Model comparison
GPT-5.5 Pro vs Cohere Command R7B
Compare GPT-5.5 Pro vs Cohere Command R7B API pricing: input/output token costs, cache pricing, context windows, workload estimates, and routing fit.
GPT-5.5 Pro
openai · gpt-5.5-pro
- Input
- $30
- Output
- $180
- Context
- 1.1M
Cohere Command R7B
cohere_chat · command-r7b-12-2024
- Input
- $0.037
- Output
- $0.15
- Context
- 128K
Quick take
Cohere Command R7B has the lower input price at $0.037 per 1M input tokens. Cohere Command R7B is cheaper for the example blended workload below. GPT-5.5 Pro has the larger context window at 1.1M tokens.
Choose GPT-5.5 Pro if...
- GPT-5.5 Pro is safer for long documents, repository analysis, and RAG prompts because it has the larger context window.
- GPT-5.5 Pro gives more room for long generated answers, reports, or code output.
- GPT-5.5 Pro is stronger when the same large prompt or document is reused because it supports prompt caching.
Choose Cohere Command R7B if...
- Cohere Command R7B is the better default for cost-sensitive traffic and repeated high-volume calls.
Example workload cost
Estimates use input tokens plus 20% output tokens. They exclude provider discounts, cache hits, and tool/search surcharges.
| Workload | GPT-5.5 Pro | Cohere Command R7B | Cheaper |
|---|---|---|---|
| 1M input + 200K output | $66.00 | $0.07 | Cohere Command R7B |
| 10M input + 2M output | $660.00 | $0.68 | Cohere Command R7B |
| 100M input + 20M output | $6,600.00 | $6.75 | Cohere Command R7B |
Context, output, and capability fit
GPT-5.5 Pro provides the larger context window. Check max output separately when the task needs long reports, code generation, or full-document rewrites.
- GPT-5.5 Pro max output
- 128K
- Cohere Command R7B max output
- 4.1K
- GPT-5.5 Pro features
- prompt caching, function calling, vision
- Cohere Command R7B features
- function calling
Risk notes for GPT-5.5 Pro
- High output price: cap max tokens for verbose generation workloads.
Risk notes for Cohere Command R7B
- Smaller context window: long PDFs, codebases, or RAG prompts may need chunking.
- No prompt caching in this snapshot: repeated long-context calls may be more expensive.
Routing tags
frontierpremiumreasoningcodingagentslong-contextmultimodalcache-friendlyragbudgethigh-volumeenterprise-rag