Meta: Llama 4 Scout

Meta: Llama 4 Scout

meta-llama · Released Apr 5, 2025 Professional
Intelligence #10 / 565
82.0 Our Score
Speed #113 / 262
115.2 tokens / sec
Input #177 / 565
$0.080 per 1M tokens
Output #203 / 565
$0.300 per 1M tokens
Context #1 / 565
10M tokens

Analysis Summary

Meta: Llama 4 Scout sits in the Professional tier on our leaderboard, ranked #10 of 565 published models on overall intelligence. At $0.080 input and $0.300 output per 1M tokens, it is among the most expensive on the market. It offers an exceptionally large context window suited to long-document workflows and supports tool use, function calling, and vision.

Editorial notes

Meta Llama 4 Scout delivers a 10M token context window with vision, tool use, and function calling at very low cost, though its intelligence and coding scores are modest relative to its context ambition.

Assessed May 31, 2026

Rankings consider pricing, capabilities, benchmarks, and real-world applicability and are refreshed as new models launch. Feedback?

Performance Profile

Intelligence2.7Technical1.5Value8.3Content3.7
Intelligence 2.7/10
Technical 1.5/10
Content 3.7/10
Value 8.3/10

How Meta: Llama 4 Scout compares

Meta: Llama 4 Scout ranks #249 of 370 AI models we track for overall intelligence, #257 of 307 for coding, #258 of 282 for agentic tasks. Its 10M-token context window is larger than 100% of the models we list. At $0.08 per million input tokens it is cheaper than 69% of comparable models.

About Meta: Llama 4 Scout

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..

Capabilities

Tool Use Function Calling Vision

Performance Indices

Source: Artificial Analysis

13.5 Intelligence Index
6.7 Coding Index
8.5 Agentic Index
14 Math Index

Benchmark Scores

Intelligence

GPQA Diamond 58.7% Graduate-level scientific reasoning
HLE 4.3% Humanity's Last Exam
MMLU Pro 75.2% Multi-task language understanding
MATH 500 84.4% Mathematical problem-solving
AIME 28.3% Competition mathematics
AIME 2025 14% Competition mathematics (2025)
SciCode 17% Scientific computing

Technical

LiveCodeBench 29.9% Live coding evaluation
TerminalBench Hard 1.5% Agentic terminal tasks
τ²-Bench 15.5% Conversational agent benchmark

Content

IFBench 39.5% Instruction following
LCR 25.8% Long-context reasoning

Benchmark data from Artificial Analysis and Hugging Face

How does Meta: Llama 4 Scout stack up?

Compare side-by-side with other professional models.

Compare Models

Model Information

OpenRouter ID meta-llama/llama-4-scout
Providermeta-llama
Model FamilyLlama 4
Release Date April 5, 2025
Context Length10,000,000 tokens
Max Completion16,384 tokens
Status Active

Pricing

Token Type Cost per 1M tokens Cost per 1K tokens
Input $0.08 $0.000080
Output $0.30 $0.000300

Live Performance

Live endpoint metrics, refreshed every 30 minutes.

99.8%
Avg Uptime
301ms
Best Latency (TTFT)
123 tok/s
Best Throughput
4/4
Active Endpoints
Available via: DeepInfra, Groq, Novita, Google

Leaderboard Categories

Frequently asked questions about Meta: Llama 4 Scout

How much does Meta: Llama 4 Scout cost?

Meta: Llama 4 Scout costs $0.08 per million input tokens and $0.30 per million output tokens.

What is the context window of Meta: Llama 4 Scout?

Meta: Llama 4 Scout has a context window of 10,000,000 tokens (10M).

Is Meta: Llama 4 Scout good for coding?

On our coding benchmark index, Meta: Llama 4 Scout ranks #257 of 307 models, placing it in the broader range of the field for code generation and debugging.

What can Meta: Llama 4 Scout do?

Meta: Llama 4 Scout supports image/vision input, tool use, and function calling.

Who created Meta: Llama 4 Scout?

Meta: Llama 4 Scout is developed by Meta and was released on April 5, 2025.