Model comparison
Command A vs DeepSeek-V3.1-Terminus
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 36.5 on the Noometry Index.
Last verified . 13 shared benchmarks.
Cohere
DeepSeekSummary
- They share 13 benchmarks with published results for both. Command A scores higher in 0 categories and DeepSeek-V3.1-Terminus in 7 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in coding, where DeepSeek-V3.1-Terminus leads 42.0 to 27.2.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 28.8% for Command A and 57.4% for DeepSeek-V3.1-Terminus.
- DeepSeek-V3.1-Terminus is cheaper at $0.27 / $1 per million input/output tokens, against $2.50 / $10 for Command A.
- Command A accepts more context: 256K tokens versus 164K.
Side by side
| Command A | DeepSeek-V3.1-Terminus | |
|---|---|---|
| Provider | Cohere | DeepSeek |
| Noometry Index | 36.5 | 43.1 |
| Released | 2025-03-13 | 2025-09-22 |
| Weights | Open | Open |
| Context window | 256K | 164K |
| Max output | 8K | 147K |
| Input $ / M tokens | $2.50 | $0.27 |
| Output $ / M tokens | $10 | $1 |
| Results tracked | 24 | 16 |
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Category by category
Coding DeepSeek-V3.1-Terminus leads
Command A: 27.2 (#322), DeepSeek-V3.1-Terminus: 42.0 (#113)
| Benchmark | Command A | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Coding | 1330 | 1426 |
| Aider Polyglot | 12% | — |
| SciCode | — | 40.6% |
| ALE-Bench | — | 745.17 |
Agentic & Tool Use Not comparable
Command A: 35.9 (#40), DeepSeek-V3.1-Terminus: —
| Benchmark | Command A | DeepSeek-V3.1-Terminus |
|---|---|---|
| Berkeley Function Calling Leaderboard | 57.1% | — |
Reasoning DeepSeek-V3.1-Terminus leads
Command A: 18.3 (#283), DeepSeek-V3.1-Terminus: 26.4 (#133)
| Benchmark | Command A | DeepSeek-V3.1-Terminus |
|---|---|---|
| Kagi LLM Benchmark | 28.8% | 57.4% |
| LMArena Hard Prompts | 1326 | 1426 |
| DTBench | 61.3% | 81.3% |
| LMCA | 10.3% | 28.6% |
| CritPt | — | 1.7% |
Math DeepSeek-V3.1-Terminus leads
Command A: 36.2 (#171), DeepSeek-V3.1-Terminus: 38.5 (#137)
| Benchmark | Command A | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Math | 1300 | 1402 |
Knowledge Not comparable
Command A: 37.1 (#159), DeepSeek-V3.1-Terminus: —
| Benchmark | Command A | DeepSeek-V3.1-Terminus |
|---|---|---|
| Vectara Hallucination Rate | 9.3% | — |
| LMArena Expert | 1295 | — |
Multilingual DeepSeek-V3.1-Terminus leads
Command A: 45.3 (#170), DeepSeek-V3.1-Terminus: 52.1 (#92)
| Benchmark | Command A | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Non-English | 1313 | 1407 |
| LMArena Russian | 1314 | 1436 |
| LMArena Chinese | 1327 | — |
| LMArena French | 1351 | — |
| LMArena German | 1341 | — |
| LMArena Japanese | 1285 | — |
| LMArena Korean | 1285 | — |
| LMArena Spanish | 1347 | — |
Instruction Following DeepSeek-V3.1-Terminus leads
Command A: 69.1 (#177), DeepSeek-V3.1-Terminus: 74.0 (#106)
| Benchmark | Command A | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Instruction Following | 1309 | 1404 |
Long Context DeepSeek-V3.1-Terminus leads
Command A: 40.6 (#151), DeepSeek-V3.1-Terminus: 43.4 (#97)
| Benchmark | Command A | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Longer Query | 1334 | 1421 |
Writing & Preference DeepSeek-V3.1-Terminus leads
Command A: 47.6 (#208), DeepSeek-V3.1-Terminus: 61.0 (#92)
| Benchmark | Command A | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Text | 1331 | 1419 |
| LMArena Creative Writing | 1319 | 1403 |
| LMArena Multi-Turn | 1339 | 1411 |
| EQ-Bench Creative Writing | 1145 | — |
Frequently asked questions
Is Command A better than DeepSeek-V3.1-Terminus?
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 36.5 on the Noometry Index.
Which is cheaper, Command A or DeepSeek-V3.1-Terminus?
DeepSeek-V3.1-Terminus is cheaper. It lists at $0.27 per million input tokens and $1 per million output tokens; Command A lists at $2.50 and $10.
Is Command A or DeepSeek-V3.1-Terminus better for coding?
DeepSeek-V3.1-Terminus scores higher on coding benchmarks: 42.0 versus 27.2 in the Noometry coding category.
Which has the bigger context window?
Command A does, with 256K tokens against 164K.
How many benchmarks do Command A and DeepSeek-V3.1-Terminus share?
13 benchmarks have published results for both models. Command A has 24 scored results on Noometry and DeepSeek-V3.1-Terminus has 16.