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Google: Gemma 4 31B vs OpenAI: GPT-4.1 Nano

A side-by-side comparison of Google: Gemma 4 31B ($0.70 / 1M tokens) and OpenAI: GPT-4.1 Nano ($0.35 / 1M tokens) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.

Specifications

	Google: Gemma 4 31B	OpenAI: GPT-4.1 Nano
Provider	Google	OpenAI
Input	$0.70 / 1M tokens	$0.35 / 1M tokens
Output	$1.40 / 1M tokens	$1.40 / 1M tokens
Cache read	-	$0.11 / 1M tokens
Web search	-	$35.00 / 1K searches
Context window	262,144	1,047,576
Max output	16,384	942,818
Input	image, text, video	image, text, file
Output	text	text
Tool calling
Structured output
Reasoning control
Added	Apr 2, 2026	Apr 14, 2025

Key differences

OpenAI: GPT-4.1 Nano is 50% cheaper on input tokens.
OpenAI: GPT-4.1 Nano reads 4.0× more context (1,047,576 tokens).
Only Google: Gemma 4 31B supports reasoning effort control.
A request with 1,000 input and 500 output tokens costs $0.00140 with Google: Gemma 4 31B and $0.00105 with OpenAI: GPT-4.1 Nano.

In depth

Google: Gemma 4 31B is a text model from Google, listed on api14 under the model id google/gemma-4-31b-it. OpenAI: GPT-4.1 Nano is a text model from OpenAI, listed under the model id openai/gpt-4.1-nano. Both are served through the same OpenAI-compatible endpoint, so the choice between them is mostly about which one fits the shape of your task rather than which one you can technically reach.

The two differ most in context and modalities. GPT-4.1 Nano carries a much larger context window, over a million tokens, while Gemma 4 31B sits at roughly a quarter of that. Gemma 4 31B accepts image, text and video as input, whereas GPT-4.1 Nano accepts image, text and file input. Neither model produces anything other than text. On price, GPT-4.1 Nano is the cheaper of the two for input, and the two are about the same price for output. Gemma 4 31B is the only one of the pair that exposes reasoning controls, along with a broader set of sampling parameters such as top_k, min_p, repetition_penalty, logit_bias and logprobs. GPT-4.1 Nano's parameter surface is narrower, covering the essentials like temperature, top_p, seed, tools and structured outputs.

For practical work, reach for GPT-4.1 Nano when the job is long. Large document sets, big codebases, lengthy transcripts or anything where you want to keep a lot of material in a single request fits its larger context. It is also the cheaper input option, which matters when you are sending a lot of tokens per call. Reach for Gemma 4 31B when you need video input, when you want reasoning controls or the wider sampling and scoring parameters, or when you want to tune generation behaviour more finely with top_k, min_p or repetition penalties. Both support tools and structured outputs, so function calling and JSON-shaped responses are available on either side.

Calling either model through api14 works the same way. You point your client at the OpenAI-compatible base URL, send a chat completions request, and set the model field to google/gemma-4-31b-it or openai/gpt-4.1-nano. Everything else in the request body follows the OpenAI schema you already use. Switching between the two is a one-line change to that model id, so you can build against one and compare against the other without rewriting your integration.

There are still cases where the other model wins. If your input is video, GPT-4.1 Nano is not the pick, since Gemma 4 31B is the one that lists video among its input modalities. If you want reasoning output or the extra sampling parameters, the same applies. Conversely, if your prompt is enormous or your input volume is high, Gemma 4 31B is the weaker fit, because GPT-4.1 Nano gives you the larger context and the cheaper input. Match the model to the input type, the length of the request and the controls you need, and the decision usually makes itself.

Switch with one string

Both models use the same endpoint and request shape. Change the model value from "google/gemma-4-31b-it" to "openai/gpt-4.1-nano" and prompts, streaming and tools keep working.

Google: Gemma 4 31B details & playground →OpenAI: GPT-4.1 Nano 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-4.1-nano",
  "messages": [
    {
      "role": "user",
      "content": "Explain vector databases in two sentences."
    }
  ]
});
console.log(result.choices[0].message.content);

More comparisons

Gemma 4 31B vs GPT-4.1 Nano: API price, context & features · api14