Compare

Command A Plus 05 2026 vs R1

This page is context-first: how much text each model can take in one request. Full specs adds capabilities and limits; the pricing matrix below is only about $/million tokens from hosts that list both models.

Cohere

Model

Command A Plus 05 2026

Image inputTool calling

Context window

128K

128,000 tokens · ~96K words

Model page
Deepseek

Model

R1

Tool calling

Context window

128K

128,000 tokens · ~96K words

Model page

Context window · side by side

Bar length is relative to the larger of the two windows (100% = max of this pair). This is not pricing.

Command A Plus 05 2026128K
R1128K

Same context window size for both models.

Command A Plus 05 2026 and R1 have identical context windows (128K tokens).

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long output (reports, code files)

    Use Command A Plus 05 2026. Its 64K max output lets you generate complete artifacts in one request.

Full specs

Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.

SpecCommand A Plus 05 2026R1
Context window128,000 tokens (128K)128,000 tokens (128K)
Max output tokens64,000 tokens (64K)8,192 tokens (8K)
Speed tierBalancedDeep
VisionYesNo
Function callingYesYes
Extended thinkingYesYes
Prompt cachingNoYes
Batch APINoNo
Release dateN/AJan 2025

Pricing matrix

Dollar rates only: hosts that list both models, per 1M tokens. For how much text fits, use the context section above — not this table.

ProviderCommand A Plus 05 2026 inCommand A Plus 05 2026 outR1 inR1 out
Aws Bedrock$1.35/M$5.40/M
Azure$1.35/M$5.40/M
Cohere
Deepinfra$0.700/M$2.40/M
Deepseek$0.550/M$2.19/M
Fireworks$3.00/M$8.00/M
Hyperbolic$0.400/M$0.400/M
Nebius$0.800/M$2.40/M
Novita$0.700/M$2.50/M
Openrouter$0.700/M$2.50/M
Replicate$3.75/M$10.00/M
Sambanova$5.00/M$7.00/M
Snowflake$1.35/M$5.40/M
Together Ai$3.00/M$7.00/M

Frequently asked questions

R1 has a larger context window: 128K tokens vs 128K. For long documents, large codebases, or extended agent sessions, the larger context window reduces the need to chunk inputs or summarize history.

Powered by Mem0

Use a smaller model.
Get better results.

Mem0 gives your AI long-term memory so you stop re-sending context on every call. That means you can use a smaller, faster, cheaper model — and still get better answers.

Example: a multi-turn chat session

Without Mem0~128K tokens sent
Full history
Repeated info
Old context
With Mem0~20K tokens sent
Key memories
Current turn

80% less to send — works with any model