WizardLM 2 8x22B vs OLMo 2 13B

Compare WizardLM 2 8x22B and OLMo 2 13B: 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 WizardLM 2 8x22B OLMo 2 13B
CategoryOpen SourceOpen Source
Parameters176B (22B active)13B
Context Window65K32K
Input Price$0.04/1M tokens$0.015/1M tokens
Output Price$0.08/1M tokens$0.03/1M tokens
Latency~350ms~120ms

Choose WizardLM 2 8x22B when:

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

Strong instruction following, Good math, MoE efficient

Choose OLMo 2 13B when:

  • ✓ Research
  • ✓ Custom training
  • ✓ Transparency-required apps
Key Strengths:

Fully open (weights + data), Transparent, Research-friendly

Verdict: WizardLM 2 8x22B vs OLMo 2 13B

For cost efficiency, OLMo 2 13B wins at $0.015/1M input tokens. For speed, OLMo 2 13B is faster at ~120ms. WizardLM 2 8x22B excels at Complex instructions while OLMo 2 13B is better for Research. Both are available on XALEN through a single API — try them in the Playground to see which fits your workload.

Detailed Analysis

Pricing Comparison

WizardLM 2 8x22B costs $0.04/1M input tokens and $0.08/1M output tokens. OLMo 2 13B costs $0.015 input and $0.03 output. OLMo 2 13B is 2.7x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

WizardLM 2 8x22B has a 65K context window with ~350ms latency. OLMo 2 13B offers 32K context at ~120ms. WizardLM 2 8x22B has the larger context window.

Best For

WizardLM 2 8x22B (Open Source) is optimized for: Complex instructions, Math tasks, Structured output. OLMo 2 13B (Open Source) works best for: Research, Custom training, Transparency-required apps.

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

# Use OLMo 2 13B
response_b = client.chat.completions.create(
    model="olmo-2-13b",
    messages=[{"role": "user", "content": "Your question here"}]
)

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Get API Key Try in Playground

Frequently Asked Questions

Which is better, WizardLM 2 8x22B or OLMo 2 13B?

WizardLM 2 8x22B (Open Source, 176B (22B active)) offers Strong instruction following. OLMo 2 13B (Open Source, 13B) offers Fully open (weights + data). Choose WizardLM 2 8x22B for Complex instructions or OLMo 2 13B for Research.

How much does WizardLM 2 8x22B cost vs OLMo 2 13B?

WizardLM 2 8x22B: $0.04/1M input, $0.08/1M output. OLMo 2 13B: $0.015/1M input, $0.03/1M 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 WizardLM 2 8x22B and OLMo 2 13B 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.