# AI API Pricing & Model Lifecycle Report (`taroyamada/ai-api-pricing-model-lifecycle-report`) Actor Compare and watch official public pricing, model, deprecation, and release-note pages for OpenAI, Anthropic, and Gemini without API keys or model calls. - **URL**: https://apify.com/taroyamada/ai-api-pricing-model-lifecycle-report.md - **Developed by:** [naoki anzai](https://apify.com/taroyamada) (community) - **Categories:** Business, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $10.00 / 1,000 ai model price rows This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## AI API Pricing & Model Lifecycle Report This Apify Actor compares and watches official public pricing, model, deprecation, and release-note pages for three v1 providers: OpenAI, Anthropic, and Gemini. It does not accept API keys, call model endpoints, send prompts, or use provider APIs. It emits source-linked normalized observations and arithmetic monthly token-cost scenarios from the `usageProfiles` input. ### Quickstart Use `initialRunMode: "baseline_only"` for the first scheduled run. A complete source bundle is stored and the run emits zero rows and zero charges. The next run can use `mode: "watch"` with the same input. With `emitUnchanged: false`, an identical source snapshot emits zero rows and zero charges. ```json { "providers": ["openai", "anthropic", "gemini"], "models": ["openai:gpt-4o", "anthropic:claude-sonnet-4-20250514", "gemini:gemini-2.5-flash"], "usageProfiles": [ { "name": "standard-month", "inputUnits": 1000000, "outputUnits": 250000, "cacheUnits": 100000 } ], "mode": "compare", "initialRunMode": "emit_current", "generateReport": true, "emitRawRows": true, "emitUnchanged": false, "maxChargeUsd": 12, "dryRun": false } ```` `dryRun: true` uses deterministic local sample rows and never fetches a page or charges PPE. The fixture-backed parsers used by the test suite live under `fixtures/`. ### Output Rows The shared deploy integration expects these exact `rowType` values: - `ai_model_price_row`: one normalized model pricing record when `emitRawRows` is enabled. - `ai_model_lifecycle_alert`: an official deprecation or shutdown observation. - `ai_api_cost_comparison_report`: an aggregate report with `providerCount`, `scenarioCount`, `sourceUrl`, and an explicit `comparisonStatus`; rows with unpriced cache units set `monthlyCostUsd` to `null` and are not rankable. - `ai_model_migration_report`: emitted only when an official source explicitly names a replacement; it contains `provider`, `modelId`, `replacementModelId`, and `sourceUrl`. - `ai_pricing_export`: an export handoff emitted with raw model rows. Every row has a stable identity, provider, source URL, normalized model fields, retrieval time, limitations, and prohibited interpretations. No recommendation or inferred replacement field is emitted. ### Inputs - `providers`: `openai`, `anthropic`, and/or `gemini` only. - `models`: optional exact IDs, `provider:modelId` selectors, or `*`/`?` wildcard selectors. - `filters`: status, modality, context-window, deprecation, and model ID filters. - `usageProfiles`: monthly `inputUnits`, `outputUnits`, and `cacheUnits`; optional cache read/write splits are supported, and an omitted cache quantity means zero. - `mode`: `compare` or `watch`. - `initialRunMode`: `baseline_only` or `emit_current`. - `generateReport`, `emitRawRows`, `emitUnchanged`, `maxChargeUsd`, and `dryRun` control delivery and billing. ### PPE Pricing There is no start charge. Only rows actually delivered through configured PPE events are billable: | Event | Row type | Price | | --- | --- | ---: | | `ai-model-price-row` | `ai_model_price_row` | $0.01 | | `ai-model-lifecycle-alert` | `ai_model_lifecycle_alert` | $0.25 | | `ai-api-cost-comparison-report` | `ai_api_cost_comparison_report` | $3.00 | | `ai-model-migration-report` | `ai_model_migration_report` | $5.00 | | `ai-pricing-export` | `ai_pricing_export` | $2.00 | The delivery layer validates the complete row batch before the first push, rejects unknown event names or mismatched row types, and refuses to deliver an Apify runtime row unless the provider returns `chargedCount >= 1`. `maxChargeUsd` is an all-or-nothing pre-delivery budget. ### Source and Safety Boundaries Only hard-coded official provider source manifests are accepted. The pricing, models, and dedicated lifecycle pages are required; release notes are optional corroborating evidence and never override a dedicated lifecycle page. The web guard checks public network targets, robots policy, response size, timeout, redirect count, and actual access-challenge markers. Normal navigation text such as `Sign in` or `Contact sales` is not itself a challenge. Structural truncation, declared-count undercoverage, partial markers, blocked pages, and non-USD pricing fail closed. A rejected bundle is skipped, its prior provider and model state is not overwritten, and no row is charged for it. Lifecycle statuses are copied only from explicit lifecycle evidence. `No shutdown date announced` does not create a shutdown, and a model removed from a complete catalog is reported as absent rather than silently reclassified. A later catalog reappearance is emitted as a separate lifecycle change. `dryRun` rows use `sourceMethod: "local_deterministic_fixture"` and `sourceProvenance: "not_fetched_local_fixture"`; their official URLs are references only and were not fetched. Read [source compliance](docs/source-compliance.md), [integration guide](docs/integration-guide.md), and [store competitive snapshot](docs/store-competitive-snapshot.md) for operational details. ### Local Tests ```bash npm test ``` The suite uses only local fixtures and covers adapters, normalization, cost arithmetic, baseline/watch state, partial-source fail-closed behavior, robots and access challenges, exact row types, budget enforcement, and PPE charge capture. # Actor input Schema ## `providers` (type: `array`): v1 provider adapters. Only OpenAI, Anthropic, and Gemini are supported. ## `models` (type: `array`): Optional exact model IDs, provider:model selectors, or glob selectors. Empty means all models found in the selected providers. ## `filters` (type: `object`): Optional status, modality, and context-window filters. ## `usageProfiles` (type: `array`): Monthly input, output, and cache token units used for source-linked cost comparisons. Values are token counts, not API calls. ## `mode` (type: `string`): Compare current official prices or watch for source-backed changes. ## `initialRunMode` (type: `string`): baseline\_only stores a complete source baseline with zero rows; emit\_current emits current rows/reports on an empty baseline. ## `generateReport` (type: `boolean`): Emit an aggregate cost-comparison report when eligible current or changed source data exists. ## `emitUnchanged` (type: `boolean`): When false, identical watch snapshots emit zero rows and zero charges. ## `emitRawRows` (type: `boolean`): Emit one normalized ai\_model\_price\_row per eligible model and an ai\_pricing\_export handoff row. ## `maxChargeUsd` (type: `number`): Optional all-or-nothing PPE budget. Zero means no actor-side budget cap. ## `dryRun` (type: `boolean`): Emit local fixture-derived sample rows without live fetches, model calls, or PPE charges. ## `snapshotKey` (type: `string`): Optional stable state namespace for separate watch baselines. ## Actor input object example ```json { "providers": [ "openai", "anthropic", "gemini" ], "models": [], "filters": {}, "usageProfiles": [ { "name": "standard-month", "inputUnits": 1000000, "outputUnits": 250000, "cacheUnits": 0 } ], "mode": "compare", "initialRunMode": "baseline_only", "generateReport": true, "emitUnchanged": false, "emitRawRows": false, "maxChargeUsd": 0, "dryRun": false, "snapshotKey": "" } ``` # Actor output Schema ## `results` (type: `string`): Rows written to the run default dataset, resolved from the run defaultDatasetId. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("taroyamada/ai-api-pricing-model-lifecycle-report").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("taroyamada/ai-api-pricing-model-lifecycle-report").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call taroyamada/ai-api-pricing-model-lifecycle-report --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=taroyamada/ai-api-pricing-model-lifecycle-report", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "AI API Pricing & Model Lifecycle Report", "description": "Compare and watch official public pricing, model, deprecation, and release-note pages for OpenAI, Anthropic, and Gemini without API keys or model calls.", "version": "0.1", "x-build-id": "9apTEB4qodc2joM7M" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/taroyamada~ai-api-pricing-model-lifecycle-report/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-taroyamada-ai-api-pricing-model-lifecycle-report", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/taroyamada~ai-api-pricing-model-lifecycle-report/runs": { "post": { "operationId": "runs-sync-taroyamada-ai-api-pricing-model-lifecycle-report", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/taroyamada~ai-api-pricing-model-lifecycle-report/run-sync": { "post": { "operationId": "run-sync-taroyamada-ai-api-pricing-model-lifecycle-report", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "providers": { "title": "Providers", "type": "array", "description": "v1 provider adapters. Only OpenAI, Anthropic, and Gemini are supported.", "items": { "type": "string" }, "default": [ "openai", "anthropic", "gemini" ] }, "models": { "title": "Models", "type": "array", "description": "Optional exact model IDs, provider:model selectors, or glob selectors. Empty means all models found in the selected providers.", "items": { "type": "string" }, "default": [] }, "filters": { "title": "Model filters", "type": "object", "description": "Optional status, modality, and context-window filters.", "properties": { "statuses": { "type": "array", "title": "Lifecycle statuses", "description": "Optional lifecycle status filters validated by the actor.", "items": { "type": "string" } }, "modalities": { "type": "array", "title": "Modalities", "description": "Optional modality filters such as text or image.", "items": { "type": "string" } }, "minContextWindowTokens": { "type": "integer", "title": "Minimum context tokens", "description": "Optional minimum official context-window size.", "minimum": 0 }, "maxContextWindowTokens": { "type": "integer", "title": "Maximum context tokens", "description": "Optional maximum official context-window size.", "minimum": 0 }, "includeDeprecated": { "type": "boolean", "title": "Include deprecated models", "description": "Include models listed by providers as deprecated or shut down.", "default": true }, "modelIds": { "type": "array", "title": "Exact model IDs", "description": "Optional exact model ID allowlist.", "items": { "type": "string" } } }, "default": {}, "additionalProperties": false }, "usageProfiles": { "title": "Monthly usage profiles", "type": "array", "description": "Monthly input, output, and cache token units used for source-linked cost comparisons. Values are token counts, not API calls.", "items": { "type": "object", "properties": { "name": { "type": "string", "title": "Profile name", "description": "Stable label for this monthly usage scenario." }, "inputUnits": { "type": "number", "title": "Input tokens", "description": "Monthly input token count.", "minimum": 0 }, "outputUnits": { "type": "number", "title": "Output tokens", "description": "Monthly output token count.", "minimum": 0 }, "cacheUnits": { "type": "number", "title": "Cache tokens", "description": "Legacy monthly cache token count; omitted means zero.", "minimum": 0 }, "monthlyInputUnits": { "type": "number", "title": "Monthly input tokens", "description": "Alias for monthly input token count.", "minimum": 0 }, "monthlyOutputUnits": { "type": "number", "title": "Monthly output tokens", "description": "Alias for monthly output token count.", "minimum": 0 }, "monthlyCacheUnits": { "type": "number", "title": "Monthly cache tokens", "description": "Alias for monthly cache token count.", "minimum": 0 }, "cacheReadUnits": { "type": "number", "title": "Cache read tokens", "description": "Monthly cache-read token count.", "minimum": 0 }, "cacheWriteUnits": { "type": "number", "title": "Cache write tokens", "description": "Monthly cache-write token count.", "minimum": 0 } }, "required": [ "name" ], "additionalProperties": false }, "default": [ { "name": "standard-month", "inputUnits": 1000000, "outputUnits": 250000, "cacheUnits": 0 } ] }, "mode": { "title": "Mode", "enum": [ "compare", "watch" ], "type": "string", "description": "Compare current official prices or watch for source-backed changes.", "default": "compare" }, "initialRunMode": { "title": "Initial run mode", "enum": [ "baseline_only", "emit_current" ], "type": "string", "description": "baseline_only stores a complete source baseline with zero rows; emit_current emits current rows/reports on an empty baseline.", "default": "baseline_only" }, "generateReport": { "title": "Generate comparison report", "type": "boolean", "description": "Emit an aggregate cost-comparison report when eligible current or changed source data exists.", "default": true }, "emitUnchanged": { "title": "Emit unchanged", "type": "boolean", "description": "When false, identical watch snapshots emit zero rows and zero charges.", "default": false }, "emitRawRows": { "title": "Emit raw model rows", "type": "boolean", "description": "Emit one normalized ai_model_price_row per eligible model and an ai_pricing_export handoff row.", "default": false }, "maxChargeUsd": { "title": "Maximum charge USD", "minimum": 0, "maximum": 100000, "type": "number", "description": "Optional all-or-nothing PPE budget. Zero means no actor-side budget cap.", "default": 0 }, "dryRun": { "title": "Dry run", "type": "boolean", "description": "Emit local fixture-derived sample rows without live fetches, model calls, or PPE charges.", "default": false }, "snapshotKey": { "title": "State namespace", "type": "string", "description": "Optional stable state namespace for separate watch baselines.", "default": "" } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```