Back to Models

Meta: Llama 4 Scout InstructActive

meta/llama-4-scout-17b-16e-instruct
CompareChat

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 (text and image) and multilingual output (text and code) across 12 supported languages. Designed for assistant-style interaction and visual reasoning, Scout uses 16 experts per forward pass and features a context length of 10 million tokens, with a training corpus of ~40 trillion tokens. Built for high efficiency and local or commercial deployment, Llama 4 Scout incorporates early fusion for seamless modality integration. It is instruction-tuned for use in multilingual chat, captioning, and image understanding tasks. Released under the Llama 4 Community License, it was last trained on data up to August 2024 and launched publicly on April 5, 2025.

By:MetaInput Type:Output Type:Publish time:2025-04-04

Providers

Route requests across multiple providers. Copy a provider slug to set your preference.

ProviderCache Hit RateContext
NovitaAI
novita
-$0.08/ M tokens$0.4/ M tokensRead:-/ M tokensWrite:-/ M tokens131.07K--

Uptime

24hours

Direct request success rate on AI Gateway and per-provider.

Oct 26, 16:14
NovitaAI100.00%

Throughput

24hours

P50 throughput on live AI Gateway traffic, in tokens per second (TPS).

No data
No data

Latency

24hours

P50 time to first token (TTFT) on live AI Gateway traffic, in milliseconds.

No data
No data

Activity

Token volume and request traffic to this model over time.

Token Consumption
Oct 25
NovitaAI5.5K

Token volume broken down by the provider that served each request. Larger segments indicate providers handling more of this model's traffic.

Benchmarks

Scores on standardized evaluations. Higher percentages are better — and rank percentile shows

Metrics sourced fromArtificial Analysis

Llama 4 Scout InstructMeta
Intelligence Index6.5

Apps

Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for. View All

Token Ranking
No data
No app usage is available for this period.

Related Models

More models from Meta

Meta: Muse Wonder
1.02Btokens

Muse Wonder is Meta's reasoning model for complex agentic tasks, with a 1M-token context window and support for text, image, video, audio, and PDF inputs.

Meta: Muse Spark 1.3 Contributor
25.13Btokens

Muse Spark 1.3 Contributor is the cost-efficient contributor tier of Meta’s multimodal reasoning model for experimentation, learning, and early-stage agentic, multi-agent, and coding workflows. It is designed to track information across extended tasks, work through conflicting inputs, and request clarification or confirmation when needed. Prompts and outputs may be used to improve Meta’s products.

Meta: Muse Spark 1.3
8.51Btokens

Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It is designed to keep track of information across extended tasks, work through conflicting inputs, and request clarification or confirmation when needed, with an emphasis on concise execution.