Model comparison
Command R vs DeepSeek-V3.1-Terminus
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 31.4 on the Noometry Index. Command R costs 1.7× less per token, which makes it the better buy when DeepSeek-V3.1-Terminus's lead doesn't matter for your workload.
Last verified . 12 shared benchmarks.
Cohere
DeepSeekSummary
- They share 12 benchmarks with published results for both. Command R 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 writing & preference, where DeepSeek-V3.1-Terminus leads 61.0 to 38.2.
- The biggest single-benchmark swing is DTBench: 46.4% for Command R and 81.3% for DeepSeek-V3.1-Terminus.
- Command R is cheaper at $0.15 / $0.60 per million input/output tokens, against $0.27 / $1 for DeepSeek-V3.1-Terminus.
- DeepSeek-V3.1-Terminus accepts more context: 164K tokens versus 128K.
Side by side
| Command R | DeepSeek-V3.1-Terminus | |
|---|---|---|
| Provider | Cohere | DeepSeek |
| Noometry Index | 31.4 | 43.1 |
| Released | 2024-08-30 | 2025-09-22 |
| Weights | Open | Open |
| Context window | 128K | 164K |
| Max output | 4K | 147K |
| Input $ / M tokens | $0.15 | $0.27 |
| Output $ / M tokens | $0.60 | $1 |
| Results tracked | 29 | 16 |
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Category by category
Coding DeepSeek-V3.1-Terminus leads
Command R: 29.3 (#306), DeepSeek-V3.1-Terminus: 42.0 (#113)
| Benchmark | Command R | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Coding | 1169 | 1426 |
| SciCode | — | 40.6% |
| BigCodeBench Instruct | 37.1% | — |
| LiveBench Coding | 17.9% | — |
| BigCodeBench Complete | 45.2% | — |
| ALE-Bench | — | 745.17 |
Reasoning DeepSeek-V3.1-Terminus leads
Command R: 13.8 (#331), DeepSeek-V3.1-Terminus: 26.4 (#133)
| Benchmark | Command R | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Hard Prompts | 1164 | 1426 |
| DTBench | 46.4% | 81.3% |
| LMCA | 9.2% | 28.6% |
| Kagi LLM Benchmark | — | 57.4% |
| CritPt | — | 1.7% |
| LiveBench Reasoning | 21.9% | — |
| LiveBench Data Analysis | 33.3% | — |
| LiveBench | 27.5% | — |
Math DeepSeek-V3.1-Terminus leads
Command R: 28.0 (#246), DeepSeek-V3.1-Terminus: 38.5 (#137)
| Benchmark | Command R | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Math | 1155 | 1402 |
| LiveBench Math | 19.4% | — |
Knowledge Not comparable
Command R: 31.0 (#221), DeepSeek-V3.1-Terminus: —
| Benchmark | Command R | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Expert | 1138 | — |
| MMLU | 65.2% | — |
Multilingual DeepSeek-V3.1-Terminus leads
Command R: 35.7 (#245), DeepSeek-V3.1-Terminus: 52.1 (#92)
| Benchmark | Command R | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Non-English | 1174 | 1407 |
| LMArena Russian | 1174 | 1436 |
| LMArena Chinese | 1182 | — |
| LMArena French | 1162 | — |
| LMArena German | 1176 | — |
| LMArena Japanese | 1143 | — |
| LMArena Korean | 1163 | — |
| LMArena Spanish | 1151 | — |
Instruction Following DeepSeek-V3.1-Terminus leads
Command R: 58.1 (#261), DeepSeek-V3.1-Terminus: 74.0 (#106)
| Benchmark | Command R | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Instruction Following | 1167 | 1404 |
| LiveBench Instruction Following | 55.6% | — |
Long Context DeepSeek-V3.1-Terminus leads
Command R: 36.3 (#231), DeepSeek-V3.1-Terminus: 43.4 (#97)
| Benchmark | Command R | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Longer Query | 1198 | 1421 |
Writing & Preference DeepSeek-V3.1-Terminus leads
Command R: 38.2 (#254), DeepSeek-V3.1-Terminus: 61.0 (#92)
| Benchmark | Command R | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Text | 1187 | 1419 |
| LMArena Creative Writing | 1170 | 1403 |
| LMArena Multi-Turn | 1163 | 1411 |
| LiveBench Language | 16.7% | — |
Frequently asked questions
Is Command R better than DeepSeek-V3.1-Terminus?
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 31.4 on the Noometry Index. Command R costs 1.7× less per token, which makes it the better buy when DeepSeek-V3.1-Terminus's lead doesn't matter for your workload.
Which is cheaper, Command R or DeepSeek-V3.1-Terminus?
Command R is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; DeepSeek-V3.1-Terminus lists at $0.27 and $1.
Is Command R or DeepSeek-V3.1-Terminus better for coding?
DeepSeek-V3.1-Terminus scores higher on coding benchmarks: 42.0 versus 29.3 in the Noometry coding category.
Which has the bigger context window?
DeepSeek-V3.1-Terminus does, with 164K tokens against 128K.
How many benchmarks do Command R and DeepSeek-V3.1-Terminus share?
12 benchmarks have published results for both models. Command R has 29 scored results on Noometry and DeepSeek-V3.1-Terminus has 16.