Model Ruler — AI Cost Calculators
by modelruler.dev in AI models & inference
Read-only AI/LLM cost tools with current MCP discovery and attributable Registry transport.
https://modelruler.dev/mcp?dist=model_everywhere_registry_native_official_registry- Tools
- 12
- open to any client
- Uptime
- 100%
- last 30 days
- Response time
- 484 ms
- 834 ms slowest 5%
- Last check
- Passed
- 2 h ago, next in 5 h
Reliability
Status and outage history · Atom feed · Watch with other listings
How to connect
Add it to any MCP client that supports remote servers.
{
"mcpServers": {
"model-ruler-ai-cost-calculators": {
"type": "http",
"url": "https://modelruler.dev/mcp?dist=model_everywhere_registry_native_official_registry"
}
}
}12 tools
- token-counter
Use when a user asks how many tokens a given text will consume, or needs to estimate prompt size before pricing a workload. Given text and tokenizer family, returns low/high token range and byte-level measurements.
- provider-cost-calculator
Use when a user asks what an LLM workload costs on a specific provider/model, or wants to compare cost across providers. Given tokens per call and call volume, returns monthly cost plus a tier comparison table.
- self-host-breakeven-calculator
Use when a user is deciding between API usage and self-hosted GPU inference at a given volume. Returns breakeven token volume, monthly cost comparison, and go/no-go recommendation.
- context-window-planner
Use when a user needs to know whether a document plus prompt plus output fits within a model's context window, or wants a strategy recommendation (truncate/summarize/rag/chunk).
- quantization-calculator
Use when a user is planning to quantize an LLM to fit on smaller hardware. Given parameter count and precision transition, returns VRAM requirement, speedup estimate, and approximate quality delta.
- fine-tune-roi-calculator
Use when a user is considering fine-tuning vs prompt engineering. Returns training cost, monthly inference savings, months-to-ROI, and breakeven volume.
- eval-cost-calculator
Use when a user needs to budget an LLM evaluation run. Given samples/models/trials, returns total cost, per-run cost, and parallel time estimate.
- observability-cost-calculator
Use when a user needs to budget LLM observability tooling. Returns monthly cost at given request volume with retention adjustment.
- rag-pipeline-cost-calculator
Use when a user needs end-to-end RAG cost estimation (embedding + vector store + generation). Returns monthly cost with breakdown and dominant-component identification.
- automation-cost-calculator
Use for generic or non-agent recurring workflow platform billing across Zapier task billing, Make credit billing, and n8n execution billing. Use agent-workflow-cost-calculator instead when the workflow is explicitly an AI agent with app actions or MCP tool calls. Use…
- agent-workflow-cost-calculator
Use for automation-platform/iPaaS cost of an AI agent workflow, including app-action fan-out and MCP tool-call accounting, explicitly excluding LLM token spend. Use automation-cost-calculator for generic non-agent workflow billing. Use agent-loop-cost-calculator for LLM…
- agent-loop-cost-calculator
Use for LLM inference/reasoning cost per successful multi-step agent task, including failure overhead and context growth across turns. Use agent-workflow-cost-calculator for iPaaS/app-action/MCP orchestration fees. Use automation-cost-calculator for generic Zapier/Make/n8n…
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Recent checks
| When | Result | HTTP | Time |
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| 2 h ago | Passed | 200 | 471 ms |
| 13 h ago | Passed | 200 | 582 ms |
| 25 h ago | Passed | 200 | 376 ms |
| 40 h ago | Passed | 200 | 454 ms |
| 2 days ago | Passed | 200 | 487 ms |
Show 10 older checks
| 3 days ago | Passed | 200 | 350 ms |
| 4 days ago | Passed | 200 | 535 ms |
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| 5 days ago | Passed | 200 | 379 ms |
| 5 days ago | Passed | 200 | 612 ms |
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| 6 days ago | Passed | 200 | 619 ms |
| 7 days ago | Passed | 200 | 485 ms |
| 7 days ago | Passed | 200 | 384 ms |
| 8 days ago | Passed | 200 | 484 ms |