If it's just for casual chatting or drafting content, honestly, just use whatever feels right. But if you're in the game of content creation, coding, running workflows, accessing APIs, building knowledge bases, or setting up AI tools, then you can't just look at model hype.
What we really need to focus on are three key things:
Pricing, stability, and customer support.
Because AI services aren't a one-and-done deal. You'll face issues like limits, endpoints, model switching, call failures, and cost control down the line.
So today we're not diving into the esoteric stuff, let's kick off with the official API pricing.
1. First, check the GPT official API pricing.
Taking the publicly available API prices on OpenAI's official website as a reference, the price for GPT-5.5 is about:
• Input: 5 USD / 1 million tokens
• Output: 30 USD / 1 million tokens
If we roughly calculate at 1 USD ≈ 7.2 CNY:
• Input about 36 CNY / 1 million tokens
• Output about 216 CNY / 1 million tokens
If using GPT-5.4, the price will be lower:
• Input: 2.5 USD / 1 million tokens
• Output: 15 USD / 1 million tokens
Which roughly translates to:
• Input about 18 CNY / 1 million tokens
• Output about 108 CNY / 1 million tokens
There are also mini versions available at lower prices:
• Input: 0.75 USD / 1 million tokens
• Output: 4.5 USD / 1 million tokens
Which roughly translates to:
• Input about 5.4 CNY / 1 million tokens
• Output about 32.4 CNY / 1 million tokens
So the characteristics of GPT are quite clear:
The model gradient is quite clear, with options from high performance to low cost.
If you're writing code, developing tools, integrating APIs, or running automation, GPT's overall adaptability will be stronger.
Second, let's look at the API prices on Claude's official website.
Claude also has different models with significant price differences.
Common Claude API prices can be understood as follows:
Claude Opus series:
• Input about 15 USD / 1 million tokens
• Output about 75 USD / 1 million tokens
Which roughly translates to:
• Input about 108 CNY / 1 million tokens
• Output about 540 CNY / 1 million tokens
Claude Sonnet series:
• Input about 3 USD / 1 million tokens
• Output about 15 USD / 1 million tokens
Which roughly translates to:
• Input about 21.6 CNY / 1 million tokens
• Output about 108 CNY / 1 million tokens
Claude Haiku series:
• Input about 0.8 USD / 1 million tokens
• Output about 5 USD / 1 million tokens
Which roughly translates to:
• Input about 5.8 CNY / 1 million tokens
• Output about 36 CNY / 1 million tokens
From a pricing perspective, Claude is not unusable, but it depends on the scenario.
Opus is powerful, but the price is also noticeably high. Sonnet is more balanced, suitable for most content and long text tasks. Haiku is cheaper, suitable for lightweight tasks, classification, and simple summaries.
Third, how to choose between GPT and Claude?
My advice is pretty straightforward.
If you're mainly writing code, integrating APIs, and doing automation, prioritize GPT.
GPT is more suitable for:
• Code generation
• Error analysis
• JSON output
• Tool invocation
• API integration
• Automated workflows
• Structured task processing
Especially in developer scenarios, GPT's engineering adaptability will be stronger.
If you're mainly writing articles, reading materials, and creating content, prioritize Claude.
Claude is more suitable for:
• Long text reading
• Copywriting refinement
• Data organization
• Article rewriting
• Optimization of Chinese expressions
• Reports, proposals, and scripts
Claude has a better sense of language, especially in understanding and expressing long texts, often more naturally.
So it's not that GPT is necessarily better than Claude, nor is Claude necessarily better than GPT.
To be more accurate:
For development, GPT is smoother; for content, Claude is more comfortable.
If your budget is sufficient, the best approach is not to choose one or the other, but to keep both and switch based on tasks.
Fourth, why I don't recommend only looking at the 'lowest price'
Many AI channels on the market are competing on price.
But I believe AI services cannot just be focused on being cheap.
Because things that are too cheap often require a second question:
Can it be used long-term? If problems arise, is there someone to handle them? Are the models genuinely usable? Is the interface stable? Can switching happen later? Will after-sales support disappear?
Especially for API users, the biggest fear is not just a slightly higher price, but interruption mid-process.
If you're just chatting on the web, if something goes wrong, you can just wait and try again. But if your API is already integrated into projects, customer service, tools, or automated processes, a stable interface is crucial, as instability affects the entire business.
So, I evaluate a channel mainly by looking at three points:
First, whether the price is reasonable. It's not just about being lower, but whether it’s low enough to be normal.
Secondly, whether the models are comprehensive. It's best to be able to use both GPT and Claude, so you don't get locked into a single model.
Third, whether there is after-sales support. AI services will definitely encounter problems, having someone to handle them is more important than just being cheap.
Fifth, under what circumstances is it suitable to use API relays?
If you're just chatting normally, a membership on the official website or the web version is enough.
But if you have the following needs, a relay station will be more suitable:
• Want to use both GPT and Claude simultaneously
• Don’t want to deal with multiple official websites separately
• Want to integrate API for projects
• Want to control invocation costs
• Want to switch models based on tasks
• Want more convenient interface integration
• Hope someone can assist in troubleshooting when issues arise
The value of API relays is not necessarily that they are superior to the official website.
It’s more like centralizing the handling of models, interfaces, quotas, prices, and after-sales support, reducing the hassle for users.
For ordinary users, it's about saving time. For developers, it's about avoiding pitfalls. For small teams, it's about reducing integration costs.
Sixth, so my suggestion is
If you have sufficient budget, are familiar with the official website process, and can handle payments and interface issues yourself, then going directly through the official website is certainly fine.
But if you just want to use GPT and Claude stably without the hassle of registration, payments, quotas, interfaces, and model switching, you might consider a reliable API relay service.
The focus is not just on being cheap, but on:
Appropriate pricing, sufficient models, available after-sales support, and issues that can be communicated.
I'm also doing API relay for GPT and Claude, mainly targeting individual users, developers, and small teams.
What I care more about is not the 'low-price gimmick', but several practical issues:
• Both GPT and Claude can be used
• Suitable for API integration
• Suitable for content creation and development scenarios
• After-sales communication
• Can assist in troubleshooting when issues arise
• Users don’t have to keep messing around with multiple platforms
Of course, I don’t recommend blind purchases.
If you're just asking a few questions occasionally, there's no need to fuss. If you often write articles, code, integrate interfaces, or run tasks, then a relay service that can use both GPT and Claude will offer better value.
Lastly, let me say this
AI models are updating too quickly now.
Today GPT is strong, tomorrow Claude updates, and the day after that, there might be new models catching up.
So I don’t recommend ordinary users to bet too long in one go, nor do I recommend buying randomly just because it's cheap.
The service truly suitable for long-term use should be:
Transparent pricing, sufficient models, available after-sales support, and someone to handle issues when they arise.
Cheap is just the first step.
Only a service that can be used long-term without worries is truly cost-effective.
