DeepSeek’s API uses usage-based pricing. V4 Flash, the most popular tier, costs $0.14 per million input tokens and $0.28 per million output tokens at standard rates, with cache-hit input tokens at just $0.0028 per million.
For small creators and small teams who are looking for a cheaper way to use AI models for their business optimization. With the rise of Chinese AI models, this has become possible. Models like DeepSeek, Qwen, Kimi, and GLM are available at much lower prices than many Western options.
Whether you manage everything yourself or run your experiments through a platform like MyClaw, the options are there. But to get the best money out of them and to get the best results, it will take some guidelines on how to use them. Read this blog to learn how to use Chinese AI models to save money.
Most AI headlines focus on which model is “smartest.” For everyday work, you likely care about the same thing: how much it costs to get a good answer.
Many Chinese labs price their models far below comparable Western ones. If you send hundreds of requests a day, like product descriptions, customer replies, or document recaps, the savings add up fast. A task that costs a few dollars on one model can cost pennies on another.
Two things help. First, many of these models use strong designs that only activate part of the model for each request, which saves computing power. Second, many are released as open-weight, so other agencies can host them and compete on price. More competition often means lower bills for you.
You don’t need the strongest model for every task. Using a top-tier model to fix a typo is like hiring a chef to make toast.
For emails, captions, outlines, and short recaps, a mid-size or “flash” model is often enough. DeepSeek’s lighter versions and Qwen’s smaller models manage this kind of work well, and they reply fast.
If you regularly work with long reports, contracts, or transcripts, look at Kimi. It’s known for handling large sums of text and keeping track of details across many steps. That makes it a good fit for research-heavy days.
GLM and DeepSeek both have a good reputation for coding help. They’re good for debugging, writing small scripts, and explaining unknown code in clear language. If you make clear automations for your business, they can save you hours.
Keep the biggest, most costly models for tasks that really need deep logic, like complex study or tricky multi-step planning. A clear rule: start with the cheaper model, and only move up if the answer isn’t good enough.
Rankings change every few weeks, so don’t trust them easily. Run your own test.
Pick work you really do. For example: summarize a long article, rework a client email in a friendlier tone, and fix a small part of broken code.
Copy and paste the same guide into two or three models. This keeps the comparison fair.
Give each answer a quick rating from 1 to 5 for accuracy, clarity, and how much editing it needs. Also note how long it takes and what it costs.
Many people end up with a cheap everyday model and a stronger one for tougher jobs. That setup gives you good quality without overspending.
AI isn’t only for spreadsheets and code. If you make logos, tattoos, posters, or merchandise, a good model can speed up the idea step a lot.
Here’s a nice workflow. Ask an AI model to brainstorm fifteen short words or sayings linked to your theme, like “balance,” “rise,” or “unity.” Then drop your most liked into an ambigram generator to see which ones can be read the same way when rotated or flipped. Some words look great this way, and others not, so you’ll quickly see which ideas are worth taking further. Then go back to the AI and ask it to tell the meaning of your top choice, or write a short caption to go with the final design.
It’s a small example, but it shows a bigger point: the best results often come from pairing an AI model with a good specialized tool.
Lower prices are best, but a few checks will protect you.
Don’t paste personal data into any AI service without reading how it uses your data. This goes for client details, financial records, and personal records. If privacy is important, an open-weight model that you or a trusted provider hosts gives you more control.
All AI models can state wrong data with total confidence. Double-check names, numbers, dates, and quotes before you post or send anything. For serious subjects, ask two different models and compare.
Models trained in different areas can answer personal or political questions differently. If your work is in those areas, test the model first and don’t assume it acts like the one you’re used to.
If you plan to sell something made on an open-weight model, learn the license. Many are friendly to commercial use, but the details change from model to model.
If you can say yes to most of these, you’re in good shape.
Chinese AI models give you something rare in tech: more power for less money, with real options. You don’t have to throw away the tools you already like. Try a cheaper model for the easy jobs, keep a stronger one on standby, and let your own results guide you.
Spend thirty minutes this week running the test above. You may find you can do the same work for a lot less, and have more space in your budget to try new things.
DeepSeek’s API uses usage-based pricing. V4 Flash, the most popular tier, costs $0.14 per million input tokens and $0.28 per million output tokens at standard rates, with cache-hit input tokens at just $0.0028 per million.
Open-weight models let users download the parameters. They can then run, modify, or host the models in their own data centers. This gives more control over data and reduces reliance on foreign APIs.
Yes, for many everyday tasks. Companies in the US and Africa already use them for coding, customer support, data extraction, and local-language work. Some companies use them for complex work as well.
