Modellwerk
llm catalog diff
Use this when an agent has an older and a newer LLM catalog snapshot and needs a deterministic migration diff before changing routing or budgets. Rows are matched by vendor plus model, id or name. The result separates added, removed and changed models and reports field-level differences for input, output and cached-input price, context window and maximum output tokens.
POST https://modell.halowerk.com/v1/llm-catalog-diffEingaben
| Feld | Typ | Pflicht | Beschreibung |
|---|---|---|---|
| before | array | Ja | Older catalog snapshot. |
| after | array | Ja | Newer catalog snapshot. |
Vollständiges Eingabeschema anzeigen
{
"type": "object",
"required": [
"before",
"after"
],
"additionalProperties": false,
"properties": {
"before": {
"type": "array",
"minItems": 1,
"maxItems": 500,
"items": {
"type": "object",
"additionalProperties": true,
"anyOf": [
{
"required": [
"model"
]
},
{
"required": [
"id"
]
},
{
"required": [
"name"
]
}
],
"properties": {
"vendor": {
"type": "string",
"maxLength": 64,
"description": "Provider name. Empty is allowed when model identifiers are globally unique."
},
"model": {
"type": "string",
"minLength": 1,
"maxLength": 160
},
"id": {
"type": "string",
"minLength": 1,
"maxLength": 160
},
"name": {
"type": "string",
"minLength": 1,
"maxLength": 160
},
"input_price_per_million": {
"type": [
"number",
"null"
],
"minimum": 0
},
"output_price_per_million": {
"type": [
"number",
"null"
],
"minimum": 0
},
"cached_input_price_per_million": {
"type": [
"number",
"null"
],
"minimum": 0
},
"context_window": {
"type": [
"integer",
"null"
],
"minimum": 0
},
"max_output_tokens": {
"type": [
"integer",
"null"
],
"minimum": 0
}
}
},
"description": "Older catalog snapshot."
},
"after": {
"type": "array",
"minItems": 1,
"maxItems": 500,
"items": {
"type": "object",
"additionalProperties": true,
"anyOf": [
{
"required": [
"model"
]
},
{
"required": [
"id"
]
},
{
"required": [
"name"
]
}
],
"properties": {
"vendor": {
"type": "string",
"maxLength": 64,
"description": "Provider name. Empty is allowed when model identifiers are globally unique."
},
"model": {
"type": "string",
"minLength": 1,
"maxLength": 160
},
"id": {
"type": "string",
"minLength": 1,
"maxLength": 160
},
"name": {
"type": "string",
"minLength": 1,
"maxLength": 160
},
"input_price_per_million": {
"type": [
"number",
"null"
],
"minimum": 0
},
"output_price_per_million": {
"type": [
"number",
"null"
],
"minimum": 0
},
"cached_input_price_per_million": {
"type": [
"number",
"null"
],
"minimum": 0
},
"context_window": {
"type": [
"integer",
"null"
],
"minimum": 0
},
"max_output_tokens": {
"type": [
"integer",
"null"
],
"minimum": 0
}
}
},
"description": "Newer catalog snapshot."
}
},
"examples": [
{
"before": [
{
"vendor": "example-ai",
"model": "model-small",
"input_price_per_million": 1,
"output_price_per_million": 3,
"context_window": 32000
}
],
"after": [
{
"vendor": "example-ai",
"model": "model-small",
"input_price_per_million": 0.8,
"output_price_per_million": 3,
"context_window": 64000
}
]
}
]
}Veröffentlichtes Eingabebeispiel
{
"before": [
{
"vendor": "example-ai",
"model": "model-small",
"input_price_per_million": 1,
"context_window": 32000
}
],
"after": [
{
"vendor": "example-ai",
"model": "model-small",
"input_price_per_million": 0.8,
"context_window": 64000
}
]
}Ergebnis & Dokumentation
Veröffentlichtes Ergebnisschema anzeigen
{
"$ref": "https://modell.halowerk.com/v1/llm-catalog-diff/schema#/outputSchema"
}Veröffentlichtes Ergebnisbeispiel öffnen
Maschinenlesbare Dokumentation dieses Hubs
Quelle dieser Seite: der veröffentlichte HALOWERK-Katalog. Stand: 2026-11-01, 15:19 UTC.
Weitere Endpunkte dieses Hubs
- Modellwerk0,003 USDC
chat completions
POSThttps://modell.halowerk.com/v1/chat-completionsRuns openai/gpt-oss-20b via GroqCloud. Messages are sent to Groq Inc., USA; payment metadata is not forwarded. At most 8 messages, 8192 UTF-8 bytes overall and 1024 completion tokens including reasoning. A length finish_reason exposes trunc
- Modellwerk0,002 USDC
context plan
POSThttps://modell.halowerk.com/v1/context-planPlans the division of a long input for a given model. It reserves room for the system prompt, the expected answer and a safety margin, then works out how many chunks are needed and where to cut, preferring paragraph boundaries over line and
- Modellwerk0,002 USDC
cost estimate
POSThttps://modell.halowerk.com/v1/cost-estimateWorks 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 f