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Gemini 3 Flash Preview vs Llama 3.1 8B

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 Flash Preview and Llama 3.1 8B.

Google

Gemini 3 Flash Preview

Gemini 3 Flash Preview is a high speed, high value thinking model designed for agentic workflows, multi turn chat, and coding assistance. It delivers near Pro level reasoning and tool...

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Meta

Llama 3.1 8B

Llama 3.1 8B is Meta's lightweight open-weight model from the Llama 3.1 generation, optimized for efficient deployment on consumer hardware and edge devices. Despite its compact 8-billion-parameter size, it delivers strong performance on instruction following, text summarization, and lightweight coding tasks. Lllama 3.1 8B is the most downloaded model in the Llama family and runs efficiently on laptops, single GPUs, and CPU via quantization โ€” making it the default choice for on-device AI applications and local prototyping.

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Technical Specifications

SpecificationGemini 3 Flash PreviewLlama 3.1 8B
ProviderGoogleMeta
Context Window1,048,576 tokens131,072 tokens
Agent SuitabilityN/A74/100
Time to First Token (TTFT)N/A80 ms
Deployment Modelmanaged apiself hostable
Production Stabilitybetastable
API AvailableYesYes
Released Date2025-12-172024-07-23

API Pricing Comparison

Input Price per Million Tokens

Gemini 3 Flash Preview

$0.50

Llama 3.1 8B

$0.04

Output Price per Million Tokens

Gemini 3 Flash Preview

$3.00

Llama 3.1 8B

$0.04

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.

Gemini 3 Flash Preview Quirks & Gotchas

No developer gotchas reported.

Llama 3.1 8B Quirks & Gotchas

  • โ–ธPerfect for CPU/edge deployment โ€” runs on Raspberry Pi with quantization
  • โ–ธLimited tool calling vs larger models โ€” best for simple classification and chat