Llama 4 Scout
SOTA 109B model with 17B active params & large context, excelling at multi-document analysis, codebase reasoning, and personalized tasks.
About model
Together AI offers day 1 support for the new Llama 4 multilingual vision models that can analyze multiple images and respond to queries about them.
Register for a Together AI account to get an API key. New accounts come with free credits to start. Install the Together AI library for your preferred language.
Model | FrontierMath Tier 4 | GPQA Diamond | HLE | SciCode | GDPval-AA | Terminal-Bench 2.1 | Agent Arena | FrontierCode | DeepSWE |
|---|---|---|---|---|---|---|---|---|---|
Llama 4 Scout | 51.8% | Related open-source models | Competitor closed-source models | ||||||
87.8% | 92.6% | 53% | 60% | 62% | 85% | 53.5% | 70% | ||
73.2% | 93.2% | 53% | 56% | 68% | 89% | +16.4pp | 53.4% | 74% | |
82.9% | 94.1% | 47% | 56% | 61% | 88% | 47.5% | 73% | ||
24.4% | 93.1% | 40% | 54% | 51% | 82% | +4.2pp | 42.4% | 54% | |
61.0% | 91.1% | 37% | 53% | 54% | 81% | 39.8% | 67% |
How to use model
Input
from together import Together client = Together() # API key via api_key param or TOGETHER_API_KEY env var # Query image with Llama 4 Scout model response = client.chat.completions.create( model="meta-llama/Llama-4-Scout-17B-16E-Instruct", messages=[{ "role": "user", "content": [ {"type": "text", "text": "What can you see in this image?"}, {"type": "image_url", "image_url": {"url": "https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png"}} ] }] ) print(response.choices[0].message.content)Output
The image depicts a serene landscape of Yosemite National Park, featuring a river flowing through a valley surrounded by towering cliffs and lush greenery. * **River:** * The river is calm and peaceful, with clear water that reflects the surrounding scenery. * It flows gently from the bottom-left corner to the center-right of the image. * The riverbank is lined with rocks and grasses, adding to the natural beauty of the scene. * **Cliffs:** * The cliffs are massive and imposing, rising steeply from the valley floor. * They are composed of light-colored rock, possibly granite, and feature vertical striations. * The cliffs are covered in trees and shrubs, which adds to their rugged charm. * **Trees and Vegetation:** * The valley is densely forested, with tall trees growing along the riverbanks and on the cliffsides. * The trees are a mix of evergreen and deciduous species, with some displaying vibrant green foliage. * Grasses and shrubs grow in the foreground, adding texture and color to the scene. * **Sky:** * The sky is a brilliant blue, with only a few white clouds scattered across it. * The sun appears to be shining from the right side of the image, casting a warm glow over the scene. In summary, the image presents a breathtaking view of Yosemite National Park, showcasing the natural beauty of the valley and its surroundings. The calm river, towering cliffs, and lush vegetation all contribute to a sense of serenity and wonder.Function Calling
Input
import os import json import openai client = openai.OpenAI( base_url = "https://api.together.ai/v1", api_key = os.environ['TOGETHER_API_KEY'], ) tools = [ { "type": "function", "function": { "name": "get_current_weather", "description": "Get the current weather in a given location", "parameters": { "type": "object", "properties": { "location": { "type": "string", "description": "The city and state, e.g. San Francisco, CA" }, "unit": { "type": "string", "enum": [ "celsius", "fahrenheit" ] } } } } } ] messages = [ {"role": "system", "content": "You are a helpful assistant that can access external functions. The responses from these function calls will be appended to this dialogue. Please provide responses based on the information from these function calls."}, {"role": "user", "content": "What is the current temperature of New York, San Francisco and Chicago?"} ] response = client.chat.completions.create( model="meta-llama/Llama-4-Scout-17B-16E-Instruct", messages=messages, tools=tools, tool_choice="auto", ) print(json.dumps(response.choices[0].message.model_dump()['tool_calls'], indent=2))Output
[ { "id": "call_1p75qwks0etzfy1g6noxvsgs", "function": { "arguments": "{\"location\":\"New York, NY\",\"unit\":\"fahrenheit\"}", "name": "get_current_weather" }, "type": "function" }, { "id": "call_aqjfgn65d0c280fjd3pbzpc6", "function": { "arguments": "{\"location\":\"San Francisco, CA\",\"unit\":\"fahrenheit\"}", "name": "get_current_weather" }, "type": "function" }, { "id": "call_rsg8muko8hymb4brkycu3dm5", "function": { "arguments": "{\"location\":\"Chicago, IL\",\"unit\":\"fahrenheit\"}", "name": "get_current_weather" }, "type": "function" } ]Query models with multiple images
Currently this model supports 5 images as input.
Input
# Multi-modal message with multiple images response = client.chat.completions.create( model="meta-llama/Llama-4-Scout-17B-16E-Instruct", messages=[{ "role": "user", "content": [ { "type": "text", "text": "Compare these two images." }, { "type": "image_url", "image_url": { "url": "https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png" } }, { "type": "image_url", "image_url": { "url": "https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/slack.png" } } ] }] ) print(response.choices[0].message.content)Output
The first image is a collage of multiple identical landscape photos showing a natural scene with rocks, trees, and a stream under a blue sky. The second image is a screenshot of a mobile app interface, specifically the navigation menu of the Canva app, which includes icons for Home, DMs (Direct Messages), Activity, Later, Canvases, and More. ### Comparison: 1. **Content**: - The first image focuses on a natural landscape. - The second image shows a digital interface from an app. 2. **Purpose**: - The first image could be used for showcasing nature, design elements in graphic work, or as a background. - The second image represents the functionality and layout of the Canva app's navigation system. 3. **Visual Style**: - The first image has vibrant colors and realistic textures typical of outdoor photography. - The second image uses flat design icons with a simple color palette suited for user interface design. 4. **Context**: - The first image is likely intended for artistic or environmental contexts. - The second image is relevant to digital design and app usability discussions.Model card
- Model String: meta-llama/Llama-4-Scout-17B-16E-Instruct
- Specs:
- 17B active parameters (109B total)
- 16-expert MoE architecture
- 327,680 context length (will be increased to 10M)
- Support for 12 languages: Arabic, English, French, German, Hindi, Indonesian, Italian, Portuguese, Spanish, Tagalog, Thai, and Vietnamese
- Multimodal capabilities (text + images)
- Support Function Calling
- Best for: Multi-document analysis, codebase reasoning, and personalized tasks
- Knowledge Cutoff: August 2024
Applications & use cases
- Multi-document summarization for legal/financial analysis: Analyze multiple legal contracts or financial statements simultaneously, identifying key terms, inconsistencies, and patterns across documents to generate comprehensive summaries and risk assessments.
- Personalized task automation using years of user data: Create tailored automation workflows by analyzing an individual's historical data patterns, communication style, and preferences, enabling highly personalized digital assistants that adapt to specific user needs.
- Efficient image parsing for multimodal applications: Process and understand image content in conjunction with text to power applications like visual search, content moderation, and accessibility features that require understanding the relationship between visual and textual elements.
- TypeChatVision
- Main use casesChatFunction CallingVision
- FeaturesFunction Calling
- Fine tuningSupported
- Deployment
- Parameters109B
- Context length1M
- Input price
$0.18 / 1M tokens
- Output price
$0.59 / 1M tokens
- Input modalitiesTextImage
- Output modalitiesText
- ReleasedApril 2, 2025
- Last updatedFebruary 5, 2026
- Quantization levelFP16
- External link
- CategoryChat
