GPT-4o-mini
OpenAI • text+image+file->text
Context Window128K
Knowledge CutoffJul 18, 2024
GPT-4o-mini vs Command R (08-2024)
Command R for retrieval-augmented enterprise workflows, GPT-4o mini for general-purpose low-cost API access.
Open model page
Command R (08-2024)
Cohere • text->text
Context Window128K
Knowledge CutoffAug 30, 2024
Editorial Verdict
GPT-4o mini is the general-purpose winner; Command R is purpose-built for RAG systems.
GPT-4o mini outperforms Command R on capability benchmarks while Command R has a unique strength in retrieval-augmented generation (RAG) workflows. For pure capability per dollar, GPT-4o mini wins. For teams building RAG-heavy applications with enterprise requirements, Command R is purpose-built for that workload.
GPT-4o-mini
- Significantly higher general reasoning and coding benchmark scores
- 128K context window — 4x larger than Command R's 32K
- More versatile for non-RAG use cases including agents and tool use
Best for: General-purpose, reasoning, and coding tasks at efficient cost
Command R (08-2024)
- Purpose-built for RAG with native citation generation and source attribution
- Strong multilingual performance across 50+ languages
- Competitive pricing for enterprise RAG applications
Best for: RAG applications, enterprise knowledge bases, and multilingual retrieval workloads
Pricing sourced from OpenRouter — updates as their catalog changes.
Pricing Comparison
All values pull from OpenRouter and update as their catalog changes.
| Metric | GPT-4o-mini | Command R (08-2024) | Winner |
|---|---|---|---|
| Input (per 1M tokens) | $0.15 | $0.15 | Tie |
| Output (per 1M tokens) | $0.60 | $0.60 | Tie |
| Request fee | N/A | N/A | N/A |
| Image fee | N/A | N/A | N/A |
Cost Estimator
Estimate monthly billing using real OpenRouter prices.
GPT-4o-mini Total
$14.25Command R (08-2024) Total
$14.25Estimated Monthly Savings: Tie
Capability Signals
Scores are directional estimates from model metadata — not official benchmark results.
GPT-4o-miniMMLU Signal (Reasoning)Command R (08-2024)
69%
76%
GPT-4o-miniHumanEval Signal (Coding)Command R (08-2024)
76%
86%
GPT-4o-miniAgentic Tooling SignalCommand R (08-2024)
84%
84%
GPT-4o-miniMultimodal SignalCommand R (08-2024)
78%
69%
Capabilities Matrix
Feature highlights for architecture and production fit.
GPT-4o-mini Strengths
- Supports image inputs for multimodal analysis workflows.
- Strong tool-calling and structured response support.
- Balanced general-purpose profile for chat, extraction, and automation tasks.
Command R (08-2024) Strengths
- Strong tool-calling and structured response support.
- High coding signal for production assistant use cases.
- Balanced general-purpose profile for chat, extraction, and automation tasks.
API Implementation
Quick start snippets for each provider style.
OpenAI (Python)
from openai import OpenAI
client = OpenAI()
response = client.chat.completions.create(
model="openai/gpt-4o-mini",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Cohere (Python)
from openai import OpenAI
client = OpenAI()
response = client.chat.completions.create(
model="cohere/command-r-08-2024",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Choose GPT-4o-mini when...
- Your application includes visual reasoning and image understanding tasks.
- You rely on function calling, tool chaining, and structured output contracts.
- You want a balanced default for mixed chat and workflow automation workloads.
Choose Command R (08-2024) when...
- You rely on function calling, tool chaining, and structured output contracts.
- You want a balanced default for mixed chat and workflow automation workloads.
- You can measure quality with your own benchmark and prompt set.
Frequently Asked Questions
Practical checks before selecting a production model.
Is GPT-4o mini better than Command R?
It depends on the workload. GPT-4o mini and Command R differ in pricing, context window, and capability mix — see the side-by-side table above for the breakdown.
What's the price difference between GPT-4o mini and Command R?
GPT-4o mini: $0.15 per 1M input tokens. Command R: $0.15 per 1M input tokens. Output token pricing typically runs 2-5x higher.
Which model is better for coding?
Coding preference depends on your stack and tool-calling needs. Compare the coding signal row, test with your repository tasks, and validate latency in your target region.
Which model is cheaper at scale?
Input and output token pricing can diverge by workload profile. Use the estimator with your monthly request count and token mix to get a realistic cost difference.
Are these official benchmark numbers?
Pricing is live from OpenRouter. Benchmark rows are ModelsAtlas metadata-based signals and should be treated as directional guidance, not official leaderboard scores.
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