Llama 4 Scout vs SDXL Turbo

Compare Llama 4 Scout and SDXL Turbo: 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 Llama 4 Scout SDXL Turbo
CategoryOpen SourceImage
Parameters109B (17B active)3.5B
Context Window512KN/A
Input Price$0.05/1M tokens$0.002/image/1M tokens
Output Price$0.08/1M tokensN/A/1M tokens
Latency~350ms~1s

Choose Llama 4 Scout when:

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

512K context, MoE efficiency, Strong multilingual

Choose SDXL Turbo when:

  • ✓ Horoscope cards
  • ✓ Festival banners
  • ✓ Quick visuals
Key Strengths:

Ultra-fast, Very low cost, Real-time capable

Verdict: Llama 4 Scout vs SDXL Turbo

For cost efficiency, SDXL Turbo wins at $0.002/image/1M input tokens. For speed, SDXL Turbo is faster at ~1s. Llama 4 Scout excels at Classical text analysis while SDXL Turbo is better for Horoscope cards. Both are available on XALEN through a single API — try them in the Playground to see which fits your workload.

Detailed Analysis

Pricing Comparison

Llama 4 Scout costs $0.05/1M input tokens and $0.08/1M output tokens. SDXL Turbo costs $0.002/image input and N/A output. SDXL Turbo is 25.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Llama 4 Scout has a 512K context window with ~350ms latency. SDXL Turbo offers N/A context at ~1s. Llama 4 Scout has the larger context window.

Best For

Llama 4 Scout (Open Source) is optimized for: Classical text analysis, Long content, Multi-turn. SDXL Turbo (Image) works best for: Horoscope cards, Festival banners, Quick visuals.

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

# Use SDXL Turbo
response_b = client.chat.completions.create(
    model="sdxl-turbo",
    messages=[{"role": "user", "content": "Your question here"}]
)

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Frequently Asked Questions

Which is better, Llama 4 Scout or SDXL Turbo?

Llama 4 Scout (Open Source, 109B (17B active)) offers 512K context. SDXL Turbo (Image, 3.5B) offers Ultra-fast. Choose Llama 4 Scout for Classical text analysis or SDXL Turbo for Horoscope cards.

How much does Llama 4 Scout cost vs SDXL Turbo?

Llama 4 Scout: $0.05/1M input, $0.08/1M output. SDXL Turbo: $0.002/image/1M input, N/A/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 Llama 4 Scout and SDXL Turbo 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.