Llama
Meta
FreePhi-4
Microsoft
FreeLlama vs Phi-4: Full Comparison (2026)
Llama is meta's open-source llm family - llama 4 with multimodal moe architecture. Phi-4 is microsoft's small language models - phi-4 leads slm benchmarks. Use the breakdown below to find the right fit for your needs.
This page presents factual information sourced from publicly available vendor documentation and product pages. AIHub does not endorse either product. The right tool depends on your specific use case, team, and requirements — we recommend evaluating both tools directly before making a decision.
Side-by-Side Overview
Pricing Model
Llama
FreePhi-4
FreeAPI Access
Llama
Not availablePhi-4
Not availablePlatforms
Llama
WebPhi-4
WebIntegrations
Llama
—Phi-4
—Vendor
Llama
MetaPhi-4
MicrosoftCategory
Llama
Language ModelsPhi-4
Language ModelsLaunch
Llama
—Phi-4
—Models
Llama
Llama 5 (Apr 2026, 600B+ params, multimodal), Llama 4 Maverick (17B active / 400B total)Phi-4
Phi-4 (14B), Phi-4-mini (3.8B)| Feature | Llama | Phi-4 |
|---|---|---|
| Pricing Model | Free | Free |
| API Access | Not available | Not available |
| Platforms | Web | Web |
| Integrations | — | — |
| Vendor | Meta | Microsoft |
| Category | Language Models | Language Models |
| Launch | — | — |
| Models | Llama 5 (Apr 2026, 600B+ params, multimodal), Llama 4 Maverick (17B active / 400B total) | Phi-4 (14B), Phi-4-mini (3.8B) |
About Llama
Llama is Meta's family of open-weight large language models. Llama 4 Scout (17B active params, 16 experts MoE) and Maverick (17B active, 128 experts) delivered top multimodal benchmarks at launch Apr 2025. Llama 3.3 70B remains the best open-source value for text tasks.
Designed For
- Self-hosted AI
- Fine-tuning for custom tasks
- Research
- Edge deployment
About Phi-4
Phi-4 (Dec 2024) is Microsoft's latest small language model at 14B parameters, surpassing GPT-4o mini and Gemini 1.5 Pro on STEM and reasoning benchmarks. Phi-4-mini (3.8B) and Phi-4-multimodal add vision and audio capabilities. Phi-4-reasoning (May 2025) adds chain-of-thought.
Designed For
- On-device AI
- Mobile apps
- Low-latency inference
- Cost-efficient deployment
Strengths & Limitations
Llama
Strengths
- Fully open weights
- Multiple size options (1B–400B)
- Commercial license
- Multimodal (Llama 4)
- MoE efficiency
Limitations
- Requires hosting infrastructure
- Large models need significant GPU RAM
Phi-4
Strengths
- Phi-4 14B beats much larger models on STEM
- Open weights (MIT license)
- Multimodal support
- Reasoning model available
- Runs on consumer hardware
Limitations
- Limited for very long documents
- Less well-known outside enterprise
Frequently Asked Questions
What is the difference between Llama and Phi-4?
Llama is meta's open-source llm family - llama 4 with multimodal moe architecture, while Phi-4 is microsoft's small language models - phi-4 leads slm benchmarks. Llama is designed for Language Models; Phi-4 is designed for Language Models. The right fit depends on your specific requirements.
How do the pricing models compare?
Llama is available under a Free model. Phi-4 is available under a Free model. Always verify pricing on each vendor's official website as it may change.
How do I choose between Llama and Phi-4?
Consider your team's technical requirements, budget, existing tooling, and use case before deciding. We recommend signing up for free trials or demos of both tools where available, and consulting each vendor's documentation. AIHub provides this comparison for informational purposes only.
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Data sourced from public vendor documentation. Pricing, features, and availability may change. Always verify on official vendor websites before making purchasing decisions. AIHub is not affiliated with any of the listed vendors.