WizardLM-2 8x22BvsPhi-3 Mini
Microsoft vs Microsoft — Side-by-side model comparison
Head-to-Head Comparison
| Metric | WizardLM-2 8x22B | Phi-3 Mini |
|---|---|---|
| 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) | 3.8B |
| Open Source | Yes | Yes |
| Best For | Complex instructions, reasoning, coding | Edge deployment, mobile, on-device AI |
| Release Date | Apr 15, 2024 | Apr 23, 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 Mini
Phi-3 Mini is Microsoft's compact 3.8 billion parameter model that delivers surprisingly strong performance for its size, rivaling models many times larger on reasoning and coding benchmarks. It features a 128K context window despite its small size, making it ideal for on-device deployment in mobile phones, laptops, and edge devices where computational resources are severely constrained.
View Microsoft profile →Key Differences: WizardLM-2 8x22B vs Phi-3 Mini
Phi-3 Mini supports a larger context window (128K), allowing it to process longer documents in a single request.
WizardLM-2 8x22B has 176B (39B active) parameters vs Phi-3 Mini's 3.8B, which affects inference speed and capability.
When to use WizardLM-2 8x22B
- +Your use case involves complex instructions, reasoning, coding
When to use Phi-3 Mini
- +You need to process long documents (128K context)
- +Your use case involves edge deployment, mobile, on-device ai
The Verdict
This is a close matchup. WizardLM-2 8x22B and Phi-3 Mini 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 Mini for edge deployment, mobile, on-device ai.
Last compared: March 2026 · Data sourced from public benchmarks and official pricing pages