LLM Reference

Llama 4 Scout 17B-16E Instruct

Released
2025-04-05
Last refreshed
2026-06-15
Status
Researched 19d ago
Open weightsCommercial use: conditionalMultimodalCodingRAGAgentsLong contextVisionClassificationJSON / Tool use

Llama 4 Scout 17B-16E Instruct is worth evaluating for coding, rag, and agents when its provider route and context window match the workload.

Use it for

  • Teams evaluating coding, rag, and agents
  • Workloads that can use a 10m context window
  • Buyers comparing 4 tracked provider routes

Do not use it for

  • Workloads where another current model has stronger sourced task evidence
Specifications
Family
Llama 4
Released
2025-04-05
Context
10m
Parameters
109B (17B active)
Architecture
Mixture of Experts
Knowledge cutoff
2024-08
Specialization
general
Openness
Open weights
License
Llama 4 CommunityCommercial use: conditional
Training
Pretrained
Created by

Large-scale open-source AI for social technologies.

Menlo Park, California, United States
Founded 2013
Website
Pricing
Output / 1M
$0.220
Input / 1M
$0.170

Cheapest of 12 routes · AWS Bedrock

About

Meta's Llama 4 Scout is a 17-billion parameter mixture-of-experts model with 16 expert routing. Optimized for efficient inference on edge and cloud environments with strong multi-turn conversation capabilities. Available on Cloudflare Workers AI.

Llama 4 Scout 17B-16E Instruct is an open-weight model in the Llama 4 family. The structured metadata tracks a 10m-token context window, multimodal input, and structured outputs. This page tracks provider routes through Cloudflare Workers AI, OpenRouter, Together AI, and 9 more, with the cheapest tracked route listed at $0.08 input and $0.3 output per 1M tokens. Headline tracked benchmarks include Chatbot Arena 1295.0, τ-bench 62.3, and Massive Multi-discipline Multimodal Understanding 69.4.

Top use-case fit: coding, agents, and build tasks

Coding

Q/$ B

1 relevant benchmark in the decision map.

RAG

Included by capability and metadata signals in the decision map.

Agents

Q/$ A

1 relevant benchmark in the decision map.

Provider price ladder

Compare all 12

Compare API pricing across 4 providers for input and output tokens, batch, and cached reads when available.

ProviderInput / 1MOutput / 1MRoute
AWS Bedrock$0.170$0.220
Serverless
DeepInfra$0.080$0.300
Serverless
OpenRouter$0.080$0.300
Serverless
GroqCloud$0.110$0.340
Serverless

Available via routers & gateways(16)

AIRouter

Router

Commercial LLM router that analyzes incoming requests and routes to the optimal model for cost/quality/latency via a drop-in OpenAI-compatible API, with a privacy-preserving embedding mode that avoids sending prompt content.

Passthrough + feeGCP Vertex AI

Amazon Bedrock Intelligent Prompt Routing

Router

AWS Bedrock's native intelligent prompt router that routes prompts between Anthropic Claude model tiers (Haiku/Sonnet) based on predicted task complexity, with no extra per-routing charge.

PassthroughAWS Bedrock

Azure AI Foundry Model Router

Router

Microsoft Azure AI Foundry's native model router that uses a trained ML model to route each prompt in real time to the optimal Azure-hosted model, with Balanced/Cost/Quality mode selection and automatic failover.

PassthroughMicrosoft Foundry

Helicone

Gateway

Observability-first AI gateway with routing, caching, rate limiting, and request tracing; Apache 2.0 open-source core with a managed hosted tier for logging and analytics.

SubscriptionMicrosoft FoundryGCP Vertex AI

Kong AI Gateway

Gateway

Multi-LLM AI gateway built on Kong Gateway 3.x, adding semantic routing, load balancing, guardrails, and MCP traffic analytics as plugins over Kong's existing API management platform.

SubscriptionGCP Vertex AIMicrosoft Foundry

LiteLLM

Gateway

Open-source Python SDK and proxy server that unifies 100+ LLM APIs behind a single OpenAI-compatible interface, with load balancing, cost tracking, and configurable failover.

Free OSSGCP Vertex AIMicrosoft Foundry

Capabilities

VisionMultimodalStructured Outputs

Benchmark peer barsfor Coding

Benchmark scores(5)

Scores are benchmark-specific and are direction-aware: the same numeric gap can mean very different outcomes across suites. Use the leaderboard context and this model's provider route to decide whether the winning margin is meaningful for your workload.
BenchmarkScoreVersionSource
Chatbot Arena1295.0https://lmarena.ai
τ-bench62.3τ-benchhttps://taubench.com/
Massive Multi-discipline Multimodal Understanding69.4https://ai.meta.com/blog/llama-4-scout-maverick/
MMLU PRO74.3https://ai.meta.com/blog/llama-4-scout-maverick/
LiveCodeBench32.8https://ai.meta.com/blog/llama-4-scout-maverick/

Migration checks

No linked migration route is available for this model yet.