Model comparison
Command A vs DeepSeek-R1-Distill-Qwen-1.5B
Command A is the stronger model overall, scoring 35.9 to 25.7 on the Noometry Index.
Last verified . 0 shared benchmarks.
Cohere
DeepSeekSummary
- The widest gap is in knowledge, where Command A leads 36.5 to 16.0.
Side by side
| Command A | DeepSeek-R1-Distill-Qwen-1.5B | |
|---|---|---|
| Provider | Cohere | DeepSeek |
| Noometry Index | 35.9 | 25.7 |
| Released | 2025-03-13 | 2025-01-20 |
| Weights | Open | Open |
| Context window | 256K | — |
| Max output | 8K | — |
| Input $ / M tokens | $2.50 | — |
| Output $ / M tokens | $10 | — |
| Results tracked | 24 | 5 |
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Category by category
Coding Command A leads
Command A: 26.8 (#317), DeepSeek-R1-Distill-Qwen-1.5B: 21.4 (#331)
| Benchmark | Command A | DeepSeek-R1-Distill-Qwen-1.5B |
|---|---|---|
| Aider Polyglot | 12% | — |
| BigCodeBench Instruct | — | 7% |
| LMArena Coding | 1331 | — |
| BigCodeBench Complete | — | 7.9% |
Agentic & Tool Use Not comparable
Command A: 35.7 (#36), DeepSeek-R1-Distill-Qwen-1.5B: —
| Benchmark | Command A | DeepSeek-R1-Distill-Qwen-1.5B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 57.1% | — |
Reasoning Too close to call
Command A: 17.7 (#276), DeepSeek-R1-Distill-Qwen-1.5B: 18.5 (#258)
| Benchmark | Command A | DeepSeek-R1-Distill-Qwen-1.5B |
|---|---|---|
| Kagi LLM Benchmark | 28.8% | — |
| Chess Puzzles | — | 0% |
| LMArena Hard Prompts | 1326 | — |
| DTBench | 61.3% | — |
| LMCA | 10.3% | — |
Math Command A leads
Command A: 33.5 (#172), DeepSeek-R1-Distill-Qwen-1.5B: 21.8 (#268)
| Benchmark | Command A | DeepSeek-R1-Distill-Qwen-1.5B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 21.4% |
| LMArena Math | 1300 | — |
Knowledge Command A leads
Command A: 36.5 (#157), DeepSeek-R1-Distill-Qwen-1.5B: 16.0 (#284)
| Benchmark | Command A | DeepSeek-R1-Distill-Qwen-1.5B |
|---|---|---|
| GPQA Diamond | — | 33.6% |
| Vectara Hallucination Rate | 9.3% | — |
| LMArena Expert | 1295 | — |
Multilingual Not comparable
Command A: 45.5 (#166), DeepSeek-R1-Distill-Qwen-1.5B: —
| Benchmark | Command A | DeepSeek-R1-Distill-Qwen-1.5B |
|---|---|---|
| LMArena Non-English | 1313 | — |
| LMArena Chinese | 1327 | — |
| LMArena French | 1352 | — |
| LMArena German | 1341 | — |
| LMArena Japanese | 1283 | — |
| LMArena Korean | 1285 | — |
| LMArena Russian | 1314 | — |
| LMArena Spanish | 1346 | — |
Instruction Following Not comparable
Command A: 69.3 (#172), DeepSeek-R1-Distill-Qwen-1.5B: —
| Benchmark | Command A | DeepSeek-R1-Distill-Qwen-1.5B |
|---|---|---|
| LMArena Instruction Following | 1309 | — |
Long Context Not comparable
Command A: 40.6 (#147), DeepSeek-R1-Distill-Qwen-1.5B: —
| Benchmark | Command A | DeepSeek-R1-Distill-Qwen-1.5B |
|---|---|---|
| LMArena Longer Query | 1334 | — |
Writing & Preference Not comparable
Command A: 47.8 (#204), DeepSeek-R1-Distill-Qwen-1.5B: —
| Benchmark | Command A | DeepSeek-R1-Distill-Qwen-1.5B |
|---|---|---|
| LMArena Text | 1331 | — |
| LMArena Creative Writing | 1319 | — |
| EQ-Bench Creative Writing | 1145 | — |
| LMArena Multi-Turn | 1338 | — |
Frequently asked questions
Is Command A better than DeepSeek-R1-Distill-Qwen-1.5B?
Command A is the stronger model overall, scoring 35.9 to 25.7 on the Noometry Index.
Is Command A or DeepSeek-R1-Distill-Qwen-1.5B better for coding?
Command A scores higher on coding benchmarks: 26.8 versus 21.4 in the Noometry coding category.
How many benchmarks do Command A and DeepSeek-R1-Distill-Qwen-1.5B share?
0 benchmarks have published results for both models. Command A has 24 scored results on Noometry and DeepSeek-R1-Distill-Qwen-1.5B has 5.