modell.halowerk.com LLM Cost Estimator

x402

modell.halowerk.com LLM Cost Estimator is a paid API for AI agents from modell.halowerk.com, paid per call via x402, $0.002/call, status unknown (last checked 2026-09-14).

Estimates the total API cost for a given LLM call by computing input, output, cache-read, and cache-write costs across models based on text or token counts.

Price / call$0.002

Seller volume →—

Success—

StatusUnknown

How this service works

Works out what a call would cost. Give either the text itself or a token count, plus the expected output length, and get input, output, cache-read and cache-write cost per model with the total. Token counts derived from text are estimates from character and word statistics, not a tokeniser, and typically land within about 15 percent — where an exact count matters, count with the vendor tokeniser.

Output

A breakdown of estimated costs per model including input cost, output cost, cache-read cost, cache-write cost, and total cost. Token counts are estimated from character and word statistics if raw text is provided (within ~15% accuracy), or taken directly if a token count is supplied.

Example use cases

Pre-flight cost check for a long prompt

“Before I send this 8,000-token system prompt plus user message to the API, can you estimate what the input and output costs will be, assuming a 1,000-token response? Break it down by model so I can pick the cheapest one.”

Budget planning for a cached RAG pipeline

“I'm building a RAG pipeline where I'll cache a 50,000-token knowledge base and send 200-token queries expecting 300-token answers. How much will each call cost per model once the cache is warm, including cache-read and cache-write fees?”

Comparing model costs for a customer support bot

“My support bot handles about 500 messages a day, each with a 1,200-token input and 400-token output. Can you estimate the daily cost across different models so I can see which one gives me the best price?”

Technical details

Endpoint

POSThttps://modell.halowerk.com/v1/cost-estimate

When to prefer

Use this endpoint when you need a fast, pre-call cost estimate for one or more LLM API calls — especially useful for budget planning, model selection, or pipeline cost analysis. It is ideal when exact tokenization is not critical and a ~15% estimate is acceptable; for exact token counts, tokenize with the vendor's tokenizer first and supply the count directly. Prefer this over the model comparison catalogue endpoint when you have a specific prompt or token count and want cost figures rather than a feature comparison.

Side effects

Missing both text and token count — request must supply one or the other
Invalid or unrecognized model name — returns error or excludes that model from results
Negative or zero output length provided — may return validation error
Very short text producing low-confidence token estimates — accuracy degrades below ~15% bound
Network timeout if request payload is extremely large

Input

Schema · Request body

Field	Type	Description
text	string	The prompt text. Either this or input_tokens.
batch	boolean	Apply the batch discount where the model has one.
calls	integer	Number of identical calls to multiply by.
models	array	Model ids to price. All known models if omitted.
input_tokens	integer	Known input token count. Either this or text.
output_tokens	integer	Expected output length in tokens.
cached_input_tokens	integer	Of the input tokens, how many are served from cache.

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