Command R vs Arctic Large

Compare Command R and Arctic Large: pricing, performance, context window, latency, and best use cases. Side-by-side comparison on XALEN.

Updated 2026-05-21 · By Abhishek Raj · Our methodology

All Cohere models All Snowflake models What is an LLM API? Python Quickstart What is inference?
Feature Command R Arctic Large
CategoryOpen SourceEnterprise
Parameters35B480B (17B active)
Context Window128K128K
Input Price$0.03/1M tokens$0.06/1M tokens
Output Price$0.06/1M tokens$0.10/1M tokens
Latency~250ms~400ms

Choose Command R when:

  • ✓ RAG applications
  • ✓ Q&A systems
  • ✓ Content generation
Key Strengths:

Good RAG, Cost-efficient, 128K context

Choose Arctic Large when:

  • ✓ Data analysis
  • ✓ SQL generation
  • ✓ Business intelligence
Key Strengths:

Strong SQL, Data analysis, Enterprise features

Verdict: Command R vs Arctic Large

For cost efficiency, Command R wins at $0.03/1M input tokens. For speed, Command R is faster at ~250ms. Command R excels at RAG applications while Arctic Large is better for Data analysis. Both are available on XALEN through a single API — try them in the Playground to see which fits your workload.

Detailed Analysis

Pricing Comparison

Command R costs $0.03/1M input tokens and $0.06/1M output tokens. Arctic Large costs $0.06 input and $0.10 output. Command R is 2.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Command R has a 128K context window with ~250ms latency. Arctic Large offers 128K context at ~400ms. Both have identical context windows.

Best For

Command R (Open Source) is optimized for: RAG applications, Q&A systems, Content generation. Arctic Large (Enterprise) works best for: Data analysis, SQL generation, Business intelligence.

Try Both on XALEN

Both models are available through XALEN's OpenAI-compatible API. Switch between them by changing the model parameter:

from xalen import XALEN

client = XALEN(api_key="xln_test_YOUR_KEY")

# Use Command R
response_a = client.chat.completions.create(
    model="command-r",
    messages=[{"role": "user", "content": "Your question here"}]
)

# Use Arctic Large
response_b = client.chat.completions.create(
    model="arctic-large",
    messages=[{"role": "user", "content": "Your question here"}]
)

Start Building with XALEN

200+ AI models. One API. Pay-as-you-go.

Get API Key Try in Playground

Frequently Asked Questions

Which is better, Command R or Arctic Large?

Command R (Open Source, 35B) offers Good RAG. Arctic Large (Enterprise, 480B (17B active)) offers Strong SQL. Choose Command R for RAG applications or Arctic Large for Data analysis.

How much does Command R cost vs Arctic Large?

Command R: $0.03/1M input, $0.06/1M output. Arctic Large: $0.06/1M input, $0.10/1M output. Both available on XALEN with batch processing at 50% discount.

Can I use both models on XALEN?

Yes. XALEN provides 200+ models through a single OpenAI-compatible API. Switch between Command R and Arctic Large by changing the model parameter. No code changes needed.

Related Comparisons

Command R vs Gemma 3 27B Command R vs Llama 4 Scout Command R vs Llama 4 Maverick Command R vs Llama 3.3 70B Command R vs Llama 3.1 405B Command R vs Llama 3.1 70B Turbo

Last updated: 2026-05-21. Pricing and specifications may change. Check pricing page for latest rates.