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WizardLM-2 8x22BvsPhi-3 Medium

Microsoft vs Microsoft — Side-by-side model comparison

Tied — both models win in equal categories

Head-to-Head Comparison

MetricWizardLM-2 8x22BPhi-3 Medium
Provider
Arena Rank
Context Window
64K
128K
Input Pricing
Free (open)/1M tokens
Free (open)/1M tokens
Output Pricing
Free (open)/1M tokens
Free (open)/1M tokens
Parameters
176B (39B active)
14B
Open Source
Yes
Yes
Best For
Complex instructions, reasoning, coding
Balanced performance, reasoning, coding
Release Date
Apr 15, 2024
May 21, 2024

WizardLM-2 8x22B

WizardLM-2 8x22B is Microsoft's instruction-tuned mixture-of-experts model built on Mixtral 8x22B. It uses advanced training techniques to significantly boost instruction-following and reasoning capabilities beyond the base model. At launch, it was among the strongest open models for complex multi-step instructions and competitive coding tasks.

View Microsoft profile →

Phi-3 Medium

Phi-3 Medium is Microsoft's 14 billion parameter model in the Phi-3 family, offering a step up in capability from Phi-3 Mini while remaining efficient enough for deployment on consumer hardware. It demonstrates that careful data curation and training methodology can produce models that compete with much larger alternatives, particularly on reasoning and STEM-related tasks.

View Microsoft profile →

Key Differences: WizardLM-2 8x22B vs Phi-3 Medium

1

Phi-3 Medium supports a larger context window (128K), allowing it to process longer documents in a single request.

2

WizardLM-2 8x22B has 176B (39B active) parameters vs Phi-3 Medium's 14B, which affects inference speed and capability.

W

When to use WizardLM-2 8x22B

  • +Your use case involves complex instructions, reasoning, coding
View full WizardLM-2 8x22B specs →
P

When to use Phi-3 Medium

  • +You need to process long documents (128K context)
  • +Your use case involves balanced performance, reasoning, coding
View full Phi-3 Medium specs →

The Verdict

This is a close matchup. WizardLM-2 8x22B and Phi-3 Medium each win in different categories, making the choice highly dependent on your use case. Choose WizardLM-2 8x22B for complex instructions, reasoning, coding. Choose Phi-3 Medium for balanced performance, reasoning, coding.

Last compared: March 2026 · Data sourced from public benchmarks and official pricing pages

Frequently Asked Questions

Which is better, WizardLM-2 8x22B or Phi-3 Medium?
WizardLM-2 8x22B and Phi-3 Medium are closely matched, each winning in different categories. WizardLM-2 8x22B excels at complex instructions, reasoning, coding, while Phi-3 Medium is optimized for balanced performance, reasoning, coding. We recommend testing both for your specific use case.
How does WizardLM-2 8x22B pricing compare to Phi-3 Medium?
WizardLM-2 8x22B charges Free (open) per 1M input tokens and Free (open) per 1M output tokens. Phi-3 Medium charges Free (open) per 1M input tokens and Free (open) per 1M output tokens. For high-volume production workloads, the pricing difference can significantly impact total cost of ownership.
What is the context window difference between WizardLM-2 8x22B and Phi-3 Medium?
WizardLM-2 8x22B supports a 64K token context window, while Phi-3 Medium supports 128K tokens. Phi-3 Medium can process longer documents, codebases, and conversations in a single request. Context window size matters most for tasks involving long documents, large codebases, or extended conversations.
Can I use WizardLM-2 8x22B or Phi-3 Medium for free?
WizardLM-2 8x22B is a paid API model starting at Free (open) per 1M input tokens. Phi-3 Medium is a paid API model starting at Free (open) per 1M input tokens. Open-source models can be self-hosted for free but require your own GPU infrastructure.
Which model has better benchmarks, WizardLM-2 8x22B or Phi-3 Medium?
WizardLM-2 8x22B's arena rank is not yet available, while Phi-3 Medium's rank is not yet available. Note that benchmarks don't capture every use case — we recommend testing both models on your specific tasks.
Is WizardLM-2 8x22B or Phi-3 Medium better for coding?
WizardLM-2 8x22B is specifically optimized for coding tasks. Phi-3 Medium is specifically optimized for coding tasks. For coding specifically, arena rank and code-specific benchmarks are the best indicators of performance.