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Gemini 3.1 Pro Preview vs Llama 4 Scout

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Gemini 3.1 Pro Preview and Llama 4 Scout.

Google

Gemini 3.1 Pro Preview

Gemini 3.1 Pro Preview is Google’s frontier reasoning model, delivering enhanced software engineering performance, improved agentic reliability, and more efficient token usage across complex workflows. Building on the multimodal foundation...

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Meta

Llama 4 Scout

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...

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Technical Specifications

SpecificationGemini 3.1 Pro PreviewLlama 4 Scout
ProviderGoogleMeta
Context Window1,048,576 tokens10,000,000 tokens
Agent SuitabilityN/A82/100
Time to First Token (TTFT)N/A350 ms
Deployment Modelmanaged apiself hostable
Production Stabilitybetabeta
API AvailableYesYes
Released Date2026-02-192025-04-05

API Pricing Comparison

Input Price per Million Tokens

Gemini 3.1 Pro Preview

$2.00

Llama 4 Scout

$0.10

Output Price per Million Tokens

Gemini 3.1 Pro Preview

$12.00

Llama 4 Scout

$0.30

Want to test both models live?

Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

MMLUGeneral knowledge & multi-task understanding
N/Avs8720.0%
Gemini 3.1 Pro Preview
Llama 4 Scout
HumanEvalPython coding & logic synthesis
N/Avs8950.0%
Gemini 3.1 Pro Preview
Llama 4 Scout
MATHComplex mathematical problem solving
N/Avs8100.0%
Gemini 3.1 Pro Preview
Llama 4 Scout
GPQAGraduate-level expert reasoning
N/Avs6680.0%
Gemini 3.1 Pro Preview
Llama 4 Scout
HellaSwagCommonsense reasoning and inference
N/Avs9450.0%
Gemini 3.1 Pro Preview
Llama 4 Scout
MT-BenchMulti-turn conversation flow quality
N/Avs910.0%
Gemini 3.1 Pro Preview
Llama 4 Scout

Gemini 3.1 Pro Preview Quirks & Gotchas

No developer gotchas reported.

Llama 4 Scout Quirks & Gotchas

  • 10M context causes significant VRAM pressure — recommend 4-bit quantization
  • Primarily designed for RAG, not agentic tool calling