Command R vs GPT-4o mini: API Cost Comparison
Compare the API pricing, context windows, features, and real-world cost projections for Command R (Cohere) and GPT-4o mini (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
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: GPT-4o mini at $4.50/month.
| Alert | |||||||
|---|---|---|---|---|---|---|---|
BestGPT-4o mini | OpenAI | $4.50 | $0.000450 | $1.50 | $3.00 | 64.0% | Alerts coming soon |
Command R | Cohere | $12.50 | $0.001250 | $5.00 | $7.50 | — | Alerts coming soon |
Monthly Cost Comparison
Price Comparison at a Glance
All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.
| Pricing Type | Command R | GPT-4o mini | Cheaper |
|---|---|---|---|
| Input (standard) | $0.50/M | $0.15/M | GPT-4o mini |
| Output | $1.50/M | $0.60/M | GPT-4o mini |
| Cached input | N/A | $0.08/M | — |
| Batch input | N/A | $0.08/M | — |
| Batch output | N/A | $0.30/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.
| Volume | Command RMonthly | GPT-4o miniMonthly | Command RPer request | GPT-4o miniPer request |
|---|---|---|---|---|
| 1K requests/mo | $1.25 | $0.45 | $0.001250 | $0.000450 |
| 10K requests/mo | $12.50 | $4.50 | $0.001250 | $0.000450 |
| 100K requests/mo | $125.00 | $45.00 | $0.001250 | $0.000450 |
| 1M requests/mo | $1,250.00 | $450.00 | $0.001250 | $0.000450 |
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 tokensWhen 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-4o mini
by OpenAI
- Text classification
- Customer support
- Data extraction
Input / 1M tokens
$0.15/M
Output / 1M tokens
$0.60/M
Context window
128,000
Tier
budget
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.
| Capability | Command R | GPT-4o mini |
|---|---|---|
| Context window | 128,000 tokens | 128,000 tokens |
| Max output tokens | 4,096 tokens | 16,384 tokens |
| Performance tier | Mid | Budget |
| Vision / image input | No | Yes |
| Function calling | Yes | Yes |
| JSON mode | Yes | Yes |
| Prompt caching | No | Yes |
| Batch API (50% discount) | No | Yes |
| Extended reasoning | No | No |
| Fine-tuning | No | Yes |
| Rate limit (req/min) | Not published | 10,000 |
Command R notes
Good price/performance for RAG. Native tool use and multi-hop reasoning.
GPT-4o mini notes
Best cost-performance ratio for high-volume lightweight workloads.
Frequently Asked Questions
Is Command R cheaper than GPT-4o mini?
At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), GPT-4o mini costs $45.00/month versus $125.00/month for Command R — a 64% 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-4o mini?
Both Command R and GPT-4o mini have the same context window: 128,000 tokens.
Do Command R and GPT-4o mini support the Batch API?
GPT-4o mini supports the Batch API (50% discount for async processing), while Command R does not. If your workload tolerates up to 24-hour latency, routing to GPT-4o mini with batch pricing could significantly cut costs versus Command R's standard rate.
Which model offers better prompt caching?
GPT-4o mini supports prompt caching at $0.08/M for cached input, while Command R does not offer prompt caching. For RAG applications or chatbots with large, repeated context, GPT-4o mini's caching capability can substantially reduce effective costs.
What are the best use cases for Command R vs GPT-4o mini?
Both models are well-suited for Customer support. Command R is particularly strong for RAG / Semantic search, General chatbot. GPT-4o mini is favored for Text classification, Data extraction. 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-4o mini?
At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — Command R costs $0.001250 per request and GPT-4o mini costs $0.000450 per request. At 100,000 requests/month, that translates to $125.00 and $45.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.
Command R vs GPT-4o mini: Summary
When comparing Command R and GPT-4o mini for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. GPT-4o mini offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $45.00/month, compared to $125.00/month for Command R.
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-4o mini charges $0.15/M input and $0.60/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-4o mini 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: Both models support 128,000 tokens per request. 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.
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Relevant Use Cases
See cost recommendations for workloads where Command R or GPT-4o mini is recommended.