o4-mini vs WizardLM 2 8x22B

Compare o4-mini 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

All OpenAI models All Microsoft models What is an LLM API? Python Quickstart What is inference?
Feature o4-mini WizardLM 2 8x22B
CategoryReasoningOpen Source
Parameters~200B176B (22B active)
Context Window200K65K
Input Price$0.03/1M tokens$0.04/1M tokens
Output Price$0.12/1M tokens$0.08/1M tokens
Latency~800ms~350ms

Choose o4-mini when:

  • ✓ Kundali scoring
  • ✓ Compatibility analysis
  • ✓ Decision systems
Key Strengths:

Fast reasoning, Cost-efficient, 200K context

Choose WizardLM 2 8x22B when:

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

Strong instruction following, Good math, MoE efficient

Verdict: o4-mini vs WizardLM 2 8x22B

For cost efficiency, o4-mini wins at $0.03/1M input tokens. For speed, WizardLM 2 8x22B is faster at ~350ms. o4-mini excels at Kundali scoring 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

o4-mini costs $0.03/1M input tokens and $0.12/1M output tokens. WizardLM 2 8x22B costs $0.04 input and $0.08 output. o4-mini is 1.3x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

o4-mini has a 200K context window with ~800ms latency. WizardLM 2 8x22B offers 65K context at ~350ms. o4-mini has the larger context window.

Best For

o4-mini (Reasoning) is optimized for: Kundali scoring, Compatibility analysis, Decision systems. 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 o4-mini
response_a = client.chat.completions.create(
    model="o4-mini",
    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

200+ AI models. One API. Pay-as-you-go.

Get API Key Try in Playground

Frequently Asked Questions

Which is better, o4-mini or WizardLM 2 8x22B?

o4-mini (Reasoning, ~200B) offers Fast reasoning. WizardLM 2 8x22B (Open Source, 176B (22B active)) offers Strong instruction following. Choose o4-mini for Kundali scoring or WizardLM 2 8x22B for Complex instructions.

How much does o4-mini cost vs WizardLM 2 8x22B?

o4-mini: $0.03/1M input, $0.12/1M 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 o4-mini and WizardLM 2 8x22B by changing the model parameter. No code changes needed.

Related Comparisons

o4-mini vs o3 o4-mini vs o3 Mini o4-mini vs Gemma 3 27B o4-mini vs Llama 4 Scout o4-mini vs Llama 4 Maverick o4-mini vs Llama 3.3 70B

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