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Meta: Llama 4 Scout

by Meta

8.7
Quality score / 10

Overview

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...

Our take

The single use case this model is built for is reasoning over genuinely enormous inputs: its standout spec is a 10,000,000-token context window, far larger than anything else on this list. It is a mixture-of-experts model activating 17 billion parameters out of 109B total, with native multimodal input, tool and function calling and structured JSON output, priced at $0.10 per 1M input tokens, cheaper than roughly three-quarters of comparable models. That combination suits an engineer feeding an entire large codebase, or a full archive of contracts and their amendments, into one prompt and asking for cross-references and a parseable summary, work that smaller context windows simply cannot hold. Unlike Claude Sonnet 5 or Gemini, which offer strong but far smaller contexts, this differentiates almost entirely on the sheer size of what you can load at once, and at a low per-token price. The caveat is no free tier, with a knowledge cutoff of August 2024. Ideal for developers and analysts whose bottleneck is fitting massive documents or codebases into a single context rather than peak per-token reasoning quality. Choose it when input size is the constraint; look elsewhere if your prompts are modest and you would rather pay for sharper reasoning or a free tier.

How Meta: Llama 4 Scout stacks up

Among the 368 chatbots & llms tools in our directory, it ranks #81 of 355 on quality (8.7/10), 9% above the 355-tool average of 8.0, and its $0.1/1M input-token rate is in the budget end — 94% cheaper than the 345-model average of $1.58/1M.

Weighing quality against cost, Meta: Llama 4 Scout's cost-per-quality-point of $0.01 places it in the top 13% for value among chatbots & llms tools.

Meta: Llama 4 Scout in depth

Meta: Llama 4 Scout, built by Meta, sits in the chatbots & llms space and is a paid tool starting at $0.10/1M tokens. Our editors rate it 8.7 out of 10 based on capability, ecosystem and value. It handles a context window of 1,310,720 tokens.

On the feature side, Meta: Llama 4 Scout brings 1,310,720-token context window, vision (image input), tool / function calling and structured (json) outputs. These are the capabilities that most shape day-to-day use and separate it from thinner alternatives.

Its biggest strength is low api price — $0.1 per 1m input tokens, cheaper than roughly 75% of comparable models, while the main trade-off to weigh is that no free tier — usage is billed per token. Keep both in mind when deciding whether it fits your workflow.

Meta: Llama 4 Scout is most often chosen for research and writing. If that matches your goals, it's a strong candidate to shortlist.

Speed
Context window
1,310,720 tokens
Free tier
No
Updated
2026-08-15

Key features

  • 1,310,720-token context window
  • Vision (image input)
  • Tool / function calling
  • Structured (JSON) outputs
  • Knowledge cutoff 2024-08-31

Pricing

$0.10/1M tokens
Pay per token
Paid$0.10/1M tokens
API input
$0.1 / 1M tokens
API output
$0.3 / 1M tokens
See full API pricing → llmprice.app

Pros

  • +Low API price — $0.1 per 1M input tokens, cheaper than roughly 75% of comparable models
  • +Large 1,310,720-token context window, bigger than most models listed here
  • +Accepts images as input (vision-capable)
  • +Supports tool / function calling for agent-style workflows

Cons

  • No free tier — usage is billed per token

Who should use Meta: Llama 4 Scout

  • Anyone looking for a chatbots & llms tool from Meta.
  • Teams and individuals focused on research and writing.
  • People who value low api price — $0.1 per 1m input tokens, cheaper than roughly 75% of comparable models.
  • Workflows that need a 1,310,720 tokens context window.

Who should look elsewhere

  • Anyone who needs a free tier — this tool is paid only.
  • Those for whom no free tier — usage is billed per token is a dealbreaker.

Best for

10 Best Meta: Llama 4 Scout Alternatives in 2026

Meta: Llama 4 Scout is a strong chatbots & llms tool, but it is not the only option. Whether you are after a lower price, different features or a better fit for your workflow, here are the 10 best alternatives to Meta: Llama 4 Scout, ranked and compared.

1
ClaudeFree tier$20/mo

Anthropic

Claude is Anthropic's family of AI assistants, known for long-context reasoning, careful writing and strong coding…

+ Best-in-class long-document reasoning+ Natural, high-quality writing+ Strong safety and reliability
Read full Claude review →
2
ChatGPTFree tier$20/mo

OpenAI

ChatGPT is OpenAI's flagship conversational AI, powering hundreds of millions of weekly users across web, mobile and…

+ Most polished and widely supported ecosystem+ Excellent general reasoning and coding+ Huge third-party integration support
Read full ChatGPT review →
3
GeminiFree tier$20/mo

Google DeepMind

Gemini is Google's natively multimodal model family, deeply integrated across Search, Workspace, Android and the Pixel…

+ Massive context window+ Tight integration with Google ecosystem+ Generous free access
Read full Gemini review →
4

Google

Gemini 3.7 Flash is a multimodal model from Google for fast agentic workflows, coding, and complex multi-step…

+ Large 1,048,576-token context window, bigger than most models listed here+ Built-in reasoning (chain-of-thought) mode for harder problems+ Accepts images as input (vision-capable)
Read full Google: Gemini 3.7 Flash (batch) review →
5
Meta: Muse Spark 1.2Paid$1.25/1M tokens

Meta

Muse Spark 1.2 is a reasoning model from Meta, designed for complex agentic tasks.

+ Large 1,048,576-token context window, bigger than most models listed here+ Built-in reasoning (chain-of-thought) mode for harder problems+ Accepts images as input (vision-capable)
Read full Meta: Muse Spark 1.2 review →
6
Qwen: Qwen3.8 MaxPaid$2.00/1M tokens

Qwen

Qwen3.8 Max is the flagship model in Alibaba's Qwen3.8 series, the general-availability successor to the Qwen3.8 Max…

+ Large 1,000,000-token context window, bigger than most models listed here+ Built-in reasoning (chain-of-thought) mode for harder problems+ Accepts images as input (vision-capable)
Read full Qwen: Qwen3.8 Max review →
7
Qwen: Qwen3.7 FlashPaid$0.03/1M tokens

Qwen

Qwen3.7 Flash is a vision-language reasoning model from Alibaba. It is suited for multimodal agents, visual coding…

+ Low API price — $0.03 per 1M input tokens, cheaper than roughly 75% of comparable models+ Large 1,000,000-token context window, bigger than most models listed here+ Built-in reasoning (chain-of-thought) mode for harder problems
Read full Qwen: Qwen3.7 Flash review →
8
Claude Opus 5 (Fast)Paid$10.00/1M tokens

Anthropic

Fast-mode variant of [Opus 5](/anthropic/claude-opus-5) - identical capabilities with higher output speed at 2x pricing…

+ Large 1,000,000-token context window, bigger than most models listed here+ Built-in reasoning (chain-of-thought) mode for harder problems+ Accepts images as input (vision-capable)
Read full Claude Opus 5 (Fast) review →
9
Claude Opus 5 (batch)Paid$2.50/1M tokens

Anthropic

Claude Opus 5 is Anthropic’s flagship model for demanding reasoning, coding, and long-horizon agentic work.

+ Large 1,000,000-token context window, bigger than most models listed here+ Built-in reasoning (chain-of-thought) mode for harder problems+ Accepts images as input (vision-capable)
Read full Claude Opus 5 (batch) review →
10

Google

Gemini 3.6 Flash is a high-efficiency model from Google for coding, agentic workflows, and web and app development.

+ Large 1,048,576-token context window, bigger than most models listed here+ Built-in reasoning (chain-of-thought) mode for harder problems+ Accepts images as input (vision-capable)
Read full Google: Gemini 3.6 Flash (batch) review →

Meta: Llama 4 Scout vs top alternatives

A side-by-side look at how Meta: Llama 4 Scout stacks up against its closest rivals.

FeatureMeta: Llama 4 ScoutMetaClaudeAnthropicChatGPTOpenAIGeminiGoogle DeepMind
Quality score8.7 / 109.6 / 109.5 / 109.2 / 10
Starting price$0.10/1M tokens$20/mo$20/mo$20/mo
Free tierNoYes — Free tier availableYes — Free tier availableYes — Free tier available
API input price$0.1 / 1M tokens$10 / 1M tokens$0.1 / 1M tokens$0.1875 / 1M tokens
API output price$0.3 / 1M tokens$50 / 1M tokens$0.6 / 1M tokens$0.9375 / 1M tokens
SpeedFastFastFast
Context window1,310,720 tokens200K tokens128K tokens1M-2M tokens
CategoriesChatbots & LLMsChatbots & LLMs, Coding, WritingChatbots & LLMs, Coding, WritingChatbots & LLMs, Coding, Writing
Key features
  • 1,310,720-token context window
  • Vision (image input)
  • Tool / function calling
  • Structured (JSON) outputs
  • Industry-leading long context (200K+ tokens)
  • Artifacts for live previews
  • Strong agentic coding (Claude Code)
  • Vision and document analysis
  • Multimodal text, image and voice input
  • Advanced data analysis (code interpreter)
  • Custom GPTs and GPT Store
  • Web browsing and real-time search
  • Up to 2M token context window
  • Deep Google Workspace integration
  • Native video and audio understanding
  • Real-time Google Search grounding
Pros
  • + Low API price — $0.1 per 1M input tokens, cheaper than roughly 75% of comparable models
  • + Large 1,310,720-token context window, bigger than most models listed here
  • + Accepts images as input (vision-capable)
  • + Supports tool / function calling for agent-style workflows
  • + Best-in-class long-document reasoning
  • + Natural, high-quality writing
  • + Strong safety and reliability
  • + Most polished and widely supported ecosystem
  • + Excellent general reasoning and coding
  • + Huge third-party integration support
  • + Massive context window
  • + Tight integration with Google ecosystem
  • + Generous free access
Cons
  • No free tier — usage is billed per token
  • No native image generation
  • Fewer consumer integrations than ChatGPT
  • Usage caps on the most capable models
  • Can be verbose and overly cautious
  • Quality can be inconsistent on edge cases
  • Privacy concerns for some users

Frequently asked questions

Q. Is Meta: Llama 4 Scout free?

No — Meta: Llama 4 Scout is a paid tool, starting at $0.10/1M tokens.

Q. How much does Meta: Llama 4 Scout cost?

Meta: Llama 4 Scout starts at $0.10/1M tokens. API usage is around $0.1 per 1M input tokens and $0.3 per 1M output tokens.

Q. What is Meta: Llama 4 Scout best for?

Meta: Llama 4 Scout is best suited to research and writing, within the chatbots & llms category.

Q. What are the best Meta: Llama 4 Scout alternatives?

Popular alternatives to Meta: Llama 4 Scout include Claude, ChatGPT, Gemini and Google: Gemini 3.7 Flash (batch). Each trades off price, quality and ecosystem differently.

Q. Is there a free alternative to Meta: Llama 4 Scout?

Yes. Claude, ChatGPT, Gemini offer a free tier, making them good starting points if you want to avoid an upfront subscription.

Q. Why switch from Meta: Llama 4 Scout?

Common reasons include pricing, specific feature gaps (No free tier — usage is billed per token), data-privacy requirements, or simply wanting a tool that fits your stack better.

How we rate AI tools

Our quality score weighs capability on real tasks, breadth of features and integrations, pricing and value, and how actively the tool is maintained. Scores are editorial guidance, not benchmarks — always trial a tool on your own workflow before committing. Pricing and features change frequently, so verify current details on the official site.

Ready to try Meta: Llama 4 Scout?

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Visit Meta: Llama 4 Scout