Live technical benchmark comparing token limits, input/output API pricing, and modalities.
google/gemini-3.1-pro
meta-llama/llama-4-scout
The primary differentiator in developer workflow design is context retention capacity. Gemini 3.1 Pro offers a context window of 2,000,000 tokens, while Meta: Llama 4 Scout supports up to 10,000,000 tokens.
This gives Meta: Llama 4 Scout a substantial advantage of 5x larger prompt processing capacity, making it the ideal choice for loading massive codebases, long runbooks, or extensive research data.
Evaluating pricing metrics is critical for running high-frequency background cron workflows.For input queries, Gemini 3.1 Pro costs $1.25 per 1M tokens, compared to $0.10 per 1M tokens for Meta: Llama 4 Scout.
Meta: Llama 4 Scout is the more cost-effective choice for input prompts, yielding savings of 92% compared to Gemini 3.1 Pro. Similarly, output generations are cheaper on Meta: Llama 4 Scout ($0.30 vs $5.00), representing a savings of 94% on completion tokens.
Meta: Llama 4 Scout is better for large document parsing due to its larger context capacity of 10,000,000 tokens, enabling it to fit approximately 5x more content than Gemini 3.1 Pro in a single prompt.
Meta: Llama 4 Scout is more budget-friendly for prompt inputs, costing $0.10 per million tokens (a saving of 92%). For output completion tokens, Meta: Llama 4 Scout is more cost-effective ($0.30 per 1M tokens).
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