Llama 4 Scout vs WizardLM 2 8x22B

Compare Llama 4 Scout and WizardLM 2 8x22B: 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 WizardLM 2 8x22B
CategoryOpen SourceOpen Source
Parameters109B (17B active)176B (22B active)
Context Window512K65K
Input Price$0.05/1M tokens$0.04/1M tokens
Output Price$0.08/1M tokens$0.08/1M tokens
Latency~350ms~350ms

Choose Llama 4 Scout when:

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

512K context, MoE efficiency, Strong multilingual

Choose WizardLM 2 8x22B when:

  • ✓ Complex instructions
  • ✓ Math tasks
  • ✓ Structured output
Key Strengths:

Strong instruction following, Good math, MoE efficient

Verdict: Llama 4 Scout vs WizardLM 2 8x22B

For cost efficiency, WizardLM 2 8x22B wins at $0.04/1M input tokens. For speed, WizardLM 2 8x22B is faster at ~350ms. Llama 4 Scout excels at Classical text analysis while WizardLM 2 8x22B is better for Complex instructions. 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. WizardLM 2 8x22B costs $0.04 input and $0.08 output. WizardLM 2 8x22B is 1.3x 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. WizardLM 2 8x22B offers 65K context at ~350ms. 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. WizardLM 2 8x22B (Open Source) works best for: Complex instructions, Math tasks, Structured output.

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 WizardLM 2 8x22B
response_b = client.chat.completions.create(
    model="wizardlm-2-8x22b",
    messages=[{"role": "user", "content": "Your question here"}]
)

Start Building with XALEN

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Get API Key Try in Playground

Frequently Asked Questions

Which is better, Llama 4 Scout or WizardLM 2 8x22B?

Llama 4 Scout (Open Source, 109B (17B active)) offers 512K context. WizardLM 2 8x22B (Open Source, 176B (22B active)) offers Strong instruction following. Choose Llama 4 Scout for Classical text analysis or WizardLM 2 8x22B for Complex instructions.

How much does Llama 4 Scout cost vs WizardLM 2 8x22B?

Llama 4 Scout: $0.05/1M input, $0.08/1M output. WizardLM 2 8x22B: $0.04/1M 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 Llama 4 Scout and WizardLM 2 8x22B 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.