--- title: llama-4-scout-17b-16e-instruct description: Meta's Llama 4 Scout is a 17 billion parameter model with 16 experts that is natively multimodal. These models leverage a mixture-of-experts architecture to offer industry-leading performance in text and image understanding. image: https://developers.cloudflare.com/dev-products-preview.png --- > Documentation Index > Fetch the complete documentation index at: https://developers.cloudflare.com/workers-ai/llms.txt > Use this file to discover all available pages before exploring further. [Skip to content](#%5Ftop) ![Meta logo](https://developers.cloudflare.com/_astro/meta.BR4nfp35.svg) # llama-4-scout-17b-16e-instruct Text Generation • Meta `@cf/meta/llama-4-scout-17b-16e-instruct` Meta's Llama 4 Scout is a 17 billion parameter model with 16 experts that is natively multimodal. These models leverage a mixture-of-experts architecture to offer industry-leading performance in text and image understanding. | Model Info | | | ------------------------------------------------------------------------------------ | ------------------------------------------------------------------------------------ | | Context Window[ ↗](https://developers.cloudflare.com/workers-ai/glossary/) | 131,000 tokens | | Terms and License | [link ↗](https://github.com/meta-llama/llama-models/blob/main/models/llama4/LICENSE) | | Function calling [ ↗](https://developers.cloudflare.com/workers-ai/function-calling) | Yes | | Vision | Yes | | Batch | Yes | | Unit Pricing | $0.27 per M input tokens, $0.85 per M output tokens | ## Playground Try out this model with Workers AI LLM Playground. It does not require any setup or authentication and an instant way to preview and test a model directly in the browser. [ Launch the LLM Playground ](https://playground.ai.cloudflare.com/?model=@cf/meta/llama-4-scout-17b-16e-instruct) ## Usage * [ Worker (Streaming) ](#tab-panel-5184) * [ TypeScript ](#tab-panel-5185) * [ Python ](#tab-panel-5186) * [ curl ](#tab-panel-5187) TypeScript ``` export interface Env { AI: Ai;} export default { async fetch(request, env): Promise { const messages = [ { role: "system", content: "You are a friendly assistant" }, { role: "user", content: "What is the origin of the phrase Hello, World", }, ]; const stream = await env.AI.run("@cf/meta/llama-4-scout-17b-16e-instruct", { messages, stream: true, }); return new Response(stream, { headers: { "content-type": "text/event-stream" }, }); },} satisfies ExportedHandler; ``` ``` export interface Env { AI: Ai;} export default { async fetch(request, env): Promise { const messages = [ { role: "system", content: "You are a friendly assistant" }, { role: "user", content: "What is the origin of the phrase Hello, World", }, ]; const response = await env.AI.run("@cf/meta/llama-4-scout-17b-16e-instruct", { messages }); return Response.json(response); },} satisfies ExportedHandler; ``` ``` import osimport requests ACCOUNT_ID = "your-account-id"AUTH_TOKEN = os.environ.get("CLOUDFLARE_AUTH_TOKEN") prompt = "Tell me all about PEP-8"response = requests.post( f"https://api.cloudflare.com/client/v4/accounts/{ACCOUNT_ID}/ai/run/@cf/meta/llama-4-scout-17b-16e-instruct", headers={"Authorization": f"Bearer {AUTH_TOKEN}"}, json={ "messages": [ {"role": "system", "content": "You are a friendly assistant"}, {"role": "user", "content": prompt} ] })result = response.json()print(result) ``` Terminal window ``` curl https://api.cloudflare.com/client/v4/accounts/$CLOUDFLARE_ACCOUNT_ID/ai/run/@cf/meta/llama-4-scout-17b-16e-instruct \ -X POST \ -H "Authorization: Bearer $CLOUDFLARE_AUTH_TOKEN" \ -d '{ "messages": [{ "role": "system", "content": "You are a friendly assistant" }, { "role": "user", "content": "Why is pizza so good" }]}' ``` OpenAI compatible endpoints Workers AI also supports OpenAI compatible API endpoints for `/v1/chat/completions` and `/v1/embeddings`. For more details, refer to [Configurations ](https://developers.cloudflare.com/workers-ai/configuration/open-ai-compatibility/). ## Parameters Synchronous — Send a request and receive a complete response * [ Input ](#tab-panel-5188) * [ Output ](#tab-panel-5189) prompt `string`requiredminLength: 1The input text prompt for the model to generate a response. guided\_json{} `object`JSON schema that should be fulfilled for the response. ▶response\_format{} `object` raw `boolean`default: falseIf true, a chat template is not applied and you must adhere to the specific model's expected formatting. stream `boolean`default: falseIf true, the response will be streamed back incrementally using SSE, Server Sent Events. max\_tokens `integer`default: 256The maximum number of tokens to generate in the response. temperature `number`default: 0.15minimum: 0maximum: 5Controls the randomness of the output; higher values produce more random results. top\_p `number`minimum: 0maximum: 2Adjusts the creativity of the AI's responses by controlling how many possible words it considers. Lower values make outputs more predictable; higher values allow for more varied and creative responses. top\_k `integer`minimum: 1maximum: 50Limits the AI to choose from the top 'k' most probable words. Lower values make responses more focused; higher values introduce more variety and potential surprises. seed `integer`minimum: 1maximum: 9999999999Random seed for reproducibility of the generation. repetition\_penalty `number`minimum: 0maximum: 2Penalty for repeated tokens; higher values discourage repetition. frequency\_penalty `number`minimum: 0maximum: 2Decreases the likelihood of the model repeating the same lines verbatim. presence\_penalty `number`minimum: 0maximum: 2Increases the likelihood of the model introducing new topics. response `string`The generated text response from the model ▶usage{} `object`Usage statistics for the inference request ▶tool\_calls\[\] `array`An array of tool calls requests made during the response generation Streaming — Send a request with \`stream: true\` and receive server-sent events * [ Input ](#tab-panel-5190) * [ Output ](#tab-panel-5191) prompt `string`requiredminLength: 1The input text prompt for the model to generate a response. guided\_json{} `object`JSON schema that should be fulfilled for the response. ▶response\_format{} `object` raw `boolean`default: falseIf true, a chat template is not applied and you must adhere to the specific model's expected formatting. stream `boolean`default: falseIf true, the response will be streamed back incrementally using SSE, Server Sent Events. max\_tokens `integer`default: 256The maximum number of tokens to generate in the response. temperature `number`default: 0.15minimum: 0maximum: 5Controls the randomness of the output; higher values produce more random results. top\_p `number`minimum: 0maximum: 2Adjusts the creativity of the AI's responses by controlling how many possible words it considers. Lower values make outputs more predictable; higher values allow for more varied and creative responses. top\_k `integer`minimum: 1maximum: 50Limits the AI to choose from the top 'k' most probable words. Lower values make responses more focused; higher values introduce more variety and potential surprises. seed `integer`minimum: 1maximum: 9999999999Random seed for reproducibility of the generation. repetition\_penalty `number`minimum: 0maximum: 2Penalty for repeated tokens; higher values discourage repetition. frequency\_penalty `number`minimum: 0maximum: 2Decreases the likelihood of the model repeating the same lines verbatim. presence\_penalty `number`minimum: 0maximum: 2Increases the likelihood of the model introducing new topics. type `string` contentType `text/event-stream` format `binary` Batch — Send multiple requests in a single API call * [ Input ](#tab-panel-5192) * [ Output ](#tab-panel-5193) ▶requests\[\] `array`required response `string`The generated text response from the model ▶usage{} `object`Usage statistics for the inference request ▶tool\_calls\[\] `array`An array of tool calls requests made during the response generation ## API Schemas (Raw) Synchronous Input [ ](https://developers.cloudflare.com/workers-ai/models/llama-4-scout-17b-16e-instruct/sync-input.json "Open") [ ](https://developers.cloudflare.com/workers-ai/models/llama-4-scout-17b-16e-instruct/sync-input.json "Download") Synchronous Output [ ](https://developers.cloudflare.com/workers-ai/models/llama-4-scout-17b-16e-instruct/sync-output.json "Open") [ ](https://developers.cloudflare.com/workers-ai/models/llama-4-scout-17b-16e-instruct/sync-output.json "Download") Streaming Input [ ](https://developers.cloudflare.com/workers-ai/models/llama-4-scout-17b-16e-instruct/streaming-input.json "Open") [ ](https://developers.cloudflare.com/workers-ai/models/llama-4-scout-17b-16e-instruct/streaming-input.json "Download") Streaming Output [ ](https://developers.cloudflare.com/workers-ai/models/llama-4-scout-17b-16e-instruct/streaming-output.json "Open") [ ](https://developers.cloudflare.com/workers-ai/models/llama-4-scout-17b-16e-instruct/streaming-output.json "Download") Batch Input [ ](https://developers.cloudflare.com/workers-ai/models/llama-4-scout-17b-16e-instruct/batch-input.json "Open") [ ](https://developers.cloudflare.com/workers-ai/models/llama-4-scout-17b-16e-instruct/batch-input.json "Download") Batch Output [ ](https://developers.cloudflare.com/workers-ai/models/llama-4-scout-17b-16e-instruct/batch-output.json "Open") [ ](https://developers.cloudflare.com/workers-ai/models/llama-4-scout-17b-16e-instruct/batch-output.json "Download") ```json {"@context":"https://schema.org","@type":"TechArticle","@id":"https://developers.cloudflare.com/workers-ai/models/llama-4-scout-17b-16e-instruct/#page","headline":"llama-4-scout-17b-16e-instruct (Meta) · Cloudflare AI docs · Cloudflare Workers AI docs","description":"Meta's Llama 4 Scout is a 17 billion parameter model with 16 experts that is natively multimodal. 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