Live technical benchmark comparing token limits, input/output API pricing, and modalities.
meta-llama/llama-4-scout
google/gemini-3.5-flash
The primary differentiator in developer workflow design is context retention capacity. Meta: Llama 4 Scout offers a context window of 1,310,720 tokens, while Google: Gemini 3.5 Flash supports up to 1,048,576 tokens.
This gives Meta: Llama 4 Scout a substantial advantage of 1x 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, Meta: Llama 4 Scout costs $0.11 per 1M tokens, compared to $1.50 per 1M tokens for Google: Gemini 3.5 Flash.
Meta: Llama 4 Scout is the more cost-effective choice for input prompts, yielding savings of 93% compared to Google: Gemini 3.5 Flash. Similarly, output generations are cheaper on Meta: Llama 4 Scout ($0.34 vs $9.00), representing a savings of 96% on completion tokens.
Meta: Llama 4 Scout is better for large document parsing due to its larger context capacity of 1,310,720 tokens, enabling it to fit approximately 1x more content than Google: Gemini 3.5 Flash in a single prompt.
Meta: Llama 4 Scout is more budget-friendly for prompt inputs, costing $0.11 per million tokens (a saving of 93%). For output completion tokens, Meta: Llama 4 Scout is more cost-effective ($0.34 per 1M tokens).
Browse versioned prompts, system instructions, and workflow packages designed specifically for these frontier AI models on AIMD.