How I Cut 70% of My Team's AI Costs

If you use AI models for coding, content, or automation, there is a good chance you are paying more than you need to. Not because the expensive models are bad, but because most people never actually compare what they get for the money.

So I ran a simple experiment. I took one prompt, an HTML animation, and sent the exact same prompt to six of the top models available right now. Then I looked at two things: the quality of the output, and the real cost of each run.

The results surprised me, and they might change how you pick a model too.

The six models

Here are the models I put head to head:

• GLM 5.2, an open weight model that punches well above its price
• Opus 4.8 from Anthropic
• Sonnet 5, the newer Anthropic model
• Fable 5, the model everyone has been talking about lately
• Sakana Fugu, a Japanese model claiming benchmarks close to Fable 5
• GPT 5.5 from OpenAI

Same prompt for every one. No tweaking, no retries. Just a fair, side by side run.

The cost breakdown

This is where it gets interesting. Here is what each model cost for the identical task:

Look at the spread. The cheapest run cost about twenty six cents. The most expensive cost over three dollars. That is roughly a twelve times price difference for the same prompt.

Fable 5 produced an impressive result, though even that had a small glitch in the animation. Meanwhile GLM 5.2, at a fraction of the cost, held its own. Sonnet 5 looked great to me for the price. Opus 4.8, honestly, I expected more from given what it charged.

The takeaway is not that expensive models are useless. It is that the most expensive model is not automatically the best one for your task. And if you are defaulting to a premium model for everything, you are almost certainly overpaying.

The real problem: switching is a pain

Here is the catch. Even once you know a cheaper model works fine for a given job, actually switching between models is annoying. Every provider has its own API, its own keys, its own config. Reconfiguring your setup every time you want to test a different model kills the whole idea before you start. So most people just stick with one expensive default and eat the cost.

That is exactly the problem I wanted to solve.

How Clawgate helps you stop overpaying

Full disclosure, Clawgate is a tool my team at Virstack built, so I am biased. But it is also the reason this whole comparison was even practical to run.

Clawgate acts as a single hub for all your models. You configure it once, connect it to your tools like Claude Code and Codex, and then you can switch between any model straight from the dashboard. No touching your local config, no juggling multiple API keys, no reconfiguring anything.

Here is how that translates into spending less:

One key, every model. You set up Claude Code or Codex a single time with one Clawgate key. After that, changing the underlying model is a dashboard action, not a code change. Trying GLM 5.2 instead of Opus 4.8 takes seconds.

Real cost visibility per model. Every run in this experiment was tracked automatically. The exact costs you saw came straight out of the Clawgate usage and dashboard pages, broken down model by model. When you can actually see that one task cost twelve times more on one model than another, you make smarter choices.

Policies and forced models. You can set a policy that limits which models a key can use, or force a specific model for a given project. That means you can route cheaper tasks to cheaper models on purpose, instead of everything defaulting to the priciest option.

Pay as you go. No lock in to one provider. You use what you use, across every model, through one bill.

The point is not to always pick the cheapest model. It is to have the freedom to pick the right model for each task, and the visibility to know what that choice actually costs you. That is how you stop overpaying.

Try it yourself

Ask yourself a simple question about your own workflow: are you paying premium prices for tasks a cheaper model could handle just as well? If the answer is yes, it might be time to rethink your setup.