Cohere: Command R+ (08-2024) vs OpenAI: GPT-6.1 Sol Pro
A side-by-side comparison of Cohere: Command R+ (08-2024) ($8.75 / 1M tokens) and OpenAI: GPT-6.1 Sol Pro ($7.00 / 1M tokens) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.
Specifications
| Cohere: Command R+ (08-2024) | OpenAI: GPT-6.1 Sol Pro | |
|---|---|---|
| Provider | Cohere | OpenAI |
| Input | $8.75 / 1M tokens | $7.00 / 1M tokens |
| Output | $35.00 / 1M tokens | $35.00 / 1M tokens |
| Cache read | - | $0.35 / 1M tokens |
| Cache write | - | $8.75 / 1M tokens |
| Web search | - | $35.00 / 1K searches |
| Context window | 128,000 | 1,050,000 |
| Max output | 4,000 | 128,000 |
| Input | text | file, image, text |
| Output | text | text |
| Tool calling | ||
| Structured output | ||
| Reasoning control | ||
| Added | Aug 30, 2024 | Sep 29, 2026 |
Key differences
- OpenAI: GPT-6.1 Sol Pro is 20% cheaper on input tokens.
- OpenAI: GPT-6.1 Sol Pro reads 8.2× more context (1,050,000 tokens).
- Only OpenAI: GPT-6.1 Sol Pro supports reasoning effort control.
- A request with 1,000 input and 500 output tokens costs $0.03 with Cohere: Command R+ (08-2024) and $0.02 with OpenAI: GPT-6.1 Sol Pro.
In depth
Cohere: Command R+ (08-2024) is a text model from Cohere, released on 30 August 2024. OpenAI: GPT-6.1 Sol Pro is a text model from OpenAI, released on 29 September 2026. Both are served through api14 as chat models in the text category, so either one can slot into the same kind of application code.
The two differ most in context and input handling. Command R+ accepts text only and carries a context window of 128,000 tokens. GPT-6.1 Sol Pro accepts file, image and text input, and its context window is 1,050,000 tokens, which is substantially larger. GPT-6.1 Sol Pro is also the only one of the two that exposes reasoning controls, with parameters such as reasoning, reasoning_effort and include_reasoning. On the parameter side, Command R+ supports frequency_penalty, presence_penalty, top_k, top_p, temperature, seed, stop, response_format, structured_outputs, tools and tool_choice. GPT-6.1 Sol Pro supports max_completion_tokens, max_tokens, seed, response_format, structured_outputs, tools, tool_choice and verbosity alongside its reasoning parameters. Neither model is listed as uniquely offering tools or structured outputs, so those capabilities are effectively shared.
For task selection, the deciding factors are input type, context size and whether you want reasoning effort to be tunable. If your workload is plain text, fits comfortably inside 128,000 tokens and you want sampling controls like top_k and presence_penalty, Command R+ is a reasonable fit. If you need to pass images or files, or you are working with very long documents, codebases or transcripts that would strain a smaller window, GPT-6.1 Sol Pro is the better choice. The same applies when you want to dial reasoning effort up or down per request, since only GPT-6.1 Sol Pro exposes that. On price, GPT-6.1 Sol Pro is the cheaper of the two for input, while output pricing is about the same, so cost is unlikely to be the deciding factor unless your traffic is heavily input dominated.
Calling either model through api14 works the same way because the API is OpenAI compatible. You point your client at the api14 base URL, send a normal chat completions request, and set the model field to the id you want. To use Cohere's model, set model to "cohere/command-r-plus-08-2024". To use OpenAI's model, set model to "openai/gpt-6.1-sol-pro". Everything else in the request body stays as your code already builds it, with the caveat that parameters are not perfectly interchangeable: top_k and presence_penalty belong to the Cohere side, while reasoning, reasoning_effort, include_reasoning and verbosity belong to the OpenAI side. If you switch ids, check that the parameters you send are supported by the target model, and adjust max_tokens versus max_completion_tokens accordingly.
There are still cases where Command R+ is the better pick. If your application is purely text, your inputs are short enough for a 128,000 token window, and you rely on sampling controls such as top_k, frequency_penalty or presence_penalty to shape output, Command R+ gives you those knobs directly. It is also the simpler target when you do not want reasoning behaviour involved at all and prefer a straightforward text in, text out call.
Switch with one string
Both models use the same endpoint and request shape. Change the model value from "cohere/command-r-plus-08-2024" to "openai/gpt-6.1-sol-pro" and prompts, streaming and tools keep working.
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api14.com/api/v1",
apiKey: process.env.API14_API_KEY,
});
const result = await client.chat.completions.create({
"model": "openai/gpt-6.1-sol-pro",
"messages": [
{
"role": "user",
"content": "Explain vector databases in two sentences."
}
]
});
console.log(result.choices[0].message.content);
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