Model comparison
Command A vs Qwen1.5-14B
Command A is the stronger model overall, scoring 36.5 to 32.7 on the Noometry Index.
Last verified . 16 shared benchmarks.
Cohere
Alibaba (Qwen)Summary
- They share 16 benchmarks with published results for both. Command A scores higher in 6 categories and Qwen1.5-14B in 2 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in multilingual, where Command A leads 45.3 to 30.7.
Side by side
| Command A | Qwen1.5-14B | |
|---|---|---|
| Provider | Cohere | Alibaba (Qwen) |
| Noometry Index | 36.5 | 32.7 |
| Released | 2025-03-13 | 2024-02-04 |
| Weights | Open | Open |
| Context window | 256K | — |
| Max output | 8K | — |
| Input $ / M tokens | $2.50 | — |
| Output $ / M tokens | $10 | — |
| Results tracked | 24 | 17 |
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Category by category
Coding Qwen1.5-14B leads
Command A: 27.2 (#322), Qwen1.5-14B: 33.1 (#263)
| Benchmark | Command A | Qwen1.5-14B |
|---|---|---|
| LMArena Coding | 1330 | 1138 |
| Aider Polyglot | 12% | — |
Agentic & Tool Use Not comparable
Command A: 35.9 (#40), Qwen1.5-14B: —
| Benchmark | Command A | Qwen1.5-14B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 57.1% | — |
Reasoning Qwen1.5-14B leads
Command A: 18.3 (#283), Qwen1.5-14B: 21.4 (#223)
| Benchmark | Command A | Qwen1.5-14B |
|---|---|---|
| LMArena Hard Prompts | 1326 | 1113 |
| Kagi LLM Benchmark | 28.8% | — |
| DTBench | 61.3% | — |
| LMCA | 10.3% | — |
Math Command A leads
Command A: 36.2 (#171), Qwen1.5-14B: 32.4 (#215)
| Benchmark | Command A | Qwen1.5-14B |
|---|---|---|
| LMArena Math | 1300 | 1125 |
Knowledge Command A leads
Command A: 37.1 (#159), Qwen1.5-14B: 29.8 (#232)
| Benchmark | Command A | Qwen1.5-14B |
|---|---|---|
| LMArena Expert | 1295 | 1094 |
| Vectara Hallucination Rate | 9.3% | — |
| MMLU | — | 68.6% |
Multilingual Command A leads
Command A: 45.3 (#170), Qwen1.5-14B: 30.7 (#262)
| Benchmark | Command A | Qwen1.5-14B |
|---|---|---|
| LMArena Non-English | 1313 | 1095 |
| LMArena Chinese | 1327 | 1147 |
| LMArena French | 1351 | 1116 |
| LMArena German | 1341 | 1043 |
| LMArena Japanese | 1285 | 1019 |
| LMArena Russian | 1314 | 1046 |
| LMArena Spanish | 1347 | 1085 |
| LMArena Korean | 1285 | — |
Instruction Following Command A leads
Command A: 69.1 (#177), Qwen1.5-14B: 56.8 (#271)
| Benchmark | Command A | Qwen1.5-14B |
|---|---|---|
| LMArena Instruction Following | 1309 | 1102 |
Long Context Command A leads
Command A: 40.6 (#151), Qwen1.5-14B: 33.7 (#257)
| Benchmark | Command A | Qwen1.5-14B |
|---|---|---|
| LMArena Longer Query | 1334 | 1113 |
Writing & Preference Command A leads
Command A: 47.6 (#208), Qwen1.5-14B: 33.6 (#276)
| Benchmark | Command A | Qwen1.5-14B |
|---|---|---|
| LMArena Text | 1331 | 1128 |
| LMArena Creative Writing | 1319 | 1091 |
| LMArena Multi-Turn | 1339 | 1110 |
| EQ-Bench Creative Writing | 1145 | — |
Frequently asked questions
Is Command A better than Qwen1.5-14B?
Command A is the stronger model overall, scoring 36.5 to 32.7 on the Noometry Index.
Is Command A or Qwen1.5-14B better for coding?
Qwen1.5-14B scores higher on coding benchmarks: 33.1 versus 27.2 in the Noometry coding category.
How many benchmarks do Command A and Qwen1.5-14B share?
16 benchmarks have published results for both models. Command A has 24 scored results on Noometry and Qwen1.5-14B has 17.