Control your costs
The two levers that shape what you spend in Hyperagent, which plan you pick and which model does the work.
Two levers shape what you spend in Hyperagent: which plan you pick, and which model does the work. The first sets the ceiling on a period. The second sets what your work costs run to run. This page covers both.
Pick the plan that fits your usage
Your spending is bounded by the credit you hold. You pay your plan price each month, it is charged up front and becomes credit plus a progressive bonus, and your agents spend that balance as they run. There is no separate cost cap to configure: with credit top-ups and auto-recharge left off, your plan price is the ceiling for the period.
Pick a plan that matches your work
A higher monthly plan earns a larger bonus, up to 45 percent, so more of your usage is covered by credit. Pick the tier that matches how much work you expect to run. See Plans for the full ladder.
Turn on auto-recharge, or top up
When credit runs low, add a credit block in Settings → Billing, or turn on auto-recharge so a new block is added automatically when your balance falls below the threshold you set.
Because usage spends a balance you already hold, your plan price is itself the guardrail. Leaving auto-recharge off keeps the period capped at what you paid up front. Turning it on trades that hard stop for continuity when a run needs more than the balance left. See Credits for how the balance is spent and Usage and invoices for how to track it.
Choose the right model for the work
Model cost and capability vary widely for the same job, so the model you pick is the biggest lever on what a run costs. The model picker in the agent editor is the source of truth for what each model costs in your workspace right now. The roster changes as models are added and prices are adjusted, so read the picker rather than memorizing a list, and let it guide the tradeoff between price and capability.
The general principle is to start lighter and escalate on purpose. Many jobs do not need the strongest model, and a lighter model that finishes the work well costs less per token. Reach for a stronger model when the task's judgment is high-stakes, or when the cost of reviewing and correcting a weaker answer would exceed the price difference.
Name the job
A specific task, such as preparing a weekly report, is easier to staff than a general one.
Start where the job seems to fit
Weigh the job's judgment and frequency before reaching for the strongest option in the picker.
Test one class lighter
Run a few real runs on a lighter model with the same instructions and skills, then compare the finished quality and the bill.
Escalate when needed
Move up when the review burden or the cost of a wrong answer exceeds the price difference.
Model choice does not require rebuilding an agent. You can run the same agent on two models with the same instructions, tools, and inputs, then compare quality and spend in Usage and invoices. A cheaper run stops being cheaper when someone has to redo the work, so test the finished output, not just the price.
Effort and per-run budget are secondary dials
Many models also expose an effort control and a per-run budget on the agent. Effort trades latency and cost for more reasoning room; the per-run budget caps what a single query can spend. Both sit below the model choice in impact. See Supported models.
How the two levers work together
Your plan sets how much you can spend in a period, and your model choice sets what each run costs against that balance. A well-matched model stretches a given plan further, and a plan sized to your usage keeps the period predictable. The two are complementary, and neither replaces the other.