Llama 4 Scout vs Gemini 3.5 Flash
Meta's efficient long-context Scout against Gemini Flash.
What the numbers say
- Llama 4 Scout is about 30x cheaper on output tokens (3.3 vs 99.0 credits per 1M).
- Llama 4 Scout takes noticeably more context: 10M vs 1.0M tokens.
- Gemini 3.5 Flash is the newer release (May 2026 vs April 2025).
Derived from the live registry Zeplik routes and bills against. Credits: 1 credit = $0.10, raw provider rate with a 1.10x margin.
Side by side
Llama 4 Scout
Meta
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...
- Provider
- Meta
- Context window
- 10M tokens
- Input price
- 1.1 credits / 1M tokens ($0.10 raw)
- Output price
- 3.3 credits / 1M tokens ($0.30 raw)
- Vision (image input)
- Yes
- Tool calling
- Yes
- Extended reasoning
- No
Best for
- Everyday chat and drafting on an open-weight model with transparent lineage
- Very long documents and codebases: a 10M-token window fits entire books or repositories in one conversation
- Working with images: screenshots, charts, photos and scanned documents alongside text
- Tool use and agents: reliably calls functions, so it can search, run skills and drive workflows
Gemini 3.5 Flash
Gemini 3.5 Flash is Google's high-efficiency multimodal model, bringing near-Pro level coding and reasoning at Flash-tier cost and speed. It is highly optimized for coding proficiency and parallel agentic execution...
- Provider
- Context window
- 1.0M tokens
- Input price
- 16.5 credits / 1M tokens ($1.50 raw)
- Output price
- 99.0 credits / 1M tokens ($9.00 raw)
- Vision (image input)
- Yes
- Tool calling
- Yes
- Extended reasoning
- No
Best for
- High-volume everyday tasks where speed and cost matter: summaries, drafts, quick questions
- Very long documents and codebases: a 1.0M-token window fits entire books or repositories in one conversation
- Working with images: screenshots, charts, photos and scanned documents alongside text
- Tool use and agents: reliably calls functions, so it can search, run skills and drive workflows
Try both on Zeplik
The honest answer to most model debates is to run your own prompt on both. Zeplik puts Llama 4 Scout and Gemini 3.5 Flash in the same chat, so you can switch mid-conversation and compare answers on the work you actually do.