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Llama 4 Scout vs GPT-5.2

A side-by-side comparison of two multimodal models — real specs, pricing, strengths and weaknesses, and a clear verdict on which to choose. Kept current by our agents.

Quick verdict: which should you choose?

Choose Llama 4 Scout if you need

  • extremely large 10M-token context for long text and image sequences
  • fast output at 112.48 tokens per second and low cost of $0.3 per million tokens
  • open-weight model with native multimodal input support
  • strong reasoning over very long inputs

Choose GPT-5.2 if you need

  • much higher intelligence index of 46.6 for complex tasks
  • support for files, images, and text with unified multimodal processing
  • scalable document-level analysis from OpenAI
  • extensive 400k context window

Verdict

GPT-5.2 leads decisively on intelligence (46.6 vs 13.5) and offers broader file-plus-image support, while Llama 4 Scout dominates on context length (10M vs 400k tokens), speed (112.48 t/s), and price ($0.3 vs $14 per million tokens). Llama 4 Scout is the practical choice for long-sequence multimodal work on a budget; GPT-5.2 suits users who prioritize raw capability over cost or scale.

Llama 4 Scout vs GPT-5.2: side by side

SpecLlama 4 ScoutGPT-5.2Winner
Intelligence13.546.6GPT-5.2
Output speed112 t/sTie
Output price$0.30/1M$14.00/1MLlama 4 Scout
Context10000K400KLlama 4 Scout
ParamsTie
TypeOpen-weightProprietaryTie
ProviderMetaOpenAITie

Detailed analysis

Intelligence

Winner: GPT-5.2

GPT-5.2 scores 46.6 on the intelligence index compared with Llama 4 Scout's 13.5. This gap favors GPT-5.2 for tasks requiring advanced reasoning.

Context & Speed

Winner: Llama 4 Scout

Llama 4 Scout provides a 10M-token context window versus GPT-5.2's 400k tokens and delivers 112.48 tokens per second output. GPT-5.2's speed is unspecified.

Pricing

Winner: Llama 4 Scout

Llama 4 Scout costs $0.3 per million output tokens while GPT-5.2 costs $14 per million. The 46x price difference makes Llama 4 Scout far more economical at scale.

Modalities

Winner: GPT-5.2

GPT-5.2 supports files, images, and text with unified processing. Llama 4 Scout is limited to native text and image inputs only.

Llama 4 Scout

Pros

  • +Extremely large context window
  • +Native multimodal input support
  • +Strong reasoning over long inputs

Cons

  • High compute cost at maximum context
  • Limited to text and image modalities only
  • May exhibit latency on very long sequences
Full Llama 4 Scout review →

GPT-5.2

Pros

  • +Extensive context window
  • +Support for files, images, and text
  • +Unified multimodal processing
  • +Scalable document-level analysis

Cons

  • High resource use with maximum context
  • No native audio or video modalities
  • Risk of diluted focus in very long inputs
Full GPT-5.2 review →

Summary: Llama 4 Scout vs GPT-5.2

Choose Llama 4 Scout when maximum context, speed, and low cost matter most. Select GPT-5.2 when highest intelligence and file-handling capabilities are required. The models serve different priorities within multimodal workloads.

Frequently asked questions

GPT-5.2 leads on intelligence while Llama 4 Scout leads on context size, speed, and price; neither is universally better.

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