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Command R vs Kimi K2 (Groq): API Cost Comparison

Compare the API pricing, context windows, features, and real-world cost projections for Command R (Cohere) and Kimi K2 (Groq) (Groq). Use the interactive calculator below to compute your exact monthly cost based on your token usage and request volume.

Prices verified Mar 6, 2026

Interactive Cost Calculator

CohereCommand RGroqKimi K2 (Groq)

Fills in typical token counts for a workload type

Tokens in each prompt sent to the model

Tokens generated in each response

Total API calls per month

Showing costs for 2 models. Cheapest: Command R at $12.50/month.

Cheapest: Command R at $12.50/mo — save 50.0% vs Kimi K2 (Groq)
Alert
BestCommand R
Cohere$12.50$0.001250$5.00$7.5050.0%Alerts coming soon
Kimi K2 (Groq)
Groq$25.00$0.002500$10.00$15.00Alerts coming soon

Monthly Cost Comparison

Price Comparison at a Glance

All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.

Pricing TypeCommand RKimi K2 (Groq)Cheaper
Input (standard)$0.50/M$1.00/MCommand R
Output$1.50/M$3.00/MCommand R

Prices last verified: 2026-03-06

Cost Breakdown by Usage Volume

Estimated monthly costs at different request volumes, assuming 1,000 input tokens and 500 output tokens per request. Adjust in the calculator above for your specific use case.

VolumeCommand RMonthlyKimi K2 (Groq)MonthlyCommand RPer requestKimi K2 (Groq)Per request
1K requests/mo$1.25$2.50$0.001250$0.002500
10K requests/mo$12.50$25.00$0.001250$0.002500
100K requests/mo$125.00$250.00$0.001250$0.002500
1M requests/mo$1,250.00$2,500.00$0.001250$0.002500

Green values indicate the lower-cost option at each volume tier. Cost per request is calculated at 1,000 input + 500 output tokens using standard (non-batch, non-cached) pricing.

Price History

Input price per 1M tokens

When to Choose Command R

by Cohere

  • RAG / Semantic search
  • General chatbot
  • Customer support

Input / 1M tokens

$0.50/M

Output / 1M tokens

$1.50/M

Context window

128,000

Tier

mid

When to Choose Kimi K2 (Groq)

by Groq

  • Code generation
  • RAG / Semantic search

Input / 1M tokens

$1.00/M

Output / 1M tokens

$3.00/M

Context window

256,000

Tier

premium

Key Differences Beyond Price

Cost is only one factor in choosing an AI model. Context window size, rate limits, supported features, and latency all affect whether a model fits your use case.

CapabilityCommand RKimi K2 (Groq)
Context window128,000 tokens256,000 tokens
Max output tokens4,096 tokens32,768 tokens
Performance tierMidPremium
Vision / image inputNoNo
Function callingYesYes
JSON modeYesYes
Prompt cachingNoNo
Batch API (50% discount)NoNo
Extended reasoningNoNo
Fine-tuningNoNo
Rate limit (req/min)Not published30

Command R notes

Good price/performance for RAG. Native tool use and multi-hop reasoning.

Kimi K2 (Groq) notes

Moonshot AI's flagship model on Groq hardware.

Frequently Asked Questions

Is Command R cheaper than Kimi K2 (Groq)?

At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), Command R costs $125.00/month versus $250.00/month for Kimi K2 (Groq) — a 50% saving. Your actual savings will vary based on your token profile; output-heavy workloads amplify differences in output pricing.

Which model has a larger context window, Command R or Kimi K2 (Groq)?

Kimi K2 (Groq) has a larger context window at 256,000 tokens, compared to 128,000 tokens for Command R. A larger context window is important for processing long documents, multi-turn conversations, or large codebases without truncation.

Do Command R and Kimi K2 (Groq) support the Batch API?

Neither Command R nor Kimi K2 (Groq) currently supports a batch API with discounted pricing. For batch-eligible alternatives, consider models from OpenAI, Anthropic, or Google that include batch API support.

Which model offers better prompt caching?

Neither Command R nor Kimi K2 (Groq) currently supports prompt caching. For prompt-caching capable alternatives, consider Claude models from Anthropic or GPT-4o from OpenAI.

What are the best use cases for Command R vs Kimi K2 (Groq)?

Both models are well-suited for RAG / Semantic search. Command R is particularly strong for General chatbot, Customer support. Kimi K2 (Groq) is favored for Code generation. At the same quality level, the lower-cost model is usually preferable; use this page's calculator to compare total monthly spend at your volume.

What is the cost per request for Command R vs Kimi K2 (Groq)?

At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — Command R costs $0.001250 per request and Kimi K2 (Groq) costs $0.002500 per request. At 100,000 requests/month, that translates to $125.00 and $250.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.

Command R vs Kimi K2 (Groq): Summary

When comparing Command R and Kimi K2 (Groq) for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. Command R offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $125.00/month, compared to $250.00/month for Kimi K2 (Groq).

Both models are priced in USD per million tokens, the standard unit across all major AI API providers. Command R charges $0.50/M for input tokens and $1.50/M for output tokens. Kimi K2 (Groq) charges $1.00/M input and $3.00/M output. If your workload is output-heavy (more tokens generated than consumed as input), the model with the lower output price compounds cost savings significantly at scale.

Context window capacity differs between the two: Kimi K2 (Groq) supports up to 256,000 tokens in a single request, versus 128,000 tokens for Command R. A larger context window is essential for document summarization, large codebase analysis, and multi-document retrieval-augmented generation (RAG) applications.

Use the interactive calculator at the top of this page to enter your actual token usage and monthly request volume for a precise cost comparison tailored to your workload. Adjust for batch API discounts and prompt caching to find the most cost-effective option for your specific deployment.

Explore other model comparisons from the same providers or performance tiers.

Related Provider Pages

View complete pricing tables and model lineups for the providers behind these models.

Relevant Use Cases

See cost recommendations for workloads where Command R or Kimi K2 (Groq) is recommended.