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Claude Sonnet 4 vs Llama 4 Scout

Compare Anthropic and Meta (via Together AI) AI models

Anthropic
Claude Sonnet 4
vs
Meta (via Together AI)
Llama 4 Scout

Cost Comparison (1000 input + 500 output tokens, 100 requests/day)

Claude Sonnet 4

Per Request:$0.0105
Daily:$1.05
Monthly:$31.50
Yearly:$383.25

Llama 4 Scout

Per Request:$0.000230
Daily:$0.023
Monthly:$0.69
Yearly:$8.395

Cost Differences

$0.01027
Per Request
$1.027
Daily
$30.81
Monthly
$374.855
Yearly

Llama 4 Scout costs less than Claude Sonnet 4

Feature Comparison

FeatureClaude Sonnet 4Llama 4 Scout
ProviderAnthropicMeta (via Together AI)
Input Price$3.00/1M tokens$0.08/1M tokens
Output Price$15.00/1M tokens$0.30/1M tokens
Context Window200,000 tokens10,000,000 tokens
Max Output64,000 tokens32,768 tokens
Categorystandardefficient
Capabilities
textvisioncodereasoning
textvisioncode
Release Date5/14/20254/5/2025

Claude Sonnet 4 vs Llama 4 Scout: Which Should You Choose?

Choosing between Claude Sonnet 4 and Llama 4 Scout depends on your priorities: cost efficiency, context length, or raw capability. Llama 4 Scout is the more affordable option at $0.08/1M input tokens97% cheaper than Claude Sonnet 4. Meanwhile, Llama 4 Scout offers a significantly larger context window at 10,000,000 tokens vs 200,000 for Claude Sonnet 4.

These models come from different providers — Anthropic and Meta (via Together AI) — which means different API ecosystems, SDKs, rate limits, and terms of service. If you're already integrated with Anthropic, switching to Meta (via Together AI)involves migration effort beyond just pricing. Factor in your existing infrastructure when deciding.

These models target different tiers: Claude Sonnet 4 is a standard model while Llama 4 Scout is efficient. This means they're optimized for different workloads. Llama 4 Scout targets more demanding workloads, while Claude Sonnet 4 provides a cost-effective option for everyday tasks.

Output costs matter too. Claude Sonnet 4 charges $15.00/1M output tokens vs $0.30 for Llama 4 Scout. For generation-heavy workloads (content creation, code generation, summarization), output pricing often dominates your bill. Llama 4 Scout has the edge here at $0.30/1M output tokens.

Multimodal capabilities: Both models support vision (image understanding), so you can send images alongside text prompts with either option.

Best Use Cases

Choose Claude Sonnet 4 when:

  • • You need more capabilities (reasoning)
  • • You need longer outputs (up to 64,000 tokens)
  • • You're already using Anthropic's API ecosystem

Choose Llama 4 Scout when:

  • • Budget is a primary concern
  • • You need a larger context window (10,000,000 tokens)
  • • You're already using Meta (via Together AI)'s API ecosystem
  • • You're running high-volume, latency-sensitive workloads

Try Different Scenarios

Use the calculator below to see how costs change with different usage patterns

Claude Sonnet 4 (Anthropic)

Llama 4 Scout (Meta (via Together AI))

Start using Claude Sonnet 4 today

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Start using Llama 4 Scout today

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Frequently Asked Questions

Which is cheaper, Claude Sonnet 4 or Llama 4 Scout?
Llama 4 Scout is cheaper for input tokens at $0.08 per million tokens vs $3.00 for Claude Sonnet 4 — that's 97% savings on input costs.
What is the context window difference between Claude Sonnet 4 and Llama 4 Scout?
Claude Sonnet 4 supports 200,000 tokens while Llama 4 Scout supports 10,000,000 tokens — a difference of 9,800,000 tokens in favor of Llama 4 Scout.
Which model is better for AI Chatbot?
Both models support text. For ai chatbot, Llama 4 Scout is the lower-cost option, while Llama 4 Scout offers a larger context window (10,000,000 vs 200,000 tokens). Choose Llama 4 Scout for budget sensitivity or Llama 4 Scout for longer context tasks.
Which model has better overall pricing for heavy usage?
At 100 requests/day with 1,000 input and 500 output tokens each, Claude Sonnet 4 costs about $31.50/month and Llama 4 Scout costs about $0.69/month. Overall, Llama 4 Scout has lower combined input + output rates ($0.08 in, $0.30 out) vs Claude Sonnet 4.

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