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Claude Sonnet 4.6 vs Llama 4 Scout

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Claude Sonnet 4.6 and Llama 4 Scout.

Anthropic

Claude Sonnet 4.6

Sonnet 4.6 is Anthropic's most capable Sonnet-class model yet, with frontier performance across coding, agents, and professional work. It excels at iterative development, complex codebase navigation, end-to-end project management with...

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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...

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Technical Specifications

SpecificationClaude Sonnet 4.6Llama 4 Scout
ProviderAnthropicMeta
Context Window1,000,000 tokens10,000,000 tokens
Agent Suitability94/10082/100
Time to First Token (TTFT)350 ms350 ms
Deployment Modelmanaged apiself hostable
Production Stabilitystablebeta
API AvailableYesYes
Released Date2026-02-172025-04-05

API Pricing Comparison

Input Price per Million Tokens

Claude Sonnet 4.6

$3.00

Llama 4 Scout

$0.10

Output Price per Million Tokens

Claude Sonnet 4.6

$15.00

Llama 4 Scout

$0.30

Want to test both models live?

Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

MMLUGeneral knowledge & multi-task understanding
9040.0%vs8720.0%
Claude Sonnet 4.6
Llama 4 Scout
HumanEvalPython coding & logic synthesis
9370.0%vs8950.0%
Claude Sonnet 4.6
Llama 4 Scout
MATHComplex mathematical problem solving
8230.0%vs8100.0%
Claude Sonnet 4.6
Llama 4 Scout
GPQAGraduate-level expert reasoning
6500.0%vs6680.0%
Claude Sonnet 4.6
Llama 4 Scout
HellaSwagCommonsense reasoning and inference
9600.0%vs9450.0%
Claude Sonnet 4.6
Llama 4 Scout
MT-BenchMulti-turn conversation flow quality
940.0%vs910.0%
Claude Sonnet 4.6
Llama 4 Scout

Claude Sonnet 4.6 Quirks & Gotchas

  • โ–ธBest balance of speed and capability โ€” default for most Claude integrations
  • โ–ธComputer-use (beta) feature enables autonomous UI interaction

Llama 4 Scout Quirks & Gotchas

  • โ–ธ10M context causes significant VRAM pressure โ€” recommend 4-bit quantization
  • โ–ธPrimarily designed for RAG, not agentic tool calling