Gemma 3 12B vs Llama 4 Scout

Compare Gemma 3 12B and Llama 4 Scout: pricing, performance, context window, latency, and best use cases. Side-by-side comparison on XALEN.

Updated 2026-05-21 · By Abhishek Raj · Our methodology

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Feature Gemma 3 12B Llama 4 Scout
CategoryCompactOpen Source
Parameters12B109B (17B active)
Context Window128K512K
Input Price$0.015/1M tokens$0.05/1M tokens
Output Price$0.03/1M tokens$0.08/1M tokens
Latency~100ms~350ms

Choose Gemma 3 12B when:

  • ✓ Edge deployments
  • ✓ Classification
  • ✓ Simple chatbots
Key Strengths:

Very compact, Fast, Low cost

Choose Llama 4 Scout when:

  • ✓ Classical text analysis
  • ✓ Long content
  • ✓ Multi-turn
Key Strengths:

512K context, MoE efficiency, Strong multilingual

Verdict: Gemma 3 12B vs Llama 4 Scout

For cost efficiency, Gemma 3 12B wins at $0.015/1M input tokens. For speed, Gemma 3 12B is faster at ~100ms. Gemma 3 12B excels at Edge deployments while Llama 4 Scout is better for Classical text analysis. Both are available on XALEN through a single API — try them in the Playground to see which fits your workload.

Detailed Analysis

Pricing Comparison

Gemma 3 12B costs $0.015/1M input tokens and $0.03/1M output tokens. Llama 4 Scout costs $0.05 input and $0.08 output. Gemma 3 12B is 3.3x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Gemma 3 12B has a 128K context window with ~100ms latency. Llama 4 Scout offers 512K context at ~350ms. Llama 4 Scout has the larger context window.

Best For

Gemma 3 12B (Compact) is optimized for: Edge deployments, Classification, Simple chatbots. Llama 4 Scout (Open Source) works best for: Classical text analysis, Long content, Multi-turn.

Try Both on XALEN

Both models are available through XALEN's OpenAI-compatible API. Switch between them by changing the model parameter:

from xalen import XALEN

client = XALEN(api_key="xln_test_YOUR_KEY")

# Use Gemma 3 12B
response_a = client.chat.completions.create(
    model="gemma-3-12b",
    messages=[{"role": "user", "content": "Your question here"}]
)

# Use Llama 4 Scout
response_b = client.chat.completions.create(
    model="llama-4-scout",
    messages=[{"role": "user", "content": "Your question here"}]
)

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Frequently Asked Questions

Which is better, Gemma 3 12B or Llama 4 Scout?

Gemma 3 12B (Compact, 12B) offers Very compact. Llama 4 Scout (Open Source, 109B (17B active)) offers 512K context. Choose Gemma 3 12B for Edge deployments or Llama 4 Scout for Classical text analysis.

How much does Gemma 3 12B cost vs Llama 4 Scout?

Gemma 3 12B: $0.015/1M input, $0.03/1M output. Llama 4 Scout: $0.05/1M input, $0.08/1M output. Both available on XALEN with batch processing at 50% discount.

Can I use both models on XALEN?

Yes. XALEN provides 200+ models through a single OpenAI-compatible API. Switch between Gemma 3 12B and Llama 4 Scout by changing the model parameter. No code changes needed.

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Last updated: 2026-05-21. Pricing and specifications may change. Check pricing page for latest rates.