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Command R vs GPT-5.1: API Cost Comparison

Compare the API pricing, context windows, features, and real-world cost projections for Command R (Cohere) and GPT-5.1 (OpenAI). 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 ROpenAIGPT-5.1

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 80.0% vs GPT-5.1
Alert
BestCommand R
Cohere$12.50$0.001250$5.00$7.5080.0%Alerts coming soon
GPT-5.1
OpenAI$62.50$0.006250$12.50$50.00Alerts 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 RGPT-5.1Cheaper
Input (standard)$0.50/M$1.25/MCommand R
Output$1.50/M$10.00/MCommand R
Cached inputN/A$0.13/M

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 RMonthlyGPT-5.1MonthlyCommand RPer requestGPT-5.1Per request
1K requests/mo$1.25$6.25$0.001250$0.006250
10K requests/mo$12.50$62.50$0.001250$0.006250
100K requests/mo$125.00$625.00$0.001250$0.006250
1M requests/mo$1,250.00$6,250.00$0.001250$0.006250

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 GPT-5.1

by OpenAI

  • Code generation
  • Content & copywriting
  • RAG / Semantic search

Input / 1M tokens

$1.25/M

Output / 1M tokens

$10.00/M

Context window

400,000

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 RGPT-5.1
Context window128,000 tokens400,000 tokens
Max output tokens4,096 tokens128,000 tokens
Performance tierMidPremium
Vision / image inputNoYes
Function callingYesYes
JSON modeYesYes
Prompt cachingNoYes
Batch API (50% discount)NoNo
Extended reasoningNoNo
Fine-tuningNoNo
Rate limit (req/min)Not published10,000

Command R notes

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

GPT-5.1 notes

1M context window. Strong all-around performance between GPT-5.2 and GPT-5.

Frequently Asked Questions

Is Command R cheaper than GPT-5.1?

At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), Command R costs $125.00/month versus $625.00/month for GPT-5.1 — a 80% 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 GPT-5.1?

GPT-5.1 has a larger context window at 400,000 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 GPT-5.1 support the Batch API?

Neither Command R nor GPT-5.1 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?

GPT-5.1 supports prompt caching at $0.13/M for cached input, while Command R does not offer prompt caching. For RAG applications or chatbots with large, repeated context, GPT-5.1's caching capability can substantially reduce effective costs.

What are the best use cases for Command R vs GPT-5.1?

Both models are well-suited for RAG / Semantic search. Command R is particularly strong for General chatbot, Customer support. GPT-5.1 is favored for Code generation, Content & copywriting. 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 GPT-5.1?

At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — Command R costs $0.001250 per request and GPT-5.1 costs $0.006250 per request. At 100,000 requests/month, that translates to $125.00 and $625.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.

Command R vs GPT-5.1: Summary

When comparing Command R and GPT-5.1 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 $625.00/month for GPT-5.1.

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. GPT-5.1 charges $1.25/M input and $10.00/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.

Prompt caching is supported by GPT-5.1 but not Command R. For workloads with large, repeated system prompts or document context — such as RAG pipelines or multi-turn conversations with a fixed knowledge base — prompt caching can reduce effective input costs by 60–90%, which may change the cost ranking between these two models at your specific usage pattern.

Context window capacity differs between the two: GPT-5.1 supports up to 400,000 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 GPT-5.1 is recommended.