Gemini 1.5 Pro vs Llama 4 Scout
Gemini 1.5 Pro and Llama 4 Scout are closely matched at 12.0 and 7.8 on the LLM Stats Score. Llama 4 Scout is 32.4x cheaper per token.
Google · Meta · Updated for 2026
Which is better?
Gemini 1.5 Pro and Llama 4 Scout are closely matched on the overall LLM Stats Score at 12.0 and 7.8.
In the 7 individual benchmarks reported for both models, Gemini 1.5 Pro wins 4; this is a narrower head-to-head signal than the composite indexes.
On price, Llama 4 Scout is roughly 32.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Llama 4 Scout also accepts a larger context window (10,000,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Gemini 1.5 Pro
- you value its reported benchmark strengths — it wins 4 of 7 exact shared results
Choose Llama 4 Scout
- cost matters — it's about 32.4x cheaper per token
- you process long inputs — it offers a 10,000,000 token context window
- you want the most recent training data — it shipped Apr 2025
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
23 reported for Gemini 1.5 Pro · 12 for Llama 4 Scout
Gemini 1.5 Pro outperforms in 4 benchmarks (GPQA, MATH, MMLU, MMLU-Pro), while Llama 4 Scout is better at 3 benchmarks (MathVista, MGSM, MMMU).
Gemini 1.5 Pro has a slight edge in benchmark performance.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Gemini 1.5 Pro ($2.50/1M tokens) is 31.3x more expensive than Llama 4 Scout ($0.08/1M tokens).
For output processing, Gemini 1.5 Pro ($10.00/1M tokens) is 33.3x more expensive than Llama 4 Scout ($0.30/1M tokens).
In conclusion, Gemini 1.5 Pro is more expensive than Llama 4 Scout.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Llama 4 Scout accepts 10,000,000 input tokens compared to Gemini 1.5 Pro's 2,097,152 tokens. Llama 4 Scout can generate longer responses up to 10,000,000 tokens, while Gemini 1.5 Pro is limited to 8,192 tokens.
Input capabilities
Documented input modalities across available providers
Both Gemini 1.5 Pro and Llama 4 Scout support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Gemini 1.5 Pro
Llama 4 Scout
License
Usage and distribution terms
Gemini 1.5 Pro is licensed under a proprietary license, while Llama 4 Scout uses Llama 4 Community License Agreement.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Llama 4 Community License Agreement
Open weights
Release Timeline
When each model was launched
Gemini 1.5 Pro was released on 2024-05-01, while Llama 4 Scout was released on 2025-04-05.
Llama 4 Scout is 11 months newer than Gemini 1.5 Pro.
May 1, 2024
2.4 years ago
Apr 5, 2025
1.5 years ago
11mo newerKnowledge Cutoff
When training data ends
Gemini 1.5 Pro has a documented knowledge cutoff of 2023-11-01, while Llama 4 Scout's cutoff date is not specified.
We can confirm Gemini 1.5 Pro's training data extends to 2023-11-01, but cannot make a direct comparison without Llama 4 Scout's cutoff date.
Nov 2023
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Provider Availability
Gemini 1.5 Pro is available from Google. Llama 4 Scout is available from DeepInfra, Lambda, Novita, Groq, Fireworks, Together.
Gemini 1.5 Pro
Llama 4 Scout
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemini 1.5 Pro and Llama 4 Scout side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemini 1.5 Pro vs Llama 4 Scout.