 14× less per token, which makes it the better buy when Qwen3.7 Max's lead doesn't matter for your workload.
Last verified . 14 shared benchmarks.
Cohere
Alibaba (Qwen)Summary
- They share 14 benchmarks with published results for both. Command R scores higher in 0 categories and Qwen3.7 Max in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Qwen3.7 Max leads 49.2 to 13.8.
- The biggest single-benchmark swing is DTBench: 46.4% for Command R and 92.3% for Qwen3.7 Max.
- Command R is cheaper at $0.15 / $0.60 per million input/output tokens, against $2.50 / $7.50 for Qwen3.7 Max.
- Qwen3.7 Max accepts more context: 1M tokens versus 128K.
- Command R has downloadable open weights; the other is API-only.
Side by side
| Command R | Qwen3.7 Max | |
|---|---|---|
| Provider | Cohere | Alibaba (Qwen) |
| Noometry Index | 31.4 | 51.5 |
| Released | 2024-08-30 | 2026-05-19 |
| Weights | Open | Proprietary |
| Context window | 128K | 1M |
| Max output | 4K | 131K |
| Input $ / M tokens | $0.15 | $2.50 |
| Output $ / M tokens | $0.60 | $7.50 |
| Results tracked | 29 | 33 |
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Category by category
Coding Qwen3.7 Max leads
Command R: 29.3 (#306), Qwen3.7 Max: 50.4 (#45)
| Benchmark | Command R | Qwen3.7 Max |
|---|---|---|
| LMArena Coding | 1169 | 1498 |
| SWE-bench Verified | — | 77.3% |
| LMArena WebDev | — | 1515 |
| SciCode | — | 48.8% |
| BigCodeBench Instruct | 37.1% | — |
| LiveBench Coding | 17.9% | — |
| BigCodeBench Complete | 45.2% | — |
| ALE-Bench | — | 1,189 |
Agentic & Tool Use Not comparable
Command R: —, Qwen3.7 Max: 22.1 (#135)
| Benchmark | Command R | Qwen3.7 Max |
|---|---|---|
| GBAEval | — | 0.4% |
Reasoning Qwen3.7 Max leads
Command R: 13.8 (#331), Qwen3.7 Max: 49.2 (#38)
| Benchmark | Command R | Qwen3.7 Max |
|---|---|---|
| LMArena Hard Prompts | 1164 | 1483 |
| DTBench | 46.4% | 92.3% |
| LMCA | 9.2% | 44% |
| SimpleBench | — | 70.4% |
| NYT Connections (extended) | — | 85.1% |
| CritPt | — | 13.4% |
| Chess Puzzles | — | 19% |
| EBR-Bench | — | 9.5% |
| LiveBench Reasoning | 21.9% | — |
| Mystery Game Puzzles | — | 32% |
| LiveBench Data Analysis | 33.3% | — |
| Epoch Capabilities Index | — | 153.68 |
| LiveBench | 27.5% | — |
Math Qwen3.7 Max leads
Command R: 28.0 (#246), Qwen3.7 Max: 62.4 (#32)
| Benchmark | Command R | Qwen3.7 Max |
|---|---|---|
| LMArena Math | 1155 | 1490 |
| FrontierMath (Tiers 1-3) | — | 64.6% |
| FrontierMath Tier 4 | — | 34.1% |
| OTIS Mock AIME 2024-2025 | — | 95.6% |
| ProofBench | — | 26% |
| LiveBench Math | 19.4% | — |
Knowledge Qwen3.7 Max leads
Command R: 31.0 (#221), Qwen3.7 Max: 61.6 (#28)
| Benchmark | Command R | Qwen3.7 Max |
|---|---|---|
| LMArena Expert | 1138 | 1488 |
| GPQA Diamond | — | 90.9% |
| SimpleQA Verified | — | 55.8% |
| MMLU | 65.2% | — |
Multilingual Qwen3.7 Max leads
Command R: 35.7 (#245), Qwen3.7 Max: 56.9 (#15)
| Benchmark | Command R | Qwen3.7 Max |
|---|---|---|
| LMArena Non-English | 1174 | 1474 |
| LMArena Chinese | 1182 | 1530 |
| LMArena Russian | 1174 | 1484 |
| LMArena French | 1162 | — |
| LMArena German | 1176 | — |
| LMArena Japanese | 1143 | — |
| LMArena Korean | 1163 | — |
| LMArena Spanish | 1151 | — |
Instruction Following Qwen3.7 Max leads
Command R: 58.1 (#261), Qwen3.7 Max: 76.7 (#38)
| Benchmark | Command R | Qwen3.7 Max |
|---|---|---|
| LMArena Instruction Following | 1167 | 1460 |
| LiveBench Instruction Following | 55.6% | — |
Long Context Qwen3.7 Max leads
Command R: 36.3 (#231), Qwen3.7 Max: 45.4 (#40)
| Benchmark | Command R | Qwen3.7 Max |
|---|---|---|
| LMArena Longer Query | 1198 | 1482 |
Writing & Preference Qwen3.7 Max leads
Command R: 38.2 (#254), Qwen3.7 Max: 65.0 (#54)
| Benchmark | Command R | Qwen3.7 Max |
|---|---|---|
| LMArena Text | 1187 | 1476 |
| LMArena Creative Writing | 1170 | 1449 |
| LMArena Multi-Turn | 1163 | 1481 |
| EQ-Bench 4 | — | 1110 |
| LiveBench Language | 16.7% | — |
Frequently asked questions
Is Command R better than Qwen3.7 Max?
Qwen3.7 Max is the stronger model overall, scoring 51.5 to 31.4 on the Noometry Index. Command R costs 14× less per token, which makes it the better buy when Qwen3.7 Max's lead doesn't matter for your workload.
Which is cheaper, Command R or Qwen3.7 Max?
Command R is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; Qwen3.7 Max lists at $2.50 and $7.50.
Is Command R or Qwen3.7 Max better for coding?
Qwen3.7 Max scores higher on coding benchmarks: 50.4 versus 29.3 in the Noometry coding category.
Which has the bigger context window?
Qwen3.7 Max does, with 1M tokens against 128K.
How many benchmarks do Command R and Qwen3.7 Max share?
14 benchmarks have published results for both models. Command R has 29 scored results on Noometry and Qwen3.7 Max has 33.