Compare AI model API costs across GPT, Claude, Gemini, DeepSeek and more

What affects AI model API cost

Several factors determine how much each API request costs. Understanding these helps you compare routes and estimate spend before sending requests.

• Model family — Different providers charge different per-token rates. GPT, Claude, Gemini, DeepSeek, Qwen, and others each have their own pricing structure.
• Model size and capability — Larger or more capable model versions typically cost more per token than smaller variants.
• Input tokens — Every word, code snippet, and piece of context in your prompt counts toward input token usage.
• Output tokens — Model-generated responses also consume tokens. Longer answers cost more than short ones.
• Route availability — Some model routes may be unavailable or throttled at certain times, affecting which model you can use.
• Request volume — Frequent or concurrent requests add up quickly, especially with automation.
• Tool and coding-agent behavior — Agents that use tools, browse files, or run multiple sub-requests can generate many API calls per task.
• Retries and errors — Failed requests that are automatically retried use additional credits without producing output.
• Long context usage — Sending large prompts or conversation history significantly increases token consumption per request.

Model families covered

RutaAPI supports OpenAI-compatible access to a range of model families. Examples include:

• GPT (OpenAI)
• Claude (Anthropic)
• Gemini (Google)
• DeepSeek
• Qwen (Alibaba)
• GLM (Zhipu)
• MiniMax
• Grok
• Codex
• Seedance
• Veo

How to compare model costs safely

Before committing to a model or route, use this checklist to compare costs accurately and avoid unexpected charges.

Test your key before spending credits

Before sending any meaningful requests, confirm your API key and Base URL are working correctly.

curl https://api.rutaapi.com/v1/models \
  -H "Authorization: Bearer YOUR_RUTAAPI_KEY"

Send your first small request

After confirming your key works, send a single small chat request with an enabled model ID to see the actual cost.

curl https://api.rutaapi.com/v1/chat/completions \
  -H "Authorization: Bearer YOUR_RUTAAPI_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "YOUR_ENABLED_MODEL_ID",
    "messages": [
      {"role": "user", "content": "Say hello from RutaAPI"}
    ]
  }'

Prepaid credits and cost control

RutaAPI uses prepaid credits instead of subscriptions. Credits are deducted per API request based on the model used, input tokens, and output tokens.

• New RutaAPI accounts include $1 trial credit for testing your Base URL, API key, and one enabled model before topping up.
• Credits are deducted in real time from your account balance — spend is limited to what you have loaded.
• Your dashboard shows per-request credit usage, making it easier to spot unexpected costs early.
• Top up at any amount whenever you need more credits.
• Credits do not expire.

Common cost mistakes

Mistake	Why it happens	Safer approach
Choosing a model only by name	Different sizes and versions of the same family have different rates.	Check the exact model ID and its per-token rate in the app pricing page.
Ignoring output tokens	Long responses can generate more output tokens than input, dominating total cost.	Estimate both input and output cost before sending large-generation tasks.
Using long prompts for every request	Every token in the prompt counts toward input cost.	Keep prompts as short as the task allows. Consider summarising conversation history.
Letting coding agents retry automatically	Retries can multiply costs rapidly without producing useful output.	Review agent settings. Check usage logs after each session.
Assuming one route is always cheapest	Availability and throttling change. A more expensive model may be more reliable.	Test and compare actual per-request costs for your use case.
Not checking usage logs	It is easy to overspend without noticing until credits run low.	Review dashboard logs after each testing session or at the end of each day.
Testing with large production requests first	A single large request can consume more credits than ten small ones combined.	Always send a small test request first to calibrate cost expectations.

AI coding tools and API costs

AI coding assistants and agents can make many API requests per session. They often:

• Send multiple tool calls per user message
• Retry failed requests automatically
• Include large context (file contents, conversation history) in each request
• Run long-context requests for code understanding or refactoring

RutaAPI supports these AI coding tools with OpenAI-compatible endpoints:

• Cline
• Continue.dev
• Codex CLI
• Unified AI coding tools guide
• NextChat
• LobeChat

Frequently Asked Questions