Gemini API Pricing: How to Compare It With Claude Opus 4.7 and OpenAI

If you’ve been searching for Gemini API pricing, you’ve likely noticed something: every comparison blog seems to have a different answer, and none of them match your actual workload. That’s because flagship model pricing is only half the story. The real question isn’t “which model has the lowest per-token rate?” but “which model delivers the lowest cost per successful task?”

In this guide, we’ll look at Claude Opus 4.7 and OpenAI’s GPT-5.6 family using real rates from the OneMux model catalogue, then show you how to evaluate Gemini 3.1 Pro with the help of the aipricing.guru blog.

Why Token Price Isn’t the Only Number That Matters

Every LLM bill is made of inputs, outputs, and occasionally caching. But the inputs and outputs you send per task can vary wildly between models. A model that returns terse, correct answers might be cheaper than one that writes three paragraphs of polite apologetics. Similarly, a model with lower input price but higher output price can cost more if it makes your prompt loop verbose.

The aipricing.guru comparison can help you sanity check list prices across three flagship families. Their source summary is straightforward: compare Opus 4.7, GPT-5.4, and Gemini 3.1 Pro on API price, benchmark fit, and when each flagship model is worth the bill. That’s exactly the kind of head-to-head you need before you start a big migration.

Claude Opus 4.7 Pricing: The Stable Generalist

Claude Opus 4.7 from Anthropic sits at a balanced price point, and it’s the flagship in the OneMux catalogue for teams that want dependable reasoning without paying for unnecessary bells and whistles.

What “stable generalist” means in practice: Opus 4.7 tends to be a reference point for tasks that need deep reasoning without wild output variation. If you’re building a support copilot that has to read a long email thread and produce a short, actionable response, the $1.50 input price matters more than the $7.50 output price because your input will likely be 10x your output.

OpenAI API Pricing: GPT-5.6 Tiers

OpenAI’s current lineup in the OneMux catalogue is the GPT-5.6 family, which gives you three price-performance tiers:

Notice how the output price jumps dramatically between Terra and Sol. If you’re using plenty of few-shot examples or re-generating failed tasks, Sol can get expensive fast. Luna, on the other hand, is a strong candidate when you can afford lower verbosity and just need structured JSON back.

Where Gemini Fits in the Pricing Picture

We didn’t put Gemini 3.1 Pro in the tables above because OneMux doesn’t currently list that model in its catalogue. That doesn’t mean you should ignore it. The aipricing.guru blog specifically compares Gemini 3.1 Pro with Opus 4.7 and GPT-5.4 on both price and benchmark fit, and their conclusion—as the source summary puts it—is about “when each flagship model is worth the bill.”

If you’re evaluating Gemini API pricing, use that source as a reference for Gemini’s rates and benchmark positioning. Then, add your own token counts to get an effective cost comparison.

A Practical Decision Framework

When in doubt, run a small script that measures total tokens per task on your own data. Here’s a simple pseudo-code decision tree you can adapt:

task_type = detect_task_type()  # classification, coding, chat, reasoning

if task_type == "classification" or task_type == "extraction":
    model = "gpt-5.6-luna"       # cheapest, fastest
elif task_type == "coding":
    model = "claude-opus-4.7"    # strong at code reasoning, stable price
elif task_type == "complex_reasoning":
    model = "gpt-5.6-sol"        # top-tier reasoning, higher cost
else:
    # multimodal input: check Gemini 3.1 Pro benchmark fit via source
    model = "evaluate-with-source-reference"

This isn’t a magic formula—it’s a starting point. Replace the model names with prices from your own provider, and always measure output token counts before committing.

Routing Between Models with OneMux

The fastest way to test all these models without rewriting your code is to use a single OpenAI-compatible API. OneMux gives you access to Claude Opus 4.7, the GPT-5.6 family, and more through one endpoint. You get spend visibility, easy credit top-ups, and lower-cost pay-as-you-go usage for many workloads.

Start by browsing the OneMux model catalogue to check current rates, then head to the OneMux pricing page to see how the billing works. If you want to route traffic in minutes, the OneMux quickstart guide walks you through the first request. For full API details, the OneMux docs cover everything from key management to token streaming.

Bottom Line

Gemini API pricing is a moving target, but the decision framework stays the same: estimate your effective token use, compare flagship model rates, and route intelligently. Claude Opus 4.7 offers a dependable balance for general tasks, OpenAI’s GPT-5.6 tiers give you budget and premium options, and Gemini 3.1 Pro deserves a look if the benchmarks align with your workload.

For a current head-to-head of Opus 4.7, GPT-5.4, and Gemini 3.1 Pro, start with the aipricing.guru blog reference we cited above. Then build your own test set. The model that wins on paper is not always the one that wins on your invoice.

Frequently Asked Questions

Is Gemini API pricing cheaper than Claude Opus 4.7?

It depends on the workload and the specific rates at the time you’re reading. The aipricing.guru source compares Gemini 3.1 Pro with Opus 4.7, so check that reference for the latest per-token numbers.

What is the price of Claude Opus 4.7 per 1M tokens?

Through OneMux, Claude Opus 4.7 is $1.50 per 1M input tokens and $7.50 per 1M output tokens.

How does OpenAI API pricing work for GPT-5.6?

OpenAI API pricing for GPT-5.6 depends on the tier. Luna is $0.60 input / $3.60 output per 1M tokens, Terra is $1.50 / $9.00, and Sol is $2.50 / $15.00.

Can I use Claude Opus 4.7 and GPT-5.6 through the same API?

Yes. OneMux provides a unified OpenAI-compatible API, so you can route to both model families without changing your integration.

Sources

• aipricing.guru blog — Source summary: Compare Opus 4.7, GPT-5.4, and Gemini 3.1 Pro on API price, benchmark fit, and when each flagship model is worth the bill.