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Google: Gemini 3.1 Pro Preview Custom Tools vs OpenAI: GPT-4o

A side-by-side comparison of Google: Gemini 3.1 Pro Preview Custom Tools ($7.00 / 1M tokens) and OpenAI: GPT-4o ($8.75 / 1M tokens) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.

Specifications

	Google: Gemini 3.1 Pro Preview Custom Tools	OpenAI: GPT-4o
Provider	Google	OpenAI
Input	$7.00 / 1M tokens	$8.75 / 1M tokens
Output	$42.00 / 1M tokens	$35.00 / 1M tokens
Cache read	$0.70 / 1M tokens	$4.38 / 1M tokens
Cache write	$1.31 / 1M tokens	-
Reasoning	$42.00 / 1M tokens	-
Audio input	$7.00 / 1M tokens	-
Image	$0.000007 / image	-
Web search	$49.00 / 1K searches	-
Context window	1,048,576	128,000
Max output	65,536	16,384
Input	text, audio, image, video, file	text, image, file
Output	text	text
Tool calling
Structured output
Reasoning control
Added	Feb 25, 2026	May 13, 2024

Key differences

Google: Gemini 3.1 Pro Preview Custom Tools is 20% cheaper on input tokens.
OpenAI: GPT-4o is 17% cheaper on output tokens.
Google: Gemini 3.1 Pro Preview Custom Tools reads 8.2× more context (1,048,576 tokens).
Only Google: Gemini 3.1 Pro Preview Custom Tools supports reasoning effort control.
A request with 1,000 input and 500 output tokens costs $0.03 with Google: Gemini 3.1 Pro Preview Custom Tools and $0.03 with OpenAI: GPT-4o.

In depth

Google: Gemini 3.1 Pro Preview Custom Tools is a Google model in the text category, released by the provider on 2026-02-25. OpenAI: GPT-4o is an OpenAI model, also in the text category, released by its provider on 2024-05-13. Both are served through api14 under OpenAI-compatible model ids, so the choice between them is mostly about context, modalities and the parameters you need.

The clearest split is context length. Gemini 3.1 Pro Preview Custom Tools accepts up to 1,048,576 tokens, while GPT-4o accepts up to 128,000. Gemini also takes more input modalities: text, audio, image, video and file. GPT-4o takes text, image and file. Both return text only. On reasoning, Gemini exposes reasoning controls (include_reasoning, reasoning, reasoning_effort) and is the only one of the two with that capability here. Parameter sets differ in other ways too: GPT-4o supports frequency_penalty, logit_bias, logprobs, prediction, presence_penalty, stop, top_logprobs and web_search_options, none of which appear on the Gemini list, while Gemini supports top_p, temperature, seed, tools, tool_choice, structured_outputs, response_format and max_tokens just as GPT-4o does. Neither model is listed as uniquely supporting tools or structured outputs, so those are effectively a tie.

For practical selection, reach for Gemini 3.1 Pro Preview Custom Tools when your input is large (long documents, long transcripts, big codebases) or when you need to feed audio or video directly rather than transcribing or sampling frames first. Its reasoning parameters also make it the natural pick for tasks where you want to control how much internal reasoning effort the model spends. Reach for GPT-4o when you want the OpenAI-style sampling and debugging controls: logprobs and top_logprobs for confidence inspection, logit_bias for constrained decoding, presence and frequency penalties for repetition control, prediction for latency-sensitive edits, or web_search_options. If your inputs are text and images within 128,000 tokens and you do not need reasoning controls, GPT-4o covers the same ground.

Calling either one through api14 is the same request shape, because the gateway is OpenAI-compatible. You send a chat completions request to the same endpoint with the same headers and the same JSON body, and the only field you change is model. Set it to "google/gemini-3.1-pro-preview-customtools" for the Google model or "openai/gpt-4o" for the OpenAI model. Messages, tools, response_format and the rest of the body stay where they are, so switching is a one-line edit and you can keep a single client library for both. Just remember that parameters are not fully interchangeable: sending logprobs or web_search_options to the Gemini id, or reasoning_effort to the GPT-4o id, is outside the supported set for that model, so keep per-model parameter handling in your code.

There are still cases where GPT-4o is the better pick even though Gemini has the larger context and more input types. If your work depends on token-level probabilities, biased logits, explicit stop sequences or the built-in web search option, those live on the GPT-4o parameter list and not on the Gemini one. On price, Gemini 3.1 Pro Preview Custom Tools is the cheaper side for input, while GPT-4o is the cheaper side for output, so a workload dominated by long prompts points one way and a workload dominated by long generations points the other. Check the live price table on this page for the current numbers before you commit.

Switch with one string

Both models use the same endpoint and request shape. Change the model value from "google/gemini-3.1-pro-preview-customtools" to "openai/gpt-4o" and prompts, streaming and tools keep working.

Google: Gemini 3.1 Pro Preview Custom Tools details & playground →OpenAI: GPT-4o details & playground →

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-4o",
  "messages": [
    {
      "role": "user",
      "content": "Explain vector databases in two sentences."
    }
  ]
});
console.log(result.choices[0].message.content);

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Gemini 3.1 Pro Preview Custom Tools vs GPT-4o: API price, context & features · api14