8.1
Intelligence Index
Above 26% of 46 other free models
Me
Meta: Llama 4 Scout
Free allowance
Up to10,000neurons / day
via Cloudflare
Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimodal input...
- Input
- text
- image
- Output
- text
- 1.31M context
Providers
Available through 1 free provider. Use the model ID and API settings below to connect.
* The provider match may differ from this model. Check its docs for details.
Benchmarks
Compare scores and explore results by category.
8.2
Coding Index
Above 12% of 33 other free models
0.5
Agentic Index
Above 3% of 28 other free models
Bars show scores from other free models on this site. The marker shows this model’s score. Comparisons include only models with a score for that index.
Scores from Artificial AnalysisFrequently asked questions
Free access, setup, and what to expect.
Llama 4 Scout is available with up to 10,000 neurons / day free through Cloudflare. Free allowances can change. Check the Llama 4 Scout provider limits before you start.
To use Llama 4 Scout, choose one of the listed Llama 4 Scout API providers and follow the provider’s account and API-key setup guide. Copy the Llama 4 Scout model ID and connection settings for your chosen provider into your app or API client. Model IDs can differ between providers. API requests go directly to the provider; Free Models is a comparison site.
Llama 4 Scout accepts text and image as listed input formats. Listed output formats include text. Image or audio input support does not imply image or audio generation. Check the chosen provider’s Llama 4 Scout documentation for supported file types and request formats.
Llama 4 Scout has a listed context window of 1.31M tokens. Tokens are small pieces of content rather than a word count. Instructions, conversation history, and other inputs use context space, and the response also needs room. The maximum output length for Llama 4 Scout may be smaller than the context window and can vary by provider.
Llama 4 Scout has tool calling support listed; reasoning support isn’t listed. Reasoning enables additional processing for complex problems. Tool calling allows a model to request functions that your app executes. Check the chosen provider’s documentation for capability availability and setup.
Review the listed Llama 4 Scout benchmark results to compare performance on measured tasks. Compare scores within the same benchmark: coding indexes, Elo ratings, and win rates measure different things. The index comparison charts include only scored free models listed on Free Models. Evaluate Llama 4 Scout on examples from your own task alongside context size and provider limits.