Noometry

Model comparison

Command R+ vs DeepSeek-V3.1

DeepSeek-V3.1 is the stronger model overall, scoring 42.8 to 32.4 on the Noometry Index.

Last verified . 22 shared benchmarks.

Command R+ Cohere

32.4

Rank #257 Confirmed

DeepSeek-V3.1 DeepSeek

42.8

Rank #108 Confirmed

Summary

  • They share 22 benchmarks with published results for both. Command R+ scores higher in 1 category and DeepSeek-V3.1 in 7 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where DeepSeek-V3.1 leads 27.9 to 9.2.
  • The biggest single-benchmark swing is DTBench: 54.9% for Command R+ and 82.7% for DeepSeek-V3.1.
  • DeepSeek-V3.1 is cheaper at $0.25 / $0.95 per million input/output tokens, against $2.50 / $10 for Command R+.
  • DeepSeek-V3.1 accepts more context: 164K tokens versus 128K.

Side by side

Command R+DeepSeek-V3.1
ProviderCohereDeepSeek
Noometry Index32.442.8
Released2024-08-302025-08-21
WeightsOpenOpen
Context window128K164K
Max output4K8K
Input $ / M tokens$2.50$0.25
Output $ / M tokens$10$0.95
Results tracked3427

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Category by category

Coding DeepSeek-V3.1 leads

Command R+: 29.1 (#309), DeepSeek-V3.1: 40.3 (#144)

BenchmarkCommand R+DeepSeek-V3.1
LMArena Coding11871417
WeirdML—38.4%
BigCodeBench Instruct33.8%—
LiveBench Coding19.1%—
BigCodeBench Complete41.9%—
HumanEval+56.7%—
MBPP+63.5%—

Reasoning DeepSeek-V3.1 leads

Command R+: 9.2 (#344), DeepSeek-V3.1: 27.9 (#110)

BenchmarkCommand R+DeepSeek-V3.1
SimpleBench17.4%40%
LMArena Hard Prompts11861417
DTBench54.9%82.7%
LMCA5%24.3%
Epoch Capabilities Index119.34139.92
Kagi LLM Benchmark—53.2%
LiveBench Reasoning24.8%—
LiveBench Data Analysis38.1%—
ForecastBench—58
LiveBench31.8%—

Math DeepSeek-V3.1 leads

Command R+: 28.9 (#242), DeepSeek-V3.1: 38.9 (#122)

BenchmarkCommand R+DeepSeek-V3.1
LMArena Math11881420
LiveBench Math21.3%—

Knowledge DeepSeek-V3.1 leads

Command R+: 36.4 (#169), DeepSeek-V3.1: 43.7 (#90)

BenchmarkCommand R+DeepSeek-V3.1
Vectara Hallucination Rate6.9%5.5%
LMArena Expert11741405
MMLU69.4%—

Multilingual DeepSeek-V3.1 leads

Command R+: 38.6 (#227), DeepSeek-V3.1: 51.6 (#106)

BenchmarkCommand R+DeepSeek-V3.1
LMArena Non-English12161400
LMArena Chinese12261469
LMArena French12091447
LMArena German12161411
LMArena Japanese11661378
LMArena Korean11381337
LMArena Russian12271405
LMArena Spanish11891431

Instruction Following DeepSeek-V3.1 leads

Command R+: 60.0 (#254), DeepSeek-V3.1: 73.9 (#110)

BenchmarkCommand R+DeepSeek-V3.1
LMArena Instruction Following11971400
LiveBench Instruction Following57.6%—

Long Context Command R+ leads

Command R+: 37.3 (#219), DeepSeek-V3.1: 36.3 (#232)

BenchmarkCommand R+DeepSeek-V3.1
LMArena Longer Query12301422
Fiction.LiveBench—52.8%

Writing & Preference DeepSeek-V3.1 leads

Command R+: 43.5 (#228), DeepSeek-V3.1: 60.3 (#98)

BenchmarkCommand R+DeepSeek-V3.1
LMArena Text12291420
LMArena Creative Writing12351401
LMArena Multi-Turn12131408
EQ-Bench Creative Writing—1436
LiveBench Language29.7%—

Frequently asked questions

Is Command R+ better than DeepSeek-V3.1?

DeepSeek-V3.1 is the stronger model overall, scoring 42.8 to 32.4 on the Noometry Index.

Which is cheaper, Command R+ or DeepSeek-V3.1?

DeepSeek-V3.1 is cheaper. It lists at $0.25 per million input tokens and $0.95 per million output tokens; Command R+ lists at $2.50 and $10.

Is Command R+ or DeepSeek-V3.1 better for coding?

DeepSeek-V3.1 scores higher on coding benchmarks: 40.3 versus 29.1 in the Noometry coding category.

Which has the bigger context window?

DeepSeek-V3.1 does, with 164K tokens against 128K.

How many benchmarks do Command R+ and DeepSeek-V3.1 share?

22 benchmarks have published results for both models. Command R+ has 34 scored results on Noometry and DeepSeek-V3.1 has 27.

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