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Command R+ vs DeepSeek-V4-Pro-0813

Comparing Command R+ and DeepSeek-V4-Pro-0813 across benchmarks, pricing, and capabilities.

Cohere · DeepSeek · Updated for 2026

Which is better?

Command R+ and DeepSeek-V4-Pro-0813 trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

On price, Command R+ is roughly 1.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

DeepSeek-V4-Pro-0813 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.

Based on current benchmark, pricing, and model metadata for 2026.

Choose Command R+

  • cost matters — it's about 1.2x cheaper per token

Choose DeepSeek-V4-Pro-0813

  • you process long inputs — it offers a 1,048,576 token context window
  • you want the most recent training data — it shipped Aug 2026

At a glance

The differences that matter most.

Benchmark wins
Input price
$0.25 / M
$0.43 / M
Output price
$1.00 / M
$0.87 / M
Context window
128,000
1,048,576
Released
Aug 2024
Aug 2026
License
CC BY-NC
MIT

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Command R+ and DeepSeek-V4-Pro-0813don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Playground indexes and blind preference scores

Pricing Analysis

Price comparison per million tokens

Command R+ costs less

For input processing, Command R+ ($0.25/1M tokens) is 1.7x cheaper than DeepSeek-V4-Pro-0813 ($0.43/1M tokens).

For output processing, Command R+ ($1.00/1M tokens) is 1.1x more expensive than DeepSeek-V4-Pro-0813 ($0.87/1M tokens).

In conclusion, DeepSeek-V4-Pro-0813 is more expensive than Command R+.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Mon Aug 24 2026 • llm-stats.com
Cohere
Command R+
Input tokens$0.25
Output tokens$1.00
Best providerCohere
DeepSeek
DeepSeek-V4-Pro-0813
Input tokens$0.43
Output tokens$0.87
Best providerDeepSeek
Notice missing or incorrect data?Start an Issue

Model Size

Parameter count comparison

1496.0B diff

DeepSeek-V4-Pro-0813 has 1496.0B more parameters than Command R+, making it 1438.5% larger.

Cohere
Command R+
104.0Bparameters
DeepSeek
DeepSeek-V4-Pro-0813
1.6Tparameters
104.0B
Command R+
1600.0B
DeepSeek-V4-Pro-0813

Context Window

Maximum input and output token capacity

DeepSeek-V4-Pro-0813 accepts 1,048,576 input tokens compared to Command R+'s 128,000 tokens. DeepSeek-V4-Pro-0813 can generate longer responses up to 393,216 tokens, while Command R+ is limited to 128,000 tokens.

Cohere
Command R+
Input128,000 tokens
Output128,000 tokens
DeepSeek
DeepSeek-V4-Pro-0813
Input1,048,576 tokens
Output393,216 tokens
Mon Aug 24 2026 • llm-stats.com

License

Usage and distribution terms

Command R+ is licensed under CC BY-NC, while DeepSeek-V4-Pro-0813 uses MIT.

License differences may affect how you can use these models in commercial or open-source projects.

Command R+

CC BY-NC

Open weights

DeepSeek-V4-Pro-0813

MIT

Open weights

Release Timeline

When each model was launched

Command R+ was released on 2024-08-30, while DeepSeek-V4-Pro-0813 was released on 2026-08-13.

DeepSeek-V4-Pro-0813 is 24 months newer than Command R+.

Command R+

Aug 30, 2024

2.0 years ago

DeepSeek-V4-Pro-0813

Aug 13, 2026

1 weeks ago

2.0yr newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

Command R+ is available from Cohere, Bedrock. DeepSeek-V4-Pro-0813 is available from DeepSeek, DeepInfra, Novita, Together.

Command R+

cohere logo
Cohere
Input Price:Input: $0.25/1MOutput Price:Output: $1.00/1M
bedrock logo
AWS Bedrock
Input Price:Input: $3.00/1MOutput Price:Output: $15.00/1M

DeepSeek-V4-Pro-0813

deepseek logo
DeepSeek
Input Price:Input: $0.43/1MOutput Price:Output: $0.87/1M
deepinfra logo
Deepinfra
Input Price:Input: $1.30/1MOutput Price:Output: $2.60/1M
novita logo
Novita
Input Price:Input: $1.32/1MOutput Price:Output: $3.96/1M
together logo
Together
Input Price:Input: $1.32/1MOutput Price:Output: $3.96/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against Command R+ and DeepSeek-V4-Pro-0813 side-by-side, then vote on the output you prefer.

Command R+
✓ Preferred
DeepSeek-V4-Pro-0813
Open in Playground

FAQ

Common questions about Command R+ vs DeepSeek-V4-Pro-0813.

Which is better, Command R+ or DeepSeek-V4-Pro-0813?

Command R+ (Cohere) and DeepSeek-V4-Pro-0813 (DeepSeek) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does Command R+ compare to DeepSeek-V4-Pro-0813 in benchmarks?

Command R+ scores HellaSwag: 88.6%, Winogrande: 85.4%, MMLU: 75.7%, ARC-C: 71.0%, GSM8k: 70.7%. DeepSeek-V4-Pro-0813 scores Terminal-Bench 2.1: 87.9%, CyberGym: 83.3%, Toolathlon: 74.1%, DSBench-FullStack: 71.1%, DSBench-Hard: 67.2%.

Is Command R+ cheaper than DeepSeek-V4-Pro-0813?

Command R+ is 1.7x cheaper for input tokens. Command R+ costs $0.25/M input and $1.00/M output via cohere. DeepSeek-V4-Pro-0813 costs $0.43/M input and $0.87/M output via deepseek.

What are the context window sizes for Command R+ and DeepSeek-V4-Pro-0813?

Command R+ supports 128K tokens and DeepSeek-V4-Pro-0813 supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Command R+ and DeepSeek-V4-Pro-0813?

Key differences include context window (128K vs 1.0M), input pricing ($0.25 vs $0.43/M), licensing (CC BY-NC vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes Command R+ and DeepSeek-V4-Pro-0813?

Command R+ is developed by Cohere and DeepSeek-V4-Pro-0813 is developed by DeepSeek.