Remova Logo
Quick Profile

Command R (08-2024)

Command R (08-2024) is a cost-efficient model with standard context support, suited to code retrieval and repository search for enterprise teams.

Try Command R (08-2024) with your team

Last reviewed: 2026-09-02

Command R (08-2024)

Cohere

Stable
Context Window
128,000
Input / 1M
$0.23
Output / 1M
$0.90

What can you do with Command R (08-2024)?

Practical ways teams can use Command R (08-2024) inside governed AI workflows.

01

Search codebases with Command R (08-2024)

Embed repositories, snippets, and technical docs so developers can find relevant implementation context with Command R (08-2024).

02

Power coding assistants with Command R (08-2024)

Retrieve related files, APIs, examples, and dependency context for governed developer workflows with Command R (08-2024).

03

Index repositories with Command R (08-2024)

Create searchable vectors for source files, documentation, issues, and engineering knowledge bases with Command R (08-2024).

04

Deduplicate code knowledge with Command R (08-2024)

Cluster similar snippets, docs, tickets, and examples for cleaner engineering support systems with Command R (08-2024).

05

Rank technical evidence with Command R (08-2024)

Surface relevant code, logs, docs, and tickets during incident and compliance reviews with Command R (08-2024).

06

Measure code similarity with Command R (08-2024)

Compare snippets, repositories, and technical records for recommendations or migration planning with Command R (08-2024).

Why this model

Command R (08-2024) is available in Remova as a standard context option with $0.23 per 1M tokens input pricing, $0.90 per 1M tokens output pricing, and text input to text output support.

  • Command R (08-2024) offers standard context capacity for enterprise prompts and documents.
  • Current Remova pricing band is cost-efficient: $0.23 per 1M tokens input and $0.90 per 1M tokens output.
  • Best-fit workloads include: Code retrieval, Repository search, Coding assistant retrieval.
  • Keep role-based access in place before broad rollout.

At a glance

Model ID
cohere/command-r-08-2024
Context Window
128,000 tokens
Modality
Text input to text output
Input Modalities
Text
Output Modalities
Text
Input Price
$0.23 per 1M tokens
Output Price
$0.90 per 1M tokens
Provider
Cohere
Listing Date
2024-08-30

Strengths

  • Command R (08-2024) is suited for code retrieval.
  • Supports standard context for multi-step prompts and larger working sets.
  • Pricing profile is cost-efficient, enabling predictable workload routing decisions.
  • Can be paired with policy guardrails for safer deployment at scale.

Tradeoffs

  • Policy exceptions should be monitored and reviewed on a fixed cadence.
  • Standard context limits may require chunking or retrieval strategies for large documents.
  • Low-cost tiers can still underperform on high-consequence decisions without escalation paths.
  • Code retrieval systems need repository access controls, freshness checks, and relevance benchmarks.

Best for

  • Command R (08-2024) for codebase retrieval across repositories, docs, issues, and technical records.
  • Command R (08-2024) for repository search with access controls and relevance benchmarks.
  • Command R (08-2024) for grounding coding assistants in approved repository context.
  • Command R (08-2024) for surfacing relevant code, logs, and tickets during engineering reviews.

Rollout checklist

  • Define where Command R (08-2024) is default vs. fallback in your routing policy.
  • Enable role-based access and policy checks before opening access broadly.
  • Set spend guardrails by team and monitor weekly token consumption.
  • Start with one workflow, then expand after you verify quality and spend.
  • Re-run quality and cost benchmarks monthly as newer releases appear.

Related models

Explore adjacent model profiles for routing and benchmarking decisions.

Free Resource

Where Should Your Team Start with AI?

Tell us your industry and team size. We'll tell you which AI use cases will save the most time with the least setup.

You get

A shortlist of AI use cases ranked by impact and effort for your situation.

Tuning notes

frequency_penalty

Tune repetition control for long responses in multi-step workflows.

max_tokens

Set completion limits to avoid unpredictable long-output spend.

presence_penalty

Use carefully when expanding idea diversity in exploration-heavy prompts.

response_format

Prefer structured output where responses feed internal systems.

Free Assessment

What Could Go Wrong?

5 questions about how your company uses AI today. We'll show you the risks most companies miss until it's too late.

You get

A risk breakdown with the 3 things you should fix first.

Book demo
Knowledge Hub

Command R (08-2024) FAQs

Choose Command R (08-2024) when the workload aligns with code retrieval, repository search, coding assistant retrieval and quality targets justify its pricing profile.
It depends on workload mix. Most organizations use routing policies so routine traffic stays on lower-cost tiers.
Validate quality on real internal prompts, token efficiency, latency, and policy compliance behavior.

Deploy This Model With Governance

Use policy controls, role-based access, and budget guardrails before enabling advanced model tiers at scale.

Try Command R (08-2024) with your team