# Ai Model Pricing Availability (`haehnchen/ai-model-pricing-availability`) Actor Compare AI model prices across providers. Find where a LLM model is available and compare input/output pricing. - **URL**: https://apify.com/haehnchen/ai-model-pricing-availability.md - **Developed by:** [Haehnchen](https://apify.com/haehnchen) (community) - **Categories:** AI - **Stats:** 2 total users, 1 monthly users, 85.7% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $90.00 / 1,000 model pricing results 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.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.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/platform/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 Model Pricing / Availability Compare AI model prices across **~200 providers**. Find where a LLM model is available and compare input/output pricing in real time. ### What it does Search for any LLM model by name and get pricing data from all providers that offer it. The search is normalized — you can search by model name, slug, or common aliases (e.g. `claude sonnet 5`, `sonnet5`, `Claude Sonnet 5` all find the same model). Compare input and output costs per **1 million tokens**, see which providers have free tiers, and find direct links to each provider. ### Providers Data is aggregated from **~200 providers** including: Requesty, AIHubMix, Writingmate, OpenRouter, Nano-GPT, Kilo Code, Cline, Krater, ValorGPT, AIMLAPI, 302.AI, Featherless, Fireworks AI, Poe, Together AI, Cursor, Azure AI Services, Windsurf, Novita AI, OrcaRouter, Routeway, FastRouter, NavyAI, Atlas Cloud, ZenMUX, CometAPI, Airforce API, Eurouter, LLM Stats, Vercel AI Gateway, Arena AI, Nous Research, ApiYI, WaveSpeed AI, LLM Gateway, Auriko ### How to use Run the Actor via API with your query: ```bash curl -X POST "https://api.apify.com/v2/acts//runs" \ -H "Authorization: Bearer " \ -H "Content-Type: application/json" \ -d '{"q": "claude sonnet 5"}' ```` #### Input | Parameter | Type | Required | Description | |-----------|--------|----------|--------------------------------| | `q` | string | yes | Model name, slug, or alias (min 3 chars) | #### Search examples All of these find the same model: - `claude sonnet 5` - `sonnet5` - `Claude Sonnet 5` These also work: - `grok 4.3` / `grok43` - `kimi k2.7` / `kimik27` - `glm-5.2` / `glm52` - `gpt-5.5` / `gpt55` - `fable 5` / `fable5` - `deepseek v4` / `deepseek-v4-pro-max` - `qwen3.7` / `qwen37` - `gemini 3.5` / `gemini35` #### Output Each result is saved as a dataset item: ```json { "name": "Claude Sonnet 5", "providers": [ { "provider": "Anthropic", "inputPrice": 3.00, "outputPrice": 15.00, "isFree": true, "originalModel": "claude-sonnet-5", "link": "https://docs.anthropic.com/en/docs/about-claude/models" }, { "provider": "OpenRouter", "inputPrice": 3.00, "outputPrice": 15.00, "isFree": false, "originalModel": "anthropic/claude-sonnet-5", "link": "https://openrouter.ai/anthropic/claude-sonnet-5" } ] } ``` #### Output fields | Field | Type | Description | |-------|------|-------------| | `name` | string | Display name of the model | | `providers` | array | Providers offering this model, sorted by input price | | `providers[].provider` | string | Provider name | | `providers[].inputPrice` | number | Input price per **1M tokens** (USD) | | `providers[].outputPrice` | number | Output price per **1M tokens** (USD) | | `providers[].isFree` | boolean | Whether the model is free on this provider | | `providers[].originalModel` | string | Model identifier on the provider | | `providers[].link` | string | Direct link to the model on the provider | #### Billing You are charged per dataset item returned (max 3 per request). ### Examples #### JavaScript (Apify Client) ```javascript import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: '' }); const run = await client.actor('').call({ q: 'claude sonnet 5' }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(items); ``` #### cURL ```bash ## Start the run curl -X POST "https://api.apify.com/v2/acts//runs" \ -H "Authorization: Bearer " \ -H "Content-Type: application/json" \ -d '{"q": "claude sonnet 5"}' ## Get results (use datasetId from the response) curl "https://api.apify.com/v2/datasets//items?format=json" ``` #### Python ```python from apify_client import ApifyClient client = ApifyClient("") run = client.actor("").call(input={"q": "claude sonnet 5"}) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) ``` # Actor input Schema ## `q` (type: `string`): Model name, slug, or alias (e.g. 'claude sonnet 5', 'grok 4.3', 'gpt-5.5') ## Actor input object example ```json { "q": "claude sonnet 5" } ``` # 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 = { "q": "claude sonnet 5" }; // Run the Actor and wait for it to finish const run = await client.actor("haehnchen/ai-model-pricing-availability").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 = { "q": "claude sonnet 5" } # Run the Actor and wait for it to finish run = client.actor("haehnchen/ai-model-pricing-availability").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 '{ "q": "claude sonnet 5" }' | apify call haehnchen/ai-model-pricing-availability --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=haehnchen/ai-model-pricing-availability", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Ai Model Pricing Availability", "description": "Compare AI model prices across providers. Find where a LLM model is available and compare input/output pricing.", "version": "1.0", "x-build-id": "TvqbUdDTvAVhGExxE" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/haehnchen~ai-model-pricing-availability/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-haehnchen-ai-model-pricing-availability", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/haehnchen~ai-model-pricing-availability/runs": { "post": { "operationId": "runs-sync-haehnchen-ai-model-pricing-availability", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/haehnchen~ai-model-pricing-availability/run-sync": { "post": { "operationId": "run-sync-haehnchen-ai-model-pricing-availability", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "q" ], "properties": { "q": { "title": "Search query", "minLength": 3, "type": "string", "description": "Model name, slug, or alias (e.g. 'claude sonnet 5', 'grok 4.3', 'gpt-5.5')" } } }, "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 } } } } } } } } } } ```