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Halowerk Model Router
x402
Halowerk Model Router 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).
Scores every catalogue LLM against a given task and returns a ranked shortlist with per-model cost estimates, sub-scores, and exclusion reasons for models that can't fit the input.
Price / call$0.002
Success—
StatusUnknown
How this service works
Scores every catalogue model against one task and returns a ranked shortlist. You state the task kind, optionally a per-call budget in USD, how much speed matters, the input size and any vendor restriction; the answer names a model, the estimated cost per call, and the sub-scores it was chosen on, so the ranking can be checked rather than trusted. Models that cannot hold the input are excluded and listed separately with the reason. Weights are yours to set and are echoed back.
Output
A ranked shortlist of LLMs scored against the specified task, each entry including the model name, estimated cost per call, and sub-scores (e.g. cost, speed, context fit). Models that cannot accommodate the input size are listed separately with the reason for exclusion. The caller's weights are echoed back for auditability.
Example use cases
Budget-constrained summarization model selection
“I need to pick the cheapest model that can handle a 50,000-token legal document summarization task, with a hard cap of $0.01 per call — rank all candidates and tell me which ones can't fit the input and why.”
Real-time chatbot model recommendation
“I'm building a real-time customer support chatbot and need a fast model for short conversational inputs under 2000 tokens, with a budget of $0.002 per call — which model scores best if I weight speed at 0.7 and cost at 0.3?”
Vendor-restricted code generation routing
“Find the best model for a code generation task using only Anthropic or Mistral models, input size is around 10,000 tokens, and I don't have a strict budget cap but want the most cost-efficient option — give me the full ranked list with sub-scores.”
Technical details
Endpoint
POSThttps://modell.halowerk.com/v1/model-routerWhen to prefer
Choose this endpoint when an agent or developer needs to programmatically select the best LLM for a specific task rather than hardcoding a model. It is especially valuable when cost, speed, and context window all matter and need to be traded off transparently. Prefer it over manual model comparison when the model catalogue changes frequently or when vendor restrictions need to be enforced automatically.
Side effects
- No models in catalogue fit within the specified budget — empty shortlist returned with explanation
- Input size exceeds all available models' context windows — all candidates excluded with context-limit reasons
- Invalid task kind enum value — validation error returned
- Malformed weight values (e.g. do not sum to 1) — error or normalization warning returned
- Network timeout or service unavailability — HTTP 5xx error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| task | string | What the model has to do. |
| weights | object | Weighting of cost, capability and speed. Normalised to sum 1. |
| input_text | string | Sample input. Used to estimate input_tokens if that is not given. |
| input_tokens | integer | Expected input size in tokens. |
| require_tags | array | Capabilities the model must carry, e.g. vision. |
| output_tokens | integer | Expected output length. Defaults to a value typical for the task. |
| speed_priority | string | How much latency matters. |
| allowed_vendors | array | Restrict to these vendors, e.g. for a data-residency or procurement rule. |
| excluded_vendors | array | Exclude these vendors. |
| budget_usd_per_call | number | Ceiling per call. Models above it are excluded. |
Tags
x402
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